USMCA 201918th INTERNATIONAL SYMPOSIUM
ON NEW TECHNOLOGIESFOR URBAN SAFETY OF MEGA CITIES IN ASIA
9-10 December 2019
Yangon, Myanmar
11-12 December 2019Technical tour / Bagan, Myanmar

USMCA 2019

ICUS Report 2019-(serial No. 81)
the 18th International Symposium
on New Technologies
for Urban Safety of Mega Cities in Asia
October 9-12, 2019atYangon Technological University, Myanmar
Organized by
Yangon Technological University, Myanmar&
International Center for Urban Safety Engineering,
Institute of Industrial Science, The University of Tokyo, Japan
Sponsored by

Myanmar Engineering Society (MES), Myanmar

Super Global University (SGU) Project of UTokyo

Cooperated by
Japan International Cooperation Agency (JICA),SATREPS Office

SYMPOSIUM ORGANISERSCHAIRPERSON & CO-CHAIRPERSON

Prof. Nyan Myint Kyaw
Prof. Kimiro MeguroChairperson, Head, Dept. of Civil Engineering,
Yangon Technological University (YTU), Myanmar
Co-chairperson, Director, ICUS, IIS,The University of Tokyo (UTokyo), JapanSTEERING COMMITTEE

Prof. Myint Thein
Rector, YTU, Myanmar
Prof. Sint Soe
Rector, Mandalay Technological University, Myanmar
Mr. Aung Myint
President, Fed. MES, Myanmar
Prof. Mehedi Ahmed Ansary Bangladesh University of Engineering Technology (BUET), Bangladesh
Prof. Sudhir Misra
Indian Institute of Technology Kanpur, India
Prof. Emeritus Taketo Uomoto
UTokyo, Japan
Prof. Toshiharu Kishi
Director General, IIS, UTokyo, Japan
Prof. Wei Cheng Fan
Director, CPSR, Tsinghua University, China
Prof. Pennung Warnitchai
Head of Dept, of Civil and Infrastructure Engineering,
Asian Institute of Technology (AIT), Thailand
Prof. Emeritus Yoshifumi Yasuoka UTokyo, Japan
Dr. Haruo Sawada
President, Forestry and Forest Products Research Institute, Japan

TECHNICAL COMMITTEE

Dr. Khin Than Yu
Former Pro-rector, YTU, Myanmar
Prof. Tun Naing
Head, Dept. of Engineering Geology, YTU, Myanmar
Prof. Theingi Shwe
Head, Dept. of Architecture, YTU, Myanmar
Prof. Sao Hone Pha
Director, RS&GIS Research Center, YTU, Myanmar
Prof. Kiang Hwee Tan
National University of Singapore, Singapore
Prof. Pradeep Kumar Ramancharla International Institute of Information Technology, Hyderabad, India
Prof. Kimiro Meguro
Director, ICUS, IIS, UTokyo, Japan
Prof. Reiko Kuwano
ICUS, IIS, UTokyo, Japan
Prof. Wataru Takeuchi
IIS, UTokyo, Japan

ORGANIZING COMMITTEE

Prof. Htin Lin
Dr. Kyaw Zaya Htun
Dr. Kyaw Zin Latt
Ms. Tomoko MatsushitaCONTACT PERSON

Ms. Eiko Yoshimoto

Dept. of Mechatronic Engineering, YTU, Myanmar
Deputy Director, RS&GIS Research Center, YTU, Myanmar
Lecturer, Dept. of Engineering Geology, YTU, Myanmar
Project Researcher, ICUS, IIS, UTokyo, Japan

Project Specialist, ICUS, IIS, UTokyo, Japan

PREFACE
On behalf of the Organizing Institutes of the 18th International Symposium on New Technologies for
Urban Safety of Mega Cities in Asia (USMCA2019), I express our sincere welcome to all symposium
participants and distinguished keynote speakers.
In the Asia and Pacific-Rim regions, rapid economic development and population growth andconcentration are fast accelerating the pace of urbanization. Unfortunately, the rapid expansion of
infrastructure for urbanization is not adequately balanced with appropriate measures for their maintenanceand management; thus, big urban disasters have resulted.
The International Center for Urban Safety Engineering (ICUS) was established in 2001 at the Instituteof Industrial Science (IIS), the University of Tokyo (UTokyo). The objectives of ICUS are to carry out advanced
researches on urban safety and to implement safer cities especially in Asia and the Pacific-Rim region in the
21st century. For over a decade, ICUS has been actively tackling advanced researches, as well as theenhancement of networking, information collection and dissemination in order to fully realize ICUS’s vision.
As a part of ICUS activities, ICUS has been annually co-organizing USMCA since 2002 with its partners in the
Asian region.
In December 2019, ICUS jointly held the 18th USMCA in Yangon, Myanmar, with Yangon
Technological University (YTU). This was the second USMCA in Yangon. YTU and ICUS jointly establishedthe 5-year project in 2014 under the scheme of SATREPS (Science and Technology Research Partnershipfor Sustainable Development) with the support from JST (Japan Science and Technology Association) andJICA (Japan International Cooperation Agency). The title of the project is “Development of a Comprehensive
Disaster Resilience and Collaboration Platform in Myanmar” and its aims are to reduce future damage causedby floods including storm surges and earthquakes in Yangon City and the Bago River Basin, and to increase
the resilient capacity of the target areas. In order to achieve the goal mentioned above, research activities
have been carried out from the three viewpoints, i.e. structural measures (hardware), non-structural measures(software) and human capacity development. The year 2019 was the final year of the project, we had planned
the SATREPS especial sessions. In the sessions, approximately 30 papers were presented. Including these
papers, during the two-day symposium, 85 papers in eight parallel sessions were presented and four keynote
lectures were delivered. We also had research exhibitions in 10 booths. Totally about 150 people from 12
countries participated in the symposium. Following the symposium, two-day survey visit to Bagan, old capitalcity, were conducted with over 60 participants.
The objective of the USMCA symposium is to bring together decision makers, practitioners andresearchers involved in the field of urban safety to share their expertise, knowledge and experience in tacklingthe critical issues for safer cities in Asia and the Pacific Rim regions. It also provides an environment to create
and reinforce collaborative networks among experts in the fields relevant to urban safety. The symposium
focuses on urban safety and disaster mitigation, infrastructure management, and environment informatics.
I would like to thank all the members of the Steering, Technical and Organizing Committees as wellas the Symposium Secretariat for their hard work, time and effort in putting this symposium together. I would
also like to thank all our sponsors, especially Super Global University (SGU) Project of UTokyo that supported
us to prepare this Proceedings. Thanks are also due to all those who have contributed towards making this
symposium successful.

Professor Kimiro MEGURO
Director of ICUS, IIS, The University of Tokyo(Co-Chairman of Organizing Committee, USMCA2019)

PROGRAM OVERVIEW

Monday, 9 December
08:00 09:00
09:00 –
09:50

09:50 –
10:30
10:30 –
11:30

Registration in front of Assembly Hall
 Opening Ceremony at Assembly Hall
1. Welcome Address
2. Opening Address
3. Address by Co-Chair

Prof. Myint Thein Rector, YTU
Prof. Khin Than Yu
Prof. Kimiro Meguro, UTokyo

Group Photo – Exhibitions & Coffee Break Keynote Speech at Assembly Hall
1. Prof. Kimiro Meguro, Director,ICUS, IIS, UTokyo

Development of a comprehensive disaster resilience system andcollaboration platform in Myanmar
2. U Saw Htwe Zaw, Vice Chairman, Myanmar Earthquake Committee
11:30 –
12:30
12:30 –
14:30

14:30 –
15:15
15:15 –
17:05

18:00 –
20:00

Earthquake risk in Yangon
Lunch at top floor
 Session A: at Conference Room

 Session B: at Seminar Room 1

INFRASTRUCTURE MANAGEMENT:
MAINTENANCE AND SUSTAINABILITY /CONSTRUCTION MATERIALS ANDTECHNOLOGYURBAN SAFETY & DISASTER MITIGATION:
DISASTER MANAGEMENT, RECOVERY ANDREHABILITATION PLANNING, ENVIRONMENTINFORMATICS: TRANSPORTATION / BAGANHERITAG

Session Co-Chairs:
Dr.Koji Matsumoto, Hokkaido Univ.
Prof. Pennung Warnitchai AIT

Session Co-Chairs:
Prof. Pradeep Kumar Ramancharla
Hyderabad
U Saw Htwe Zaw, MEC

IIIT

Coffee Break & Exhibitions
 Session C: at Coference Room

 Session D: at Seminar Room 1

URBAN SAFETY & DISASTER
MITIGATION: DISASTER MITIGATION &URBAN PLANNING / EMERGENCYRESPONSE

SPECIAL SESSION: SATREPS/ DISATERMANAGEMENT / DISASTER MITIGATIONAND URBAN PLANNING

Session Co-Chairs:
Dr. Tsukasa Mizutani, UTokyo
Dr. Htay Win, YTU

Session Co-Chairs:
Prof. Takaaki Ikeda, NUT
Prof. Theingi Shwe, YTU

Banquet at Lakeside Lawn, Inyalake hotel

Tuesday, 10 December
09:00 –
10:40

 Session E: at Conference Room

 Session F: at Seminar Room 1

URBAN SAFETY & DISASTER
MITIGATION: RISK ASSESSMENT

SPECIAL SESSION: SATREPS/
TRANSPORTATION, INFRASTRUCTURE
MANAGEMENT

Session Chair:Dr. Makoto Fujiu Kanazawa Univ.
Prof. Tun Naing, YTU

10:40 –
11:10
11:10 –
12:50

12:50 –
14:00
14:00 –
15:00

Session Co-Chairs:
Dr. Junichi Susaki, Kyoto Univ.
Direcotr Sao Hone Pha, YTU

Coffee Break & Exhibitions
 Session G: at Conference Room

 Session H: at Seminar Room 1

ENVIRONMENT INFORMATICS:
GIS/REMOTE SENSING,
TRANSPORTATION, WATERRESOURCES, INFRASTRACTURE
MANAGEMENTSPECIAL SESSION: SATREPS/ WATERRESOURCES, DISASTER MITIGATIONAND URBAN PLANNNING

Session Chair:
Dr. Yudai Honma, UTokyo
Prof. Khin Maung Zaw, YTU

Session Chair:Prof. Osamu Murao, Tohoku Univ.
Prof. Kyaw Kyaw, YTU

Lunch at top floor Keynote Speech at Assembly Hall
1. Dr. Takayuki Miyoshi, Urban and Spatial Development Division, Nippon Koei Co., Ltd.

Bagan Tourism Development Project (2014-2018)
2. Dr. Toe Aung, Director, Yangon City Development Committee

Urban safety for Mega City, Yangon
15:00 –
15:30
15:30 –
16:30

18:30 -

Coffee Break & Exhibitions
 Closing Ceremony at Assembly Hall
1.
2.
3.
4.

Young Award Ceremony
Announcement of USMCA2020 Prof. Pennung Warnitchai AIT
Closing SpeechProf. TunNaing, YTU
Closing SpeechProf. Kimiro Meguro, UTokyo

Farewell Dinner at 9th floor Esperade lake view hotel
Wednesday, 11- Thursday, 12 December
Technical Tour at Bagan

CONTENTS
KEYNOTES:
1. Prof. Kimiro Meguro
Development of a comprehensive disaster resilience system and collaboration platform in
Myanmar ........................................................................................................................................ 2
2. Dr. Takayuki Miyoshi
Bagan Tourism Development Project (2014-2018) ................................................................. 4

SESSION A:
INFRASTRUCTURE MANAGEMENT: MAINTENANCE AND SUSTAINABILITY /CONSTRUCTION MATERIALS AND TECHNOLOGY
1．

Kazuya Kusaba
Inspection method for facilities in Tokyo Metro stations ..................................................... 6

2．

Tsukasa Mizutani and Tetsuya Ishida2-Dimensional pavement condition evaluation by spatial frequency analysis of point
cloud data ................................................................................................................................ 14

3．

Daisuke Tanaka
Educating system of tunnel soundness diagnosing skill with AR technology ............... 15

4．

Shinji Konishi
Large scale ground reinforcement for improvement of subway stations ....................... 19

5．

Tomotaka Fukuoka, Takahiro Minami, Makoto Fujiu and Junichi Takayama
Evaluation of image processing-based crack detection under real environment for
remote imaging inspection with AI ....................................................................................... 27

6．

Takahiro Yamaguchi, Tsukasa Mizutani and Minoru Tarumi
Subsurface pipe detection by 3D convolutional neural network and Kirchhoff migration.................................................................................................................................................. 28

7.

Naoto Ishimura, Takahiro Minami, Makoto Fujiu, Tomotaka Fukuoka
and Junichi Takayama
Fundamental study on detection of floating area of mortar sprayed surface using
infrared camera mounted on UAV and AI ........................................................................... 36

8.

Takahiro Minami, Makoto Fujiu, Tomotaka Fukuoka and Junichi Takayama
Development of crack detection and soundness diagnosis system for remote imaging
inspection with AI .................................................................................................................... 37

9．

Sothyrak Rath, Pakawat Sancharoen, Pitichon Klomjit and Somnuk Tangtermsirikul
Electrochemical properties of reinforcing steel corroded by carbonation ...................... 38

10． Arian Ghaemi, Reiko Kuwano and Masahide Otsubo
Investigating suffusion behavior of gap-graded soils using segregation experiments............................................................................................................................................................. 46
11.

Matsumoto Koji, Yushi Meng and Kohei Nagai
Meso-scale discrete analysis of concrete damaged by delayed ettringite formation ... 47

12.

Jiradilok Punyawut, Kumar Avadh and Kohei Nagai
Effect of stirrup confinement on the residual bond performance of corroded RC by 3D
RBSM ....................................................................................................................................... 48

SESSION B:
URBAN SAFETY & DISASTER MITIGATION: DISASTER MANAGEMENT,RECOVERY AND REHABILITATION PLANNING, ENVIRONMENT INFORMATICS:
TRANSPORTATION / BAGAN HERITAGE
1.

Hiroto Suzuki
Earthquake countermeasures of Shinkansen and their outcomes ................................. 60

2.

Hla Hla Aung
The religious buildings in Bagan and the 2016 M 6.8 subduction zone earthquake in
Myanmar ................................................................................................................................... 68

3．

T.M. San and K.Kyaw
Investigation on ancient brick masonry and repair mortar properties in post-earthquake
rehabilitation process of ancient Bagan monuments ........................................................ 77

4．

Kimiro Meguro
Lessons learnt from the damage and response of the 2016 Kumamoto Earthquake inJapan ........................................................................................................................................ 85

5．

Masahide Otsubo, Umair Ali and Reiko Kuwano
Insights into stability of subsurface cavity using discrete element method simulations
and laboratory model tests .................................................................................................... 89

6.

Pinglan GE, Hideomi Gokon, Kimiro Meguro and Shunichi Koshimura
Analyses on landslide extraction by synthetic aperture radar single look complex
images ...................................................................................................................................... 90

7． Gadagamma Chaitanya Krishna, Muneyoshi Numada and Kimiro Meguro
A feasibility study on the scaling of operational mode shapes of building using a shaker.................................................................................................................................................. 91
8．

Yuma Morisaki, Makoto Fujiu, Ryoichi Furuta, Takashi Sakai Kazuhiro Nagaki, Junichi
Takayama and Yuto Shiozaki
A study on the methods of understanding vulnerable people’s needs using satellite
SAR image .............................................................................................................................. 92

9.

Ryo Itoh, Kimiro Meguro and Muneyoshi Numada
Survey of reconstruction projects in Japan and making the database for disaster
response work ....................................................................................................................... 93

10.

Daisuke Watanabe
A study on analyzing road network patterns and proximity graphs in terms of efficiency
in road transportation ........................................................................................................... 94

11.

Shoichi Uemura, Hiroto Suzuki and Hiroyuki Miyakoshi
Statistical analysis of relation between seismic motion and viaduct damage inconsidering efficacy of seismic reinforcement .................................................................. 95

SESSION C:
URBAN SAFETY & DISASTER MITIGATION: DISASTER MITIGATION & URBAN
PLANNING / EMERGENCY RESPONSE
1.

Tazuyuki Takada, Kazufumi Kawabata, Hitomi Murakami and Maki Koyama
Analysis of artificial evacuation mound placement on residents’ consciousness of
Tsunami evacuation .............................................................................................................. 104

2.

Hnin Su Mon Win and Theingi Shwe
A case study on land-use and transport relationship in Yangon ............................................... 105

3.

Ryo Fujii, Makoto Fujiu, Junichi Takayama and Yuto Shiozaki
Basic analysis of aircraft divert destination selection during large-scale natural disasters
using air traffic control data -Considering the vulnerability of the airport- ............................ 112

4.

Jaeho Kim, Toshio Eda, Ippei Harada, Kazufumi Ayukawa, Tadahiro Mukai
and Takaaki KatoDevelopment of agent-based flood evacuation simulation for supporting local
government evacuation planning ........................................................................................ 113

5.

Takahisa Minami and Takaaki Kato
How much does social networking service affect the evacuation efficiency? - A study
using agent-based simulation ............................................................................................. 114

6.

Madisetti Pavan Kumar, G.K. Chaitanya and K. Rambabu
Collapse analysis of R.C buildings subjected to blast load using AEM ........................ 115

7.

Hiroko Watanabe, Yudai Honma, Kentaro Honma and Kotaro Imai
Evaluation of urban sunshine environment by shadow simulation ............................... 116

8.

Silpa Chowdary Sadineni and Kimiro Meguro
Numerical study on effect of new seismic retrofitting method to mitigate the damage in
non-ductile RC frame with masonry infill walls ................................................................. 117

9.

Tingshen Tan, Reiko Kuwano, Ryoko Sera and Mizuki Kinjou
Development of subsurface cavity filling material ............................................................ 118

10.

Gen Hayamizu, Yuma Morisaki, Takahiro Minami, Makoto Fujiu, Yuto Shiozaki
and Junichi Takayama
Returning home behavior analysis of New Chitose Airport users who were affected by
the 2018 Hokkaido Eastern Iburi Earthquake ................................................................... 119

11.

Takashi Sakai, Yuma Morisaki, Makoto Fujiu, Junichi Takayama, Yuto Siozaki,
Kiyoko Yanagihara, Tatsuya Nisino, Masahiko Sagae and Kohei Hirako
Basic study on the difficulty of evacuation in the region that considered geographicalcharacteristic .......................................................................................................................... 120

SESSION D:
SPECIAL SESSION: SATREPS/ DISATER MANAGEMENT / DISASTER
MITIGATION AND URBAN PLANNING
1.

Tun Naing, Su Thinzar and Aung Myo Zaw
Determination of site condition based on microtremors survey and boring data in threeselected townships of Yangon, Myanmar ............................................................................ 122

2.

Hideomi Gokon, Takaaki Kato, May Myat Mon, Tun Naing, Muneyoshi Numada

and Kimiro Meguro
Investigation of disaster response activities of administration offices of Yangon City ................. 130
3.

May Myat Mon, Tun Naing, Kyaw Zin Latt, Muneyoshi Numada, Khin Than Yu andKimiro Meguro
Slope modeling for future slope stability in Hakha City, Chin State, Myanmar ............. 131

4.

Khin Myat Kyaw and Kimiro Meguro
Soil-structure-interaction effects on the damage state of typical buildings in Yangon ................ 141

5.

Su Thinzar and Tun Naing
One-dimensional seismic response analysis by equivalent linear method in Kyauktada,
Pazundaung and Botahtaung Townships,Yangon, Myanmar .......................................... 142

6.

San San Moe
Overview of urban growth and Yankin redevelopment towards sustainable land use planningin Yangon .................................................................................................................................................. 150

7.

Takumi Matsumoto, Takaaki Ikeda, Hideomi Gokon, Atsuya Minagawa, Tun Naing andOsamu Murao
Estimation of site amplification factor in Yangon City ..................................................................... 151

8.

Atsuya Minagawa, Takaaki Ikeda, Hideomi Gokon, Takumi Matsumoto and Tun Naing
Study on amplification factor of maximum acceleration for seismic hazard assessment................................................................................................................................................... 152

9.

Eiei Tun, Tintin Aye, Takaki Kato and Tomoko Matsushita
Developing evacuation areas in Yangon for emergency response with GIS system ... 153

10. Tomoko Matsushita, Aya Kubota and Kimiro Meguro
A study of evacuation risk in the central business district of Yangon City and discussion
on the role of back drainage space ...................................................................................... 161

SESSION E:
URBAN SAFETY & DISASTER MITIGATION: RISK ASSESSMENT
1.

Pradeep Kumar RamancharlaLong term measures for earthquake disaster safety in developing countries of Asia .. 164

2.

Shuji Osawa, Jyunichi Takayama, Makoto Fujiu and Yuto Shiozaki
A Study on definition to natural disaster-dangerous points on road that aim to upgrade
the evaluation of disaster resistance on road-network .............................................................. 166

3.

Aye Aye Mar, Kyaw Kyaw and Takeshi Koike
Seismic vulnerability assessment of lifeline system in Myanmar .................................... 167

4.

Yusuke Nakata, Reiko kuwano, Masahide Otsubo and Umair Ali
A fundamental study on dynamic wave propagation in soil around a cavity ............................ 174

5.

Itsuki Sato and Reiko Kuwano
Unsaturated shear characteristics of extremely loose volcanic soil causing slope disaster.................................................................................................................................................... 182

7.

Kota Horiuchi and Michael Henry
Relationship between inequality, education, and disaster experience at the household
level in Yangon City, Myanmar ............................................................................................... 183

8.

Sera Ryoko and Reiko Kuwano
Development of subsurface cavity potential map for effective road cave-incountermeasures .................................................................................................................... 191

9.

Tetsuro Ito
Issues on crisis management at the Tokyo Olympic Games ........................................... 193

SESSION F:
SPECIAL SESSION: SATREPS/ TRANSPORTATION, INFRASTRUCTURE
MANAGEMENT
1.

Kyaing, Ko Ko Lwin and Yoshihide Sekimoto
Analysis of transit behaviors using mobile call detail records .......................................... 196

2. Emmanuel and Kyaing
Economic and operational analysis of public transportation in Pathein Township ......... 204
3. Thiri Aung, Kyaing and Ko Ko Lwin and Yoshihide Sekimoto
Analysis on the effect of land use and socioeconomic characteristics on travel behavior.................................................................................................................................................... 212
4. Hiroyuki Hasada and Yudai Honma
Optimization model to estimate cognitive distances from travel data .............................. 213
5. Yudai Honma and Kimiro Meguro
Mathematical relationship between minimization of travel-time and detouring behavior on grid
networks: A case study of Yangon downtown .............................................................................. 222
6.

Hein Thura Aung, Sao Hone Pha and Wataru Takeuchi
Optimization of building footprint extraction model with color and texture analysis
in Yangon city .......................................................................................................................... 229

7.

Khin Maung Zaw, Win Bo, Amy Aung, K, Matsumoto and K. Nagai
Monitoring results of Pathein Bridge towers and bearings ............................................... 238

8.

Yoshito Yokoe, Takaaki Ikeda, Takumi Matsumoto and Atstuya Minagawa
Seismic hazard assessment in Yangon City using the empirical earthquake evaluation
method ...................................................................................................................................... 239

9.

Haruki Suzuki, Takaaki Ikeda and Yukiko Kojima
Effect of surface ground characteristics on structural damage ........................................ 240

10. Takaaki Ikeda
Source modeling and ground motion simulation of the mid-scale crustal earthquake................................................................................................................................................... 241

SESSION G:
ENVIRONMENT INFORMATICS: GIS/REMOTE SENSING, TRANSPORTATION,
WATER RESOURCES, INFRASTRACTURE MANAGEMENT
1.

Yukiya Taniguchi and Muneyoshi Numada
Extraction of damage situation in Yamagata coast earthquake using UAV ................... 244

2.

May Pyai Sone Win
Study on impacts of parking on congestion by different parking management systems................................................................................................................................................... 250

3.

Moe Thet Thet Aye and Kyaing

Economic analysis of highway improvement (Case study: Yangon-Bago Highway) ... 255
4.

Myint Myat Oo, Cho Cho Thin Kyi and Win Win Zin
Study on channel migration assessment in bridge areas along Ayeyarwady River ..... 256

5.

Seemanta Sharma Bhagabati, Akiyuki Kawasaki and Michihiro Ogawa
Improving historical reanalysis dataset for hydrological modelling by integrating limited
observed data and bias correction ....................................................................................... 257

6.

Htet Wai Yee Aung and Kyaw Kyaw
Study on code of practices for qualitｙ control, health and safety management inconstruction industry ............................................................................................................... 258

7.

Yuichiro Kawaguchi, Masahide Otsubo and Reiko Kuwano
Development of cubic soil chamber fitted with multi-directional disk transducers ........ 266

8.

Reiko Kuwano, Yu Ohara and Naoto Kominami
Formation and expansion of subsurface cavity and its potential risk of collapsing ...... 267

9.

Jiro Kuwano and Albano Acacio Ajuda
Shaking table tests on effect of reinforcement stiffness arrangement on seismic stability ofgeogrid reinforced soil walls ..................................................................................................... 268

SESSION H:
SPECIAL SESSION: SATREPS/ WATER RESOURCES, DISASTER MITIGATIONAND URBAN PLANNNING
1.

Win Win Zin
Climate change scenarios in Myanmar using MRI-AGCM3.2S model ........................... 270

2.

Wai Toe, Win Win Zin, Zin Mar Lar Tin San and Akiyuki Kawasaki
Development of flood inundation map using HEC-HMS and HEC-RAS ........................ 271

3.

Badri Bhakta Shrestha and Akiyuki Kawasaki
Flood risk assessment based on quantification of flood damage ................................... 291

4. Sann Win Maung, Zin Mar Lar Tin San, Win Win Zin and Akiyuki Kawasaki
Estimation of flood discharge using with WEB-DHM model in Bago River Basin .......... 292
5. Wai Yan Soe and Kyaw Kyaw
Seismic risk assessment of existing timber building: A case study of Pyay hostel inYangon University .................................................................................................................... 300
6.

Osamu Murao, Takaaki Ikeda, Mikio Koshihara, Kimiro Meguro and Theing Shwe
Difference in building collapse risk in Yangon due to applicable dataset ....................... 309

KEYNOTESMyAnmar Nippon Zero-casualty Engineering Network (ANZEN)
Project Science and Technology Research Partnership for Sustainable
Development (SATREPS)

1

Kimiro MEGURO1 and Khin Than Yu2
Director and Professor, ICUS, Institute of Industrial Science,
The University of Tokyo, Japanmeguro@iis.u-tokyo.ac.jp
2Ex-Pro-Rector, Yangon Technological University, Myanmar

ABSTRACT
Myanmar is a country where natural hazards, such as cyclones and earthquakes, occur frequently, but
preparations for natural hazards are not enough. Cyclone damage occurs every year, and the threemajor cities of Myanmar, Yangon, Naypyidaw, and Mandalay are all located along the Sagaing fault,
which is a major active fault.
Furthermore, with the support of many countries through the transition to democratization,
development of urban areas is rapidly progressing. But due to the lack of consideration for disasters,
these developments has been increasing the vulnerability against natural hazards and there is highpossibility to have serious damage in future. When a city is developed once, it is difficult and needs
more time and budget to reduce disaster risk. Now is a very important time to improve the city's disaster
resilience, and missing this opportunity will create major problems in the future.
Thus, we have established this project with the aim of reducing future damage caused by floods
including storm surges and earthquakes in Yangon City and the Bago River Basin. In order to achieve
the goal mentioned above, from the three viewpoints, i.e. structural measures (hardware, maintenancetechnology based on vulnerability assessment of structures and maintenance management technology),
non-structural measures (software, near real time flood inundation simulation system using monitored
rainfall, disaster response support system) and continuation environment of research activity, we
designed the 5-year (2014-2020) project under the scheme of SATREPS* (Science and Technology
Research Partnership for Sustainable Development) with the support from JST (Japan Science andTechnology Association) and JICA (Japan International Cooperation Agency). Nick name of our
project is ANZEN (MyAnmar Nippon Zero-casualty Engineering Network) SATREPS project. The
meaning of ANZEN is safety and security and it corresponds to our goal that we want to implement
safer and securer Yangon society.
The research flow is as follows: 1) Create an integrated inventory database composed of structures,
soil and ground information, rainfall, traffic and people flow, etc. by using the equipment provided by
the project and by collecting existing data. Next, 2) Using these data, create a physical model toestimate damage due to flood and earthquake. 3) By combining this physical model with the future
urban development model, prepare an environment in which the future urban planning can be
examined from the amount of damage that changes due to different urban development scenarios. As
final research results, 4) Develop a near real-time flood inundation simulator for the Bago River Basin,2

a support system for disaster management planning and disaster response, and a technology formonitoring, maintaining and repairing infrastructure and buildings to reduce their damage. And thelast, 5) In order to promote the understanding of project, continuation of research activities, andcontinuous utilization of the research results, develop lectures on urban safety in YTU, establish a
Research Center, and a consortium aiming industry-government-academia collaboration.
As the year of 2019 is the final year of our 5-year project, we already obtained a lot of research results
and these results will be introduced at the USMCA 2019.
Keywords: SATREPS Project, ANZEN SATREPS Project, Disaster Resilience, YTU and UTokyo*: The SATREPS project is a project supported by JICA and JST. The project aims to achieve thefollowing three points through collaboration between JST and JICA. Since April, 2008, 145 projects
have been implemented in 51 countries around the world. Our project, ANZEN SATREPS projectis the first adopted one in Myanmar. The total research fund is about 500 million yen and annual
budget is 100 million yen (35 million yen from JST, 60 million yen from JICA)
1. Strengthening international cooperation on science and technology development between Japanand developing countries
2. Acquisition of new knowledge and technologies that lead to the resolution of global issues andthe improvement of science and technology, and creation of innovations through them
3. Capacity development

3

Bagan Tourism Development Project (2014-2018)
Takayuki Miyoshi
Urban and Spatial Development Division, Nippon Koei Co., Ltd.
miyoshi-tk@n-koei.jp
ABSTRACT
Bagan became the UNESCO World Heritage Site in 2019. Before the nomination, JICA conducted
technical transfer project for tourism development with the cooperation of the Myanmar Government.
Through 14 pilot projects for tourism management, infrastructure and human resource development,
JICA established a tourism management plan toward sustainable tourism.

4

SESSION AINFRASTRUCTURE MANAGEMENT: MAINTENANCE AND
SUSTAINABILITY / CONSTRUCTION MATERIALS ANDTECHNOLOGYManagement method of inspection information
for station facilities in Tokyo Metro stations
Kazuya KUSABA1, Kotaro KURAMOTO2,
1
Chief of Architectural Section Infrastructure Maintenance Department,
Tokyo Metro Co.,Ltd., Japank.kusaba@tokyometro.jp
2
Deputy Manager of Architectural Section Infrastructure Maintenance Department,
Tokyo Metro Co.,Ltd., Japan
ABSTRACTTokyo Metro comprises 9 lines, 195.1km of commercially operating track, and 179 stations,with a ridership of about 7.42 million persons per day.
The Tokyo Metro is the oldest subway system in Japan. When the Tokyo Metro began
operations, the station buildings were finished paint on the civil engineered structures orother simple materials. Now, almost all the stations are given full interior finishing, and there
are various disaster prevention equipment.
Falling and floating of them and equipment failures lead to operational problems and injuries
to station customers. To prevent these accidents, maintenance of the station facilities iscarried out by the following procedure.
1 Inspection and soundness judgment of station facilities
2 Management of inspection information
3 Implementation of repair
This report describes the management method of inspection information for station facilities
carried out by Tokyo Metro, and the effects.
Keywords: Subway station, Maintenance, Inspection method, Soundness Judgment,
1. INTRODUCTION
In Japan, the inspection of external walls is mandatory due to the high risk of falling objects,
there is no legal requirement for the inspection of interior materials. However, Tokyo Metro isvoluntarily performing inspections, because a falling object in a station can cause tremendous
inconvenience to station users.
About interior finish, in addition to the annual visual inspection, we do contact inspection
once in two years. About station equipment, we set inspection cycle of each equipment andcarry out it. Based on the results of this inspection, we make a soundness judgment and carryout repair or follow up.
Previously, the information of these inspections was kept in documents, but it is a hugeamount, so there is a concern that items to be observed may be overlooked.
Therefore, in order to eliminate the accident caused by the overlooking, we constructed anefficient management method of the follow-up observation items with a tablet and cloudsystem.

6

Management method of inspection information for station facilities in Tokyo Metro stations

December 2019, Yangon, Myanmar

2.INSPECTION ITEMS AND METHOD OF STATION FACILITIESInspection items have been defined for all materials in all parts, including contact inspection
and numerical measurement. Some of the major items are described in Figure 1.
Table 1. Major Inspection Items of interior finish

Part

SpacesObjects

Spandrel,aluminumpanel, etc.

Platform
Concourse
Room forhuman
occupation
Ceiling
Concourse

Track area

Scope ofinspection

Inspection
methods

100%

Prodding(@900mm)

Ceiling
substrate

PartialVisualinspection
from allinspection
hatches

Inspection
port

100%

Opening +contact
inspection

Crossparting

100%

Retighteningof screws

Mortar100%

Hammering

Inspection
scene

Inspection items
・Detachment of
clip
・Installation
condition ofsuspending bolts
・Missing screws,
etc.
・Embedding
condition of inserts
・Detachment ofclip, etc.
・Lifting ofstructural concrete(hammering tests
within the reach)・Detachment of
clip
・Installation
condition ofsuspending bolts
・Other, including
wobbliness・
Loosening/corrosionof screws
・Expansion ofscrew holes
・Lifting, bulging
・Cracks/fractures
・Other, including
wobbliness

Management method of inspection information for station facilities in Tokyo Metro stations

7

Part

SpacesObjects

Tile
MortarWall

100%

Inspection
methods

Wall Platform

100%

Pulling withsuckers

・Wobbliness・Missingscrews・Corrosion

100%

Retighteningof screws andpushing in

Floor
stone

100%

VisualFloor

Platform
Concourse

Incidental facilities

Threesided door
frames,coping(stone,metal)
Platform
Concourse

Signs

Toiletbooths

100%

100%

100%

100%

Inspection items

Hammering

Suspended
wall

TactilepavingInspection
scene

・Lifting/bulging
・
Cracks/fracture
・Movement
during contact
inspection

Platform
Concourse
Metal
plate
Stone

8

Scope ofinspection

・Loosening ofscrews・Condition ofscrew holes
・Chipping andcracking of board
・Differences inlevel
・Chipping andcracking
・Wear

Visual・Differences in
level
・Wear
・Discoloration

Shaking・Wobbliness・Chipping andcracking

Shaking・Wobbliness・Chipping andcracking

Shaking・Wobbliness・Missingscrews・Corrosion

Management method of inspection information for station facilities in Tokyo Metro stations

December 2019, Yangon, Myanmar

In addition to these inspections, we also inspect water supply / drainage facilities,
Entrance/exit facilities and disaster prevention facilities to maintain their functions.
Table 2. Inspection of other facilities
facilities

Water
supply/drainage
facilities

Item

Cycle ofinspection

Inspection items

Tank to catch Once a
water
year

・disinfection・cleaning・water analysis

Boosterpump

Once ayear

・visual inspection
・function test

3 times ayear

・visual inspection
・operation test・controller check・mover check

Once ayear

・visual inspection
・operation test・controller check・mover check

Automatic
door
Entrance/exit
facilities

Shutter

Fire alarm

Disasterprevention
facilities

Inspection
scene

Twice ayear

Fire
Twice aextinguishingyear
Equipment
Antiinundation
MeasureEquipment

Once in 2
years

・visual inspection・equipment check・operation test

・equipment check・performance test・component inspection

Management method of inspection information for station facilities in Tokyo Metro stations

93.EVALUATION CRITERIA
We use a 6-level evaluation to eliminate the effect of bias among individuals, so that the
progression of deterioration may be monitored under standardized conditions(Table 3). In
addition, a time limit for repair was defined for each level to ensure the timely
implementation of necessary repairs.
Table 3: Risk Levels
Soundness
AA
A1

The impact of driving safety on safety
threaten
Threaten early

A2

Threaten in the futureB

If progressed, move to A

CS

No effect so far
No abnormality

Measures
Immediate repair
Repair within 1 year
Observation
Repair within 3 years is advisable
Observation
Monitoring of the progression ofdeterioration
Observation
No abnormality

follow-up
Evaluation
meeting

Inspection

Final
judgment
RepairFigure 2: Flow from Inspection to Repair
4. INSPECTION INFORMATION MANAGEMENT METHOD
Although it was managed on paper media, there was a possibility that various problems would
occur due to the huge amount of information (Table 4).
Table 4: problem on paper-based management system
Content
Data storage
Items
at inspection
Reportcreation time
Inspection item

10

amount179 stations Filing book
About 90 books
Number of drawings (10~ 20 sheets)
Past inspection data (250sheets)
Inspection tool (camera/ Test hammer/
measure etc.)
2 months after inspection
Per station250 items =44,750 items at 179 stations

Possibility of problems
Increased storage space
Oversight offollow-up items
Delayin construction planning
Neglect to donecessary repairs

Management method of inspection information for station facilities in Tokyo Metro stations

December 2019, Yangon, Myanmar

Therefore, in order to maintain right situation, we started inspection with a tablet andmanagement method with cloud system (Figure 3).

Figure 3: Information Management method with Cloud system
5. CASE (INSPECTION WITH TABLET)
5.1 Download past examination information to tablet
Download the floor plan and past inspection information (follow-up items) of the station to beinspected before the inspection starts in advance
5.2 Field inspection
5.2.1 Tablet input of results of palpation / sounding test

Figure 4: Input screen of inspection result and soundness

Management method of inspection information for station facilities in Tokyo Metro stations11

If an abnormality is found, it is registered in the tablet according to the criteria in Table 3(Figure 4).
5.2.2 Check the progress and register the soundness of follow-up items

Figure 5: screen of follow-up items
The past examination information is displayed as points on the tablet plan view, and thecontents are displayed by tapping the points.
As a result of the inspection, the health information is automatically registered in the server
via the Internet line from the tablet for items that have been judged as AA (emergency
measures) as a result of the inspection, and the person in charge of the inspection confirms theorder for emergency measures construction
5.3 Determination of soundness
Regarding the soundness level, we will determine the final soundness level of the inspection
information conducted in the local area, taking into consideration the structure and impact on
the customer, and carry out repairs according to the soundness level.
5.4 Flow until construction
The determined soundness level is repair work or follow-up depending on the level (Fig. 2).
For repair work, the inspection information is sent to the repair work implementer and thework is performed. When carrying out construction work, it was possible to monitor the
progress of construction of parts that required repair as a result of inspection in cooperation
with the construction management system.

Figure 6: Screen of construction management system

12Management method of inspection information for station facilities in Tokyo Metro stations

December 2019, Yangon, Myanmar

6. EFFECT
By managing cloud-based inspections and inspection data from tablets based on paper-based
inspections, as shown in (Table 5), it is possible to reduce the storage location, the amountbrought in at the time of inspection and the reporting time, as described in (Table4). Management issues have also been resolved. In addition, by managing the inspection
information in the cloud, all employees involved in building maintenance can check theinspection information in real time, leading to more accurate building maintenance.
Table 5: effectproblemamountContent
Datastorage
Items at thetime ofinspection

Reportcreationtime
Inspectionitem

effectPossibility ofproblems
179 stations Filing Increased storage Server room installation only
book
space
No storage space expansion
About 90 books
Numberof Oversight of
Displays all station drawings
drawings(10~20
follow-up items
and past inspection
sheets)information on a tablet
Past
inspection
There are 0 paper items
data(250sheets)(drawings and inspection
Inspection
information)
tool(camera/ Test
hammer/ measureetc.)
2monthsafter Delay in
Immediate reporting after
inspection
construction
inspection
planning
Per station250 items Neglect to do
Reliable repair work=
necessary repairs
44,750 items at 179
stations

7. PRESENT ISSUES
By managing inspection information in the cloud, management of accurate inspection
information has been performed. However, there are many inspection items and criteria when
inputting inspection information using a tablet, and the tablet operation is partly
complicated. In some cases, it may take time to enter inspection information. In the future,
we want to improve the visibility and operability of the screen so that the tablet can be
operated intuitively.

Management method of inspection information for station facilities in Tokyo Metro stations13

2-DIMENSIONAL PAVEMENT CONDITION EVALUATION BY SPATIAL FREQUENCYANALYSIS OF POINT CLOUD DATA
T. MIZUTANI1, T. ISHIDA2, K. SUZUKI3, Y. TAKAHASHI4, Y. NAGATA5, H. KAWAMURA6
Associate Professor, Institute of Industrial Science, , The University of Tokyo, Tokyo, Japan, mizu-t@iis.u-tokyo.ac.jp
Professor, Department of Civil Engineering, School of Engineering, The University of Tokyo, tetsuya.ishida@civil.t.utokyo.ac.jp
3
Aero Asahi Company, Tokyo, Japan, kiyoshi-suzuki@aeroasahi.co.jp
4
Aero Asahi Company, Tokyo, Japan, youji-takahashi@aeroasahi.co.jp
5Shutoko Engineering Company Limited., Tokyo, Japan, y.nagata@shutoko-eng.jp
6Shutoko Engineering Company Limited., Tokyo, Japan, h.kawamura@shutoko-eng.jp
1

2

Keywords: 2-Dimensional Pavement Condition Evaluation, Short Time Fourier Transform, Spatial Frequency Analysis,
Point Cloud Data, Mobile Mapping System
In this research, we propose the usage of On-Vehicle
Ranging Laser System, so called “Mobile Mapping
System (MMS)” (Figure1) to conduct 2-dimensional
pavement condition evaluation. MMS can obtain 3dimensional coordinate data (3-D point cloud data) of
surrounding objects by measuring while rotating Lasers
and driving (Figure2 and Figure3). After extracting onlyroad surface data, we mainly detect local deterioration
two-dimensionally by removing noise and unnecessary
deformation on road surface via Short-Time Fourier
Transform (STFT). STFT can be used to estimate
Frequency Spectrum of non-stationary data. Considering
space as time, road surface data can be also treated as nonstationary data. In this presentation, we report the detail ofthe signal processing using STFT and show its processing
can detect the local deterioration on road surface withhigh-accuracy. In addition, we show the estimate result of
IRI (road roughness index) and rutting (Figure4).

Figure 3: Road Surface Data Sample Extracted from 3-D
Point Cloud Data[1]Figure 1: Mobile Mapping System (MMS)
Figure 4: Spatial Frequency Analysis Result Sample

Figure 2: 3-D Point Could Data Measured by Mobile
Mapping System

14

REFERENCES[1] Hirotaka HIRANO, Tsukasa MIZUTANI, Tetsuya
ISHIDA, Satoshi ANNAKA, Kiyosi SUZUKI,“Evaluation of Local Deterioration of Pavement Surface
by Spatial Frequency Analysis Based on Short-Time
Fourier Transform,” Journal of Japan Society of Civil
Engineers, Ser. E1 (Pavement Engineering), Volume 74,
Issue 3, pp. I_113-I_120, 2018. (in Japanese)Development of AR-based Training System for
Tunnel Soundness Evaluation
Daisuke TANAKA1, Yuuki ENOKIDANI2, Naoya IMAIZUMI3and Shinji KONISHI4
1
Subhead of Structure Division Engineering Department, Tokyo Metro Co.,Ltd., Japand.tanaka@tokyometro.jp
2
Chief of Structure Division Engineering Department, Tokyo Metro Co.,Ltd., Japan3
Deputy Manager of Structure Division, Engineering Department,
Tokyo Metro Co.,Ltd.,Japan
4
Director of Structure Division, Engineering Department, Tokyo Metro Co.,Ltd.,Japan
1. INTRODUCTIONTokyo Metro Co., Ltd. (Tokyo Metro) has been aiming to be a subway network offering
excellent passenger satisfaction, based on the concept of “Satisfaction = Safety + Service.”
It has been accelerating several actions including earthquake measures and installation of
platform doors, and has been proactively tackling difficult problems making use ofadvanced technologies and ideas. Faced with various issues related to facility
maintenance, the company is continuously considering and promoting the introduction of
new technologies to solve these issues.
2. PROBLEMS IN MAINTENANCE OF STRUCTURES
Tokyo Metro is operating in the Tokyo area with nine lines and a total operating distanceof 195.1 km, carrying a daily average of 7.58 million passengers. The structures ownedby the company include tunnels, viaducts, bridges, and earthwork, of whichapproximately 85% are located in tunnels.
For the maintenance of structures, regular inspections are conducted according to“Ministerial Ordinance to Provide Technical Standards on Railway” issued by the
Ministry of Land, Infrastructure and Transportation, and actions including monitoring andrepairs are planned and executed based on the results of inspections. The soundness ofstructures is guaranteed by ensuring the repetition of the inspection-planning-action cycle.
On the other hand, there are concerns that maintenance skills will decline as a result of
the decreasing working population in an aging society, in addition to the retirement ofexperienced engineers. To maintain tunnels in sound conditions and continue stable
operation in the future, it is important to address the problems concerning theimprovement of efficiency in tunnel inspection and repair planning, and the training ofmaintenance engineers. As a solution to these problems, Tokyo Metro developed an AR(augmented reality) technology-based training system for tunnel soundness evaluation,
aiming at the introduction of ICT（Information and Communication Technology） totunnel inspection and the enhancement the technical abilities of young engineers15

3. INTRODUCTION OF ICT IN TUNNEL INSPECTION
To ensure rapid, complete, and accurate
execution and recording of inspection,
Tokyo Metro introduced a light-weighttablet terminal to tunnel inspection workand developed inspection application(Photo 1) for better efficiency. The tablet
terminal can display previous inspection
information (type of deterioration andsoundness rank) and photographs, and thewhole work process from overwrite
Photo 1: Inspection Application
updating of records to taking photographs
can be completely and accurately performed and recorded on the tablet terminal. In addition,
the inspection results registered during the work in the tunnels are made available to relevant
parties via a cloud server on the next day, enabling prompt sharing of information.
Home

Inspector

No Change

Field Repair Mode

Inspections Conducted: 0Previous Data

Main Line, B LineR

Current Data

Km, Position Change

R

R

R

R
R
R

Site

Right Arch

Deterioration

Peeling
Soundness Hammering Visual

Progress

All Repairs

Remarks / Cause

Repair

Water Leak

Add

4. INTRODUCTION OF AR-BASEDSOUNDNESS EVALUATIONTRAININGSYSTEMFOR

TUNNEL

This system is an expansion of the application used in inspection work on structures. Used in
the new and deterioration-free simulation tunnel and simulation bridge/viaduct (Photos 2 and3) located in the Tokyo Metro Comprehensive Learning and Training Center, this application
can reproduce deteriorations occurring in actual tunnels and bridges/viaducts on the mobile
terminal screen.

Photo 2: Overall View of Simulation
TunnelPhoto 3: Simulation Viaduct

A feature of this application is the use of NFT (natural feature tracking), which recognizes thesimulation tunnel wall itself as markers (Photo 4), while AR markers are installed on thesimulation bridge/viaduct. This feature eliminates the need for placement and replacement ofAR markers, which are necessary in conventional systems. The present report outlines thefunctions focusing on tunnel inspection. Ten points with deterioration (Photo 5) were preparedon the side surfaces (side wall and upper slab) of the tunnel with a total length of 180 m. The
deteriorations reproduced using AR were six typical types of deteriorations occurring in thetunnels of Tokyo Metro, including cracking, peeling, lifting, cold joint, water leak, rebar
exposure, and honeycomb.

16

December 2019, Yangon, Myanmar

Point with deterioration shown by AR

Photo 4: Model Tunnel Wall without
Deterioration

Photo 5: Deterioration Points in Tunnel

Photo 6: AR Reproduction of
Deterioration, a Scene fromTraining

Photo 7: Guidance of Instructor

Holding the mobile terminal for training, the trainees experience the simulated inspection work
according to the following flow of work. (1) They move to the point of deterioration in thesimulation tunnel. (2) By aiming the mobile terminal at the wall surface, they take photographsof the simulated deterioration (Photo 6). (3) They enter information needed for maintenance,such as the type of deterioration, cause of deterioration, soundness evaluation, and remedialactions. (4) After entering the soundness evaluation for all deteriorations, they upload the input
data to the cloud server. (5) They return to the classroom and receive guidance on how to lookat, think about, and make judgments based on the input data on the PC client screen under theguidance of the instructor (Photo 7).
While the bridge and the viaduct are inspected using the same specifications as the tunnel, they
are structurally more complicated than the tunnel. The positions that require attention (11 points
on the bridge and 10 points on the viaduct) are, therefore, highlighted using AR reproductionsof deterioration in these cases.
In addition, deteriorations on the bridge and the viaduct were more difficult to visualize thanthose on the tunnel, because many of the AR-reproduced deteriorations on these structures were
given as illustrations, in contrast to those in the tunnel. For the purpose of the present report,
AR-reproduced deteriorations were created based on the photographs of the points of interest
to obtain more realistic reproductions (Photos 8 and 9).

New Technologies for Urban Safety of Mega Cities in Asia

17

December 2019, Yangon, Myanmar

Photo 8: Illustration of Deterioration

Photo 9: Reproduction of Deterioration

5. EFFECT OF USING AR-BASED TRAINING SYSTEM
Conventional teaching methods are hampered by the difficulty of providing on-site training due
to safety reasons and time restrictions relating to train operation schedules (the hours from thelast train to the first train) and limited space in the tunnel. Thus, training has chiefly been givenon the desktop using texts and photographs. The introduction of this system is effective, since
it can provide (1) simulated experience of actual inspection methods and procedures, (2) virtual
confirmation of actual deterioration for better understanding, (3) safety training without time
restrictions, and other advantages. In addition, a questionnaire asking the trainees about theeffect of this application (Table 1) provided generally positive feedback. On the other hand, italso identified several areas of improvement, such as the trainees’ request for a greater variety
of types of deterioration that are reproduced using AR.
Table 1: Summary of Trainee Questionnaire

6. CONCLUSION
The application presented here was introduced to the training of new employees and young
employees in their second and third years in the company, and was found to be effective to acertain extent, as indicated by the answers of the trainee questionnaire. Going forward, Tokyo
Metro aims to further diversify the content by adding more types of AR-reproduced
deterioration, as well as different degrees of soundness for the same types of deterioration, withthe goal of qualitatively improving human resource development.

18

New Technologies for Urban Safety of Mega Cities in Asia

Large Scale Ground Reinforcement
for Improvement of Subway Stations
Shinji KONISHI1, Tsuyoshi MORIYA2, Ryuuji FUKUDA3
and Tetsuya MURAKAMI3
1
PhD, Director of Technical Standard Section, Improvement Construction Department,
Tokyo Metro Co.,Ltd., Japans.konishi.r4r@tokyometro.jp
2
Construction office Director, Improvement Construction Department,
Tokyo Metro Co.,Ltd., Japan
3
Construction manager, Improvement Construction Department, Tokyo Metro Co.,Ltd.,Japan
ABSTRACTTokyo Metro Co.,Ltd. is advancing several improvement works of existing subway
structures for mitigating congestion. Because Tozai line, which is one of the lines
carrying out improvement work, was constructed in soft ground near sea, theimprovement works of the line need large scale ground reinforcement under thecondition that continuing operation service. This report describes ground improvement
work of the Minami-Sunamachi Station and Kiba Station. About Minami-Sunamachi
Station, the narrow existing tunnel station with one platform and two railway tracks areenlarged to large structure with two platforms and three railway tracks. To reinforce
base ground and make underground beam, ground improvement was carried out under
existing structures by the high-pressure injection and stirring method vertically andlatitudinally. The Kiba Station which is consisting of two narrow shield tunnels are あalso under enlargement work now. The structural body which is composed ofdiaphragm walls and slabs are constructed surrounding existing tunnel station andsegmental lining of the shield tunnels will be removed. Because the ground is superweak, ground improvement work is carried out now for reinforcing base ground andmaking underground beams. This report describes the works in details.
Keywords: Subway Station, Improvement, Mitigating Congestion, Ground Improvement,
High-pressure injection, underground beam
1. INTRODUCTIONTokyo Metro Co., Ltd. (hereinafter, "Tokyo Metro") opened the Tozai line in 1969,
which extends for 30.8 km connecting Nakano Station in the west of Tokyo with NishiFunabashi Station in the east of Tokyo. The line offers through-services between threecompanies (Fig. 1). Of the 9 routes owned by Tokyo Metro, Tozai Line has the longest
operating length and carries some 1.47 million passengers per day. With a congestion
rate nearing 200%, this route also happens to be the most congested (Fig.2). The
definition of ‘congestion rate’ in here is shown in Table 1. Specifically, there are
significant train delays during morning rush-hours that are particularly chronic at the
Nishi-Funabashi bound platform. Then, several measures have been implemented toalleviate this situation, such as upgrading of the Iidabashi Station to Kudanshita Station

19

Shinagwawa
Shinagwawa

Figure 1： Tozai line overview

Nishifunabashi

Minami-sunamachi

Kiba

Shibuya

ToyochoMonzennakacho

Nihombashi

Tokyo
Shibuya

Kayabacho

Ueno
Ueno

OtemachiShijuku

Kudanshita

Ikebukuro
Ikebukuro

Iidabashi

Takadanobaba

JR Chuo Line

NakanoDecember 2019, Yangon, Myanmar

JR SobuLine

Figure 2： Congestion on Tozai line

Table 1： Definition of congestion ratio
Definition of Congestion ratio
Congestion ratio means riding capacity. It shows situation that train can’t be operated safely when passengers increase morethan the number of people shown by riding capacity.
The congestion ratio becomes 100% when all seats and standing space shown by hand straps and hand rails in the train areoccupied.
Congestion ratio
Standards of congestion ratio
Passenger can sit a seat, hold a strap or a hand rail.
100%
Degree of congestion is that passenger’s body’s touch with each other. But, passenger can read a newspaper.
180%
Degree of congestion is that passenger’s body’s touch with each other and they have substantial oppressive
200%
feeling. However, passenger can read if it is a weekly magazine.
Passengers slant and can’t move every time train shakes. Also, they can’t move their hands.
250%(a) Before renovation(b) After renovation

Figure 3: Minami-sunamachi station configuration
turnaround equipment and other major station improvement work. In short,
improvement work has been carried out at each of Minami-sunamachi, Kiba, Toyocho,
Monzen-nakacho, and Kayabacho stations. This paper describes details of the large
scale ground reinforcement for improvement of Minami-sunamachi station and Kiba
station.
2. MINAMI-SUNAMACHI STATION
2.1 Outline of improvement work
Minami-sunamachi Station has an island type single-platform with two-railway
tracks (Fig.3(a)). The platform width is too narrow relative to the number ofpassengers using it, and people concentrate near the elevating equipment thatconnects the ticket gate to the platform. To address this, large-scale improvement
work is being implemented to improve the safety of passengers on the platform,
reduce congestion, and improve passenger convenience. Specifically, construction isincreasing the number of platforms and tracks to realize a two-platform three-track
configuration, as well as expanding the concourse floor and relocating platform stairs
to the platform center (Figs. 3 (b), 4, 5) (Akagi, 2017). Doing this will allow citybound trains at both stations to alternately arrive and depart from a single platform
during morning rush-hour to shorten railcar dwell time and reduce train delays while
also dispersing persons waiting to ride and increasing standby areas, thereby
improving passenger safety.

20

New Technologies for Urban Safety of Mega Cities in Asia

Figure 4: Cross-section of the station

Figure 6: Construction steps

Figure 5: Layout of platforms

Figure 7: Ground improvement under structures

This area lies in the delta region of Sumidagawa River, Arakawa River and Edogawa
River, which is composed of an alluvial soil deposit with N-values near 0. Improvement
work adds new structures outside the existing construction which is still in use, andlarge diameter jet grouting of the foundation was used for ground improvement.
Construction safety was ensured by completely enclosing the construction area with asolid diaphragm wall. Despite being large-scale excavation work, it was decided not to
use the groundwater level lowering method due to the negative impact it would have on
the surrounding environment. Fig.6 shows the construction steps.
2.2 Ground improvement
2.2.1 Vertical improvement
To reinforce base ground and make underground beam, ground improvement was
carried out under existing structures by the high-pressure injection and stirring
method. To prevent rebound of the existing tunnel by excavation, ground under the
existing tunnel was improved from railway track floor and platform by the highpressure injection in middle night before excavation of ground over the existingtunnel (Fig.7) because of expecting earth weight of the ground part. By the method,
520 columnar improving body's which are from 5.5m to 3.3m in diameter and from
3.1m to 2.0m in length were formed. Fig.8 shows layout of ground improvement
columns. Fig.9 shows measurements of box element displacement before and afterground improvement. 1BL (the leftmost section outlined in red, see Fig. 8) on theplan view is the location of the intensive construction work that was performed in theinitial stage of this project. Absolute displacement values reveal settlement of morethan 15 mm. As a countermeasure, work was dispersed to limit localized settlementin spite of overall settlement. These countermeasures were successful, and it waspossible to keep relative displacement below the primary control value through theLarge Scale Ground Reinforcement for Improvement of Subway Stations

21

December 2019, Yangon, Myanmar

Figure 8: Layout of ground improvement

Figure 9: Box Element Displacement Results
end of the work. Nightly track measurements were also performed during the ground
improvement period just as they were for the diaphragm wall excavation, and thesemeasurements produced results within Tokyo Metro maintenance standards; thus, it
was confirmed that the work had no effect on the tracks.
2.2.2 Longitudinal improvement
Moreover, when improvement work cannot be carry out from inner tunnel due toexisting machine rooms and electric power equipment rooms, underground of the rooms
were improved latitudinally by the high-pressure injection from two adits placed under
existing station tunnel (Fig.10,11).
By the method, 90 columnar improving body's which are from 1.3m to 2.4m indiameter and 54m in length were formed and finished without bad influence on train
operation for about 9 months. While the accuracy of drilling was set 150mm
horizontally and 100mm vertically, 20% of columns had to be rebuild. Because a lot of
concrete wastes, scraps of iron and wood are in under part of the caisson station, theycaused to upset drilling direction. About measurement result of existing tunnel, theexisting tunnel repeatedly deformed gently-uplift and settlement and converged about
4mm. The shape and strength of columns were checked by 10m length lateral boring forchecking from the adits and vertical boring at destination point from the existing tunnel.
Favorable result could be gotten from the borings.

22

New Technologies for Urban Safety of Mega Cities in Asia

Adit 2Adit 1A
Line

Electric
power
eq.room

B

Rail track in existing structureLine

New structure② Horizontal ground
improvement①Vertical ground
improvement

Improvement
direction

Improvement direction

Underground beam

Horizontal ground improvement

Existing structure

Removal part

Figure 10: Cross-section ofLongitudinal improvement

Figure 11: Profile ofLongitudinal improvement

Figure 12: Forward Element Work Procedure

Figure 13: Element Work

Figure 14: Element layout
2.3 Diaphragm Wall Work
Existing diaphragm walls that serve as structural sidewalls doubled as retaining walls.
The diaphragm walls are 1.0 m and 1.2 m thick, and can be separated into two types of
element: Primary element (roughly 2 m wide, roughly 44 m deep) and secondary
element (roughly 6 m wide, roughly 17 m deep). A bucket excavator (MHL) was used
to perform the excavation (Fig.12,13). Fig. 14 shows the element layout.
The ground around the construction site contains a thick layer of alluvial cohesive soilthat is very soft (N = 0-1) and only gently supports the existing box elements. These
conditions and the fact that element excavation was to be performed to a depth of 44 m
prompted concern over slurry wall collapse in the ground behind the excavation areas.
To address that concern, the stability of the slurry walls was calculated before beginningelement excavation, and it was decided to construct soil walls (using the SMW methodwith no core material) to protect the slurry walls (Fig.15). There was also concern thatthe excavation of the ground around the station would cause horizontal displacement ofthat ground, which would in turn displace existing box elements. Clinometermeasurements of ground displacement revealed that excavation caused horizontal
displacement of 4 mm toward the excavation, and concrete placement caused 1 mm ofdisplacement back toward the original position (Fig.16). In addition, settlement gauges
Large Scale Ground Reinforcement for Improvement of Subway Stations

23

December 2019, Yangon, Myanmar

Figure 15: Slurry Wall Protection
and Clinometer Installation Cross-Section

Figure 16: Horizontal Displacementof monitoring by Clinometer

Figure 17: Kiba Station - Current Longitudinal Cross-section
A

C

B

A

C

B

Figure 18: Kiba Station - Longitudinal Cross-section after Renovations
recorded settlement of up to 0.8 mm during concrete placement. Thus, the work caused
minimal displacement to the surrounding ground. In addition, nightly track
measurements during the construction period produced results within Tokyo Metrostandards for track maintenance (less than 17 mm elevation difference and less than 20mm alignment within a 10-m section); thus, it was confirmed that the work had noeffect on the tracks.
3. IMPROVEMENT WORK OF KIBA STATION
3.1 Outline of Kiba station improvement work
Since opening for service in 1967, the passengers number of Kiba Station increase
intensely and congestion occurs in recent years due to ongoing development around thestation. In the Kiba Station, 187 m of the platform length of 220 m becomes a singletrack shield portion (Fig.17). The platform width is 3.0 m on each side. As there is no
passage in the intermediate portion, which connects both platforms, the lines of flow torespective platforms become intricate at both station ends. The platform is so narrowthat passenger retention space becomes very small. As alighting passengers are large innumber, a long queuing line forms on the platform. The station’s stairs and escalators
are located only in the shaft portion at both ends of the station, where passengers
become concentrated., The long lines that form on the platform up to the center of thestation during the morning rush hours do not shrink as trains arrive. For this reason,
improvement work of Kiba station are advanced for enhancing passenger safety bywidening the platform, mitigating congestion, and improving convenience by adding
elevators and escalators from the platform to the ticket gate. In principle, improvement
work is to be executed while maintaining normal operation of the revenue line.

24

New Technologies for Urban Safety of Mega Cities in Asia

Soil

Table 2: Purposes of ground improvement

N value

Position
Name
Upper preceding(１)
underground beam
Lower preceding(２)
underground beam
Ground improvement of(３)basement
Ground improvement of(４)basement
Protecting trench wall
(５)

Legends
Road decking panel(5)

Beam for road decking
Diaphragm wall,(2)

Soldier pile (1st step)

To westTo east
(3)
(4)

(６)

Strut

Pile length = 41700

Filling, Silt, Clay

(1)

High pressure injection
and stirring improvement(Preceding underground beam)
High pressure injection
and stirring improvement(Protect existing segment)
High pressure injection
and stirring improvement(Cover defective part)

Prevent heaving
Prevent ground collapse near trench

Ground improvement at
Countermeasure for artesianedge of earth retaining wall groundwaterNorth
F Segment joint aperture gauge
E Linked 2D displacement gauge (rail track)
D Linked inner space displacement gauge

To eastC Linked 2D displacement gauge (Structure)

Protect trench wall

Gravel, Silt

High pressure injection
and stirring improvement(Protect trench wall)
PositionA
B
C

New structureD

図 2 施工概要断面図（図 1 A A 断面）

EF

DeviceSettlement gauge
Inclinometer
Linked 2D
displacement gauge
Linked inner space
displacement gauge
Linked 2D
displacement gauge
joint aperture gauge

図1
B- B断面5mB断面West
図 1 Bfrom
B-B section
中 野方にRail track
deformation
Leakage

Instauration interval
8m (Total 48 point)
6m (Total 24 point)
2m (Total 120 point)
Setting cross-section(Total 24 section)
5m (Total 78 point)
Setting cross-section(Total 24 section)

9mC断
West
図 1 C面から
from
C-C section
中 野方に9m

3m West
図 1 Cfrom
C-C section
中野

9mC断
East
図 1 C面から
from
C-C section
西 船橋方に9m

5m Eastfrom B-B section

Displacement

Displacement

B-B section

Structuralresistance

3m
East
図 1 CC断面から
from
C-C section
西 船橋方に3m

20m Eastfrom B-B section

図 15m East
面
from
B-B section
西 船橋方に15m

Target item

Figure 20: Layout of measurement devices
15m
図1 CC断East
面から
from
C-C section
西 船橋方に15m

図 10m East
面
from
B-B section
西 船橋方に10m

A Settlement
B Inclinometer

Shield tunnel for station

Figure 19: Outline of improvement work
A-A cross-section

South

F Ring joint aperture gauge

Chemical grouting(6)

Purposes
Secure formation level,
Prevent deformation of retaining wall
Secure formation level,
Prevent deformation of retaining wall
Prevent station falling

1st management value (- -) ±4.0mm
2nd management value (- -) ±7.0mm

Date

Figure 21: Measurement result ofSettlement

Horizontal displacement (------)

North: -, South: +Vertical displacement(------)

Settlement: -, Uplift:

Management vale: Confirm that shield tunnel station ispositioned on the outer side of the railroad construction
limit by clearance limit measurement .

Date

Figure 22: Deformation result of
inside cross-section at tunnel crown

Therefore, plan is to construct the new structure around the existing shield in advance,
and to subsequently remove the existing segments (Fig.18) (Hiromoto, 2017). Since theground around Kiba Station is extremely soft, the work was planned according to
inverted liming method based on using diaphragm walls as the tunnel body and ground
improvement method. This is being done to reduce to a minimum any effects onneighboring buildings and existing shield station during the excavation work. The work
sequence for improvement of Kiba Station is as shown in Figure 6.
3.2 Ground improvement work of Kiba station
Use of the inverted lining method is planned to minimize displacement associated withexcavation. Since the ground condition is extremely soft, the formation level will be
secured for construction of upper slabs from top down method by providing preceding
footing beams with ground improvement under the upper slabs, and by providing
inverted lining middle slabs for the second basement level and below the lower slabs(Fig.19, Table2).
3.3 Measurement management of Kiba station improvement work
Automatic measurement devices are installed in existing shield tunnels station formonitoring deformation of them continuously. Fig.20 shows arrangement of the devices
and purposes of them. Fig.21 and 22 show measurement results of settlement andLarge Scale Ground Reinforcement for Improvement of Subway Stations

25

December 2019, Yangon, Myanmar

deformation of inside cross-section of the tunnels. the point at B-B cross section in Fig.
19 settled on 2.2mm during ground improvement work shown in Table 2 (6). Then, thesettlement continued during ground improvement work near B-B cross section andgrowled to 3.4mm. Large deformation of Inside cross-section was appeared on thecrown of shield tunnel at C-C cross section. Tunnel at the point was moved upward on
5.2mm and horizontally on 1.9mm to North direction during ground improvement workat C-C cross section shown in Table 2 (2). Moreover, the influence continued during
ground improvement work near C-C cross section. Finally, the upward deformation
became 5.2mm and lateral deformation to North direction also reached 2.5 mm.
However, volume of these displacement are within the displacement management value
and there was no influence on our train operation by the work. From the results, it isconsidered that ground stress was released by cutting of the ground and lack of filling,
and deformation of the shield tunnel station occurred due to the ground improvementwork.
4. CONCLUSION
Two improvement works of underground stations in urban area under the condition that
continuing operation service has been described. Obtained knowledges are shown in thefollowing.
(1) The improvement work is advancing safely due to the management system tograsp even small deformation with continuous monitoring and detailmeasurement of rail track after ground improvement work every night.
(2) The improvement work is advancing without bad influence on surroundings andexisting tunnels due to application of high-rigidity diaphragm wall, large scale
ground improvement for basement and preceding underground beam.
(3) When ground was improved by the high-pressure injection and stirring method,the existing structure uplifted or settled just a little. It is important to set suitable
construction speed and sequence considering cutting size, filling speed andhardening speed of filling material.
In any case, the two-improvement work is advancing safely now.
We hope this paper is a useful point of reference in the future planning, design andconstruction of large-scale rail operation improvement work projects in major cities.
REFERENCES
Akagi ， H., 2017 ． Amazing underground construction technology in Japan ， 9thInternational Symposium on Geotechnical Aspects of Underground Construction in SoftGround – Negro & Cecilio Jr. (Eds)© 2018 Taylor & Francis Group, London, ISBN
978-1-138-29711-1，pp.3-19.
Hiromoto, K., Hashiguchi, H & Arai, Y., 2017. Large-scale improvement of convertinga Japan’s first subway station constructed by the shield tunneling method into that of an
open-cut method: Kiba Station on the Tozai Line, 9th International Symposium on
Geotechnical Aspects of Underground Construction in Soft Ground – Negro & Cecilio
Jr. (Eds)© 2018 Taylor & Francis Group, London, ISBN 978-1-138-29711-1，pp.327337.

26

New Technologies for Urban Safety of Mega Cities in Asia

EVALUATION OF IMAGE PROCESSING-BASED CRACK DETECTION UNDER REALENVIRONMENT FOR REMOTE IMAGING INSPECTION WITH AI
T. Fukuoka1, T. Minami2, M. Fujiu3, and J. TAKAYAMA4
Dr., Informatics, Kanazawa University, Geosciences and civil Engineering, Kanazawa, Japan,
2
Master (Eng), Kanazawa University, Dept. of Environmental Design, Kanazawa, Japan3
Ph.D., Associate Professor, Kanazawa University, Geosciences and civil Engineering, Kanazawa, Japan,
4Dr., Eng., Professor, Kanazawa University, Geosciences and civil Engineering, Kanazawa, Japan,
Correspond to Dr., T. Fukuoka (tfukuoka@se.kanazawa-u.ac.jp)
1

Keywords: crack detection, filming conditions, image recognition technology, deep learning
1. GENERAL INSTRCUTIONS
Recently, the study of extending the service life ofbridges has gained attention. In Japan, there are about
730,000 bridges with a length of 2 m or longer, and manyof these were built during a period of high economic
growth, and have now reached the end of their service life.
Therefore, their rebuilding and the extension of theirservice life must be considered.
However, among local public organizations, there are
we some that have insufficient manpower relative to thenumber of bridges to manage, as well as insufficientfunding for maintenance. Thus, these organizations areunable to perform routine close visual inspections.
As issues with the continuing close visual inspection ofbridges are surfacing, the remote imaging system is
expected to become a new inspection method that replaces
close visual inspection.
To develop an alternative method to the current close
visual inspection [1], the practical potential of bridge
inspections using images captured with a super-highresolution camera was examined. Although a super-highresolution camera enable us to take a wide area picture ofa target bridge from a long distance, there is no discussion
about an optimal filming conditions for AI crack detection.
In order to evaluate the effectiveness of the filming
conditions for AI crack detection, we take pictures ofconcrete structure with shifting filming conditions andcomparing the results of crack detection.
2. EXAMINATIONIn this paper, we evaluate an effectiveness of filming
condition by shifting a distance of camera and change thelight of field. We compare a precision and recall of crack
detection rate for the evaluation.
We adapt semantic segmentation method as a crack
detection method. We use DeepCrack [2] model for crack
detection. This model can output crack area with pixel unit.
We have trained this crack detection model with 137
images of crack on a concrete surface and 137 augmented
images.
We use some picture of crack on concrete building as atest image. We set camera and take picture at somedistance for evaluate an effectiveness of camera distance.
Each picture describes a crack with different resolution.
Fig 1 show an example of a different resolution of cracktaken from different distance. To evaluate an effectivenessof light intensity, we set a floodlights near the crack. We

compare a picture taken with a floodlights running and apicture taken without floodlights (Fig 2).

Figure 1. Example of zoom images of crack in a picture;taken from 5 m distance and taken from 30 m distance.

Figure 2. Example of competition of light intensity ofimages.
3. CONCLUSIONSIn Japan, there are about 730,000 bridges with a lengthof 2 m or longer. It is necessary to constant maintain themwith low cost. A bridge inspections using images is one ofa potential method which perform bridge inspection withlow cost. However, an optimal filming condition for takea picture of target bridge is not discussed enough yet.
In this paper, evaluate an effectiveness of distance of
camera and light intensity. We would evaluate anotherfilming condition in the future work.
REFERENCES[1] H. Minami, M. Fujiu, J. Takayama, S. Suda, S.
Okumura, K. Watanabe.: A basic study on diagnostic
imaging technology for bridge inspection using super highresolution camera, Journal of Sociotechnology Research
Network, 15, pp. 54-64, 2018). (in Japanese)[2] Z. Qin, Z. Zheng, L. Qingquan, Q. Xianbiao, W. Qian,
W. Song.: DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection, IEEE Transactions
on Image Processing, 28(3), pp.1498-1512, 2019.

27

Subsurface Pipe Detection by 3D Convolutional
Neural Network and Kirchhoff Migration
Takahiro YAMAGUCHI1, Tsukasa MIZUTANI, Minoru TARUMI
1
M.S., Department of Civil Engineering
School of Engineering, the University of TokyoJapan
tyamag@iis.u-tokyo.ac.jp
ABSTRACTIn this paper, the novel algorithm to detect and localize subsurface utility pipe from
Ground penetrating Radar (GPR) image is proposed. Due to the highspeed and dense
3D monitoring, GPR is a promising tool. However, vast amount of radar image and the
difficulty of interpretation are the bottlenecks of GPR method. In the research, we
propose a new algorithm by the combination of 3D Convolutional Neural Network (3DCNN) and Kirchhoff migration. A CNN architecture is optimized by about 3,000 pipe
measurement data. CNN model classifies images as 3 categories, transverse,
longitudinal and no pipe. The classification accuracy reaches about 92 %, 8 % higher
than 2D-CNN in the case of transverse pipe. After box-by-box scan by 3D-CNN,
Kirchhoff migration is applied to each detected box. By extracting the maximum
intensity peak of each section image, the algorithm successfully visualizes pipes’ 3D
positions and inclinations with reasonable calculation time.
Keywords: Ground Penetrating Radar (GPR), subsurface utility pipe, 3D convolutional
neural network (3D-CNN), Kirchhoff migration, infrastructure health monitoring
1. INTRODUCTION
Ground penetrating radar (GPR) is a promising tool for subsurface utility pipe detection
under the road. Compared to other Non-Destructive Testing (NDT) method such as
electrical and elastic wave exploration method, GPR mounted on vehicle scans under
the road high-speed, up to 80 km/h without traffic control. The problem of the GPR
method is, radar images are enormous in quantity and difficult for a nonprofessional tointerpret. Therefore, one inspection by skilled inspectors takes about several months andten-thousand dollars. An automatic anomalies detection algorithm has a possibility tosignificantly reduce inspection time and cost.
The positions of subsurface pipes need to be localized accurately and fast to help roadadministrators’ decisions. The lack of old utility pipes information delays construction
process, and in worst case, damages pipes to bring economic loss to the society. The
deteriorated pipes cause subsurface voids, which brings serious accidents of roadcollapses. For example, in Japan, over 30 % of total 470,000 km sewage pipe is going to
be over 50 years in 20 years. Furthermore, over 3,000 road collapses are caused by28

December 2019, Yangon, Myanmar

sewage pipes. To handle enormous amounts of utility pipes, accurate and fast automatic
detection algorithm is needed.
In terms of subsurface utility pipes detection by GPR, most research focuses on
migration and tomographic reconstruction, reflection pattern detection by Houghtransform, neural network or other adaptive approaches, antenna polarization, andelectromagnetic (EM) simulation. In terms of migration, Soldovieri et al. (2008)
proposed Kirchhoff-based reconstruction algorithm utilizing truncated singular value
decomposition (TSVD) for multimonostatic configuration. However, migration
algorithm is ordinally not feasible for kilometer-order long distance measurement data
because of calculation cost and time. In terms of reflection pattern detection, Gamba
and Lossani (2000) extracted pipe feature by preprocessing filter and neural network
algorithm with up to 80 % detection accuracy. Al-Nuaimy et al. (2000) proposed the
combination of window function and neural network to successfully localize the area ofpipe reflections.
In this paper, we propose a novel subsurface pipe detection algorithm based on 3D
convolutional neural network (3D-CNN). 3D-CNN is utilized in medical imaging andhuman action recognition. In this research, 3D pipe geometrical characteristics are
utilized to improve the classification accuracy. Kirchhoff migration, considered as oneof the most standard and accurate migration algorithms in NDT practice is applied toeach region detected by 3D-CNN. 3D map of subsurface pipe is constructed by the
extracted maximum intensity peaks of each migrated image. The rest of the paper isfollowed by 5 sections. Section 2 denotes the configuration of the utilized GPR system
and measurement data. Section 3 discusses the appropriate filters and modelarchitecture for 2D-CNN pipe detection. Section 4 optimizes the 3D-CNN model. The
accuracy of 2D and 3D-CNN are compared in this section. Section 5 proposes themethodology to plot 3D map of subsurface pipe. Section 6 summarizes the paper.
2. Measurement system and data
As shown in Fig. 1, the multi-channel vehicle-installed type GPR system manufactured
is utilized in the research. 29 channels are spaced at 0.075 m intervals and scan pitch is
set 0.07 m. The system adopts stepped-frequency method. Operating frequency range is
50 MHz - 3.03 GHz with frequency pitch 20 MHz. Direct coupling removal andTable 1: Measurement data.
Date
2018/3/15
2018/3/19
2018/3/21
2018/3/22

Fi

1 GPR

Transverse
Pipe (2D
Image Num.)
1,040 (30,160)
688 (19,952)
204 (5,916)
709 (20,561)

Longitudinal
Pipe (2D
Image Num.)49a (112,572)a
29 (38,688)t
New Technologies for Urban Safety of Mega Cities in Asia

29

calibration filter is applied to all the measurement data. The effects of ordinally GPR
image preprocessing filters, gain filter and BackGround Removal (BGR) are discussed
in the following section.
The measurement was conducted in Nagano prefecture, Japan, four days from March 15,2018 to March 22, 2018 (Table 1). The total transverse pipe number extracted byinspectors is 2,641. The first three days data, about the three fourths of all the pipes
were used as training data, and the last day data was used as test data. The total
longitudinal pipe number is 78, much less than transverse pipe. However, eachlongitudinal pipe length ranges from several tens meter to several hundreds meter, about
5 - 50 times longer than the length of transverse pipe, which equals to the channel width.
For the two types of pipe, the training image number is confirmed to be enough bychecking the accuracy convergence.
In the case of transverse pipe, a 29 channel pipe was divided into 29 images for 2D
image data, and images having certain channels for 3D image data. In the case of
longitudinal pipe, start and end points were provided by inspectors. Assuming each pipe
is linearly positioned from the start to end, 2D and 3D images were diagonally extracted.
No pipe images were randomly extracted from the area without pipe reflection. The nopipe image data number is the same as the pipe image data number.
3. PREPROCESSING FILTER AND LAYER ARCHITECTURE
To optimize CNN model for subsurface pipe detection, the effects of preprocessing
filters, hidden layer number and input image size are examined. In this research, GPU
NVIDIA GeForce GTX 1080 Ti and CPU Intel Core i7-8700K is utilized for training.
All the training programs are written by TensorFlow. It takes several ten minutes toseveral hours for all the training cases, not strongly depending on the difference of 2D
and 3D possibly because of the optimized backpropagation algorithms.
3.1 Preprocessing filter
The effects of two common preprocessing filters in GPR method practice, gain filter
and BGR are evaluated. Gain filter is applied in time domain to compensate forattenuation and free space loss. BGR is also applied in time domain to remove multiple

Table 2: Preprocessing filter effect.

(a)

(b)

(c)

Figure 2: Preprocessing filter. (a) Raw
image data. (b) Gain filter. (c)BackGround Removal (BGR).

30Your paper title

Preproc Accur
essingacy
Filter
(%)
No filter(propose 85.3
d)
Gain
84.0
BGR
84.3

Preci
sion
(%)

Reca
ll
(%)

AUC

90.0

79.4

0.908

85.8
85.2

82.4
83.5

0.902
0.903

December 2019, Yangon, Myanmar

reflections between antennas and medium boundaries such as asphalt surface and soil
layers. Figure 2 displays the images after gain filter and BGR. Table 2 shows the effectsof the preprocessing filters on the transverse pipe classification accuracy. From Figure 2(a) (b) and Table 2, the effect of gain filter is small when zooming in a hyperbola andfound not to be important for the accuracy. On the other hand, the image clearness
increases by BGR from Figure 2 (c). However, BGR has no effect on the accuracy from
Table 2. This is because the models’ filters automatically learned the target reflection
patterns suppressing the multiple reflections. It is favorable because The parameters of
the preprocessing filters need not be tuned for each measurement data.
3.2 Layer Architecture
The proposed model is shown in Figure 3. The model consists of 1 convolution layers
and 1 fully connected layers). Input image size (N1,N2,N3) represents depth, distanceand channel direction pixels respectively. For 2D-CNN, all the input images and filters
channel direction sizes are set 1, while each parameter is optimized in 3D-CNN as
explained in the following section.
Table 3 explains the layer number effect on the transverse pipe classification accuracy.
2 layer model is the proposed model shown in Fig. 2. 1 layer model is discussed inprevious research. For comparison, VGG16 model, 16 layer and InceptionV3, 48 layer
are utilized. Support Vector Machine (SVM) model is adopted for comparison. From
the results, the models learned certain abstract spatial features by deep layer structure,
though the complicated models such as 4 layer and deeper layer model do not have an
advantage in the context of subsurface pipe radar image classification. Because of thecalculation cost, 2 layer is considered to be optimal in the research.
4. 3D-CNN INPUT IMAGE SIZE OPTIMIZATION
Table 4 shows the input image size effect on the accuracy. All the filter parameters are
confirmed optimal in terms of the classification accuracy though the detailed
explanation is omitted for the brevity of the paper. For each input image size, there is atendency that optimal convolution filter size is almost constant because the scale of thetarget features for the convolution filters is constant.
Table 3: Model comparison.
Model

Figure 3: Proposed model.

SVM
12(Propo
sed)
4
VGG16
InceptionV3

Accu Preciracy sion(%) (%)
72.5 67.9
62.1 67.5

Rec
all
(%)
77.1
46.9

0.805
0.627

85.4

86.2

84.8

0.927

84.7
82.7

85.9
89.5

83.1
74.0

0.915
0.900

74.3

75.1

72.7

0.724

AUC

New Technologies for Urban Safety of Mega Cities in Asia

31

In the case of image size (16,8), the accuracy is by about 3 % lower than the cases ofimage size (64,32). When the image size is equal to or larger than (64,32), the accuracy
is about 85 % - 86 %. This is because the CNN model can recognize pipe reflection
hyperbolic shapes when the image size is enough as observed in Fig. 3. Because of thecalculation cost, the image size (64,32) is adopted in the research.
Table 5 exhibits the accuracy of each model by increasing channel direction input image
size. From Table 5, even in the case of channel number 5, the accuracy increases by
about 2 % compared to the most accurate 2D-CNN model. When the channel size is 29,
the most accurate case, the accuracy increases by about 8 %. The accuracy
monotonically increases with the increase of channel number. 3D-CNN model utilizes
the succession of pipe reflection hyperbolics. Figure 4 shows the Receiver Operating
Characteristic (ROC) curves of 2D and 3D-CNN. The performance of 3D-CNN isclearly improved comparing the curves of Figure 4 (a) and (b).
The same consideration is applied to longitudinal pipe case though the detailed
discussion is omitted. From the results, When the image size is equal to (64,29), theaccuracy is highest, about 90 %. Compared to the 2D-CNN case, the accuracy increases
by about 2 % when the scan number is 32, and decreases when the scan number islarger than 32. This may be due to the inclination of pipe. When the scan number is toolarge, some longitudinal pipes protrude from the 3D-CNN boxes, reducing the relative
volume of the pipes in the extracted boxes. To summarize the two cases, the channel
number 29 is determined for the accurate transverse pipe detection and scan number 32
is determined for the accurate longitudinal pipe detection.
Table 4: Image size effect.
Input
Image
(N1,N2)(16,8)(32,16)(64,32)(proposed)(128,64)

Table 5: Channel effect.

Accu
racy
(%)
82.8
84.7

Prec
ision
(%)
83.7
85.4

Rec
all
(%)
81.9
84.0

0.904
0.923

85.4

86.2

84.8

0.927

85.8

85.5

86.1

0.931

AUC

Input
Image
N3
1
9
13
29
(propose
d)

Accu
racy
(%)
85.4
87.8
89.9

Prec
ision
(%)
86.1
88.6
90.5

Rec
all
(%)
84.8
87.2
89.3

0.927
0.952
0.963

92.9

94.6

91.1

0.976

AUC

Table 6: Confusion matrix.
Predict
Actual\(a)(b)

Figure 4: ROC curve. (a) 2D-CNN. (b)3D-CNN.

32

Your paper title

No Pipe
Trans.
Long.
Recall
(%)

Accu
racy
(%)
1134
32
97
89.8

Prec Rec Precis
ision allion(%) (%)
(%)
65
70
89.4
676
1
95.3
2
1110 91.8
Acc.:
91.0 94.0
91.6

December 2019, Yangon, Myanmar

The 3D-CNN model for three class classification, no pipe, transverse and longitudinalpipe is proposed by incorporating the optimum parameters of each direction pipe case.
From the discussions of the previous two pipes’ cases, the most appropriate 3D-CNN
input image size for the two types of pipe is (64,32,29), corresponding to about 2 m
depth, 2 m distance and 2 m channel range box assuming the soil permittivity is 3.
3D-CNN for the two types of pipe is developed by increasing the class number of the
final softmax layer. Convolution layer filter number is doubled because the number ofthe features to be learned also increases by augmenting the class number (Figure 3).
Table 6 exhibits the confusion matrix of the trained 3D-CNN. The total accuracy isabout 92 %, an intermediate value between transverse and longitudinal pipe case. The
numbers of the longitudinal pipe falsely detected as transverse pipe and vice versa aresmall, indicating the direction of pipe is accurately estimated when there is a pipe.
5. 3D MAPPING OF SUBSURFACE PIPE
Because the model is an object classifier for a provided image box, an appropriate
object localization method needs to be developed. The pipes are detected by setting
appropriate box-by-box scan parameters. Then, the pipes are accurately localized byKirchhoff migration. In this paper, 3D map is shown for five transverse pipes case.
5.1 3D-CNN detection
In the case of radar image, images are monochrome, relatively large, include many
clutters and the scale of target hyperbolics are almost constant, whose situation iscompletely different from a colored scenery photo. Furthermore, the target images are
3D in this research. Therefore, instead of Faster CNN and Single Shot MultiBox
Detector (SSD), the most basic box-by-box scan method, conventionally called“exhaustive search” is adopted. By setting appropriate scan overlap parameters andprobability thresholds of three classes, the pipes are accurately detected with reasonablecalculation time.
Fig. 5 exhibits the same pipes 3D map by changing probability threshold P to 0.995 and
0.990 with the constant scan overlap 75 %. The boxes with solid and dashed lines
correspond to detected transverse and longitudinal pipes respectively. Compared to

(a)

(b)

Figure 5: Detected 3D-Region. (a) P=0.995. (b) P=0.990.
New Technologies for Urban Safety of Mega Cities in Asia

33

Figure 5 (a), false detection increases for P=0.990. In this measurement system andalgorithm settings, the appropriate probability threshold P is 0.995. Practically, theappropriate probability threshold may be determined by the acceptable false negative
rate required for the application.
5.2 Kirchhoff migration localization
In the proposed algorithm, migration is applied to each cross-section image
perpendicular to pipe direction. In figure 6, Downward and upward ray distance R± andangle θ± at point (x,z) of the image are a function of pipes’ direction, transverse or
longitudinal, detected depth dz and two antennas’ offset 2h. After migration, the pointof maximum absolute intensity in each image is plotted in 3D map as pipe’s position.
Figure 7 shows an example of image before and after migration. Before migration, thealgorithm fails to pick the apex of a hyperbola, where an upper edge of pipe isconsidered to exist. After migration, the pipe is successfully located. Figure 8 displays
the extracted peaks. As shown in Figure 8, in some cases the algorithm fails to locate
the pipes’ positions without migration. On the other hand, after migration, pipes’
positions and inclinations are visualized with centimeter-order variation around the line.
3D positions and inclinations of pipes can be inferred from the extracted peaks byKirchhoff migration. The localization accuracy is enough from a practical point of view(a)Figure 6: Kirchhoff migration.

(a)

(b)

Figure 7: Migrated image. (a) Before
migration. (b) After migration

(b)

(c)

Figure 8: Kirchhoff migration results. (a) 3D map. (b) Top view. (c) Side view.

34

Your paper title

December 2019, Yangon, Myanmar

because actual pipes’ diameter reaches to several tens centimeter. The total calculation
time for migration is less than one minute for each case, extremely high-speed
compared to conventional migration research framework.
6. CONCLUSION
In this paper, we proposed a novel subsurface pipe detection algorithm based on 3DCNN and Kirchhoff migration. In terms of transverse pipe, 3D-CNN improves theclassification accuracy by about 8 % compared to 2D-CNN considering 3D shape. The
optimized 3D-CNN parameters in two directions are common, resulting in the threeclass classification of the two types of pipe and no pipe image. By field measurement
data examples, it is found the pipes are successfully detected from 3D map by box-bybox scan method. Position and inclination of pipe are visualized as the extracted peaks
after Kirchhoff migration. The total calculation time is around ten minutes for 500 m
image data. For future work, the authors are planning to apply the same 3D-CNN
architecture for subsurface void detection. The material and diameter of pipes may be
estimated at migration process.
REFERENCES
Daniels, D. J., 2004. Ground penetrating radar. the Institution of Engineering andTechnology, London, UK.
Ministry of Land, Infrastructure, Transport and Tourism, Utility Aging
Countermeasures and Maintenance (in Japanese). Japan. Available: www.mlit.go.jp/common/001020125.pdf, Accessed on: Sep. 28, 2019.
Soldovieri, F., Brancaccio, A., Prisco, G., Leone, G., and Pierri, R., 2008. A KirchhoffBased Shape Reconstruction Algorithm for the Multimonostatic Configuration: The
Realistic Case of Buried Pipes. IEEE Transactions on Geoscience and Remote Sensing,
46.10, 3031-3038.
Gamba, P., and Lossani, S., 2000. Neural Detection of Pipe Signatures in Ground
Penetrating Radar Images. IEEE Transactions on Geoscience and Remote Sensing, 38.2,
790-796.
Al-Nuaimy, W., Huang, Y., Nakhkash, M., Fang, M. T. C., Nguyen, V. T., and Eriksen,
A., 2000. Automatic detection of buried utilities and solid objects with GPR usingneural networks and pattern recognition. Journal of Applied Geophysics, 43.2-4, 157165.
Böniger, U., and Tronicke, J., 2012. Subsurface Utility Extraction and Characterization:
Combining GPR Symmetry and Polarization Attributes. IEEE Transactions on
Geoscience and Remote Sensing, 50.3, 736-746.
Wang, T., and Oristaglio, M. L., 2000. 3-D simulation of GPR surveys over pipes indispersive soils. Geophysics, 65.5, 1560-1568.
Ji, S., Xu, W., Yang, M., and Yu, K., 3D Convolutional Neural Networks for Human
Action Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence,
35.1, 221-231.
Kamnitsas, K., Ledig, C., Newcombe, V. F. K., Simpson, J. P., Kane, A. D., Menon, D.
K., Rueckert, D., and Glocker, B., 2017. Efficient multi-scale 3D CNN with fully
connected CRF for accurate brain lesion segmentation. Medical Image Analysis, 36, 6178.

New Technologies for Urban Safety of Mega Cities in Asia

35

FUNDAMENTAL STUDY ON DETECTION OF FLOATING AREA OF MORTAR SPRAYEDSURFACE USING INFRARED CAMERA MOUNTED ON UAV AND AI
N.ISHIMURA1, T.MINAMI2, M.FUJIU3, T.FUKUOKA4, and J.TAKAYAMA5
Undergraduate Student, Dept. of Environmental Design, Kanazawa University, Kanazawa, Japan,
2
Master (Eng), Dept. of Environmental Design, Kanazawa University, Kanazawa, Japan,
3
Associate Professor, Geosciences and Civil Engineering , Kanazawa University, Kanazawa, Japan,
4 Dr., Informatics, Kanazawa University, Geosciences and Civil Engineering, Kanazawa, Japan
⁵ Professor, Geosciences and Civil Engineering, Kanazawa, University, Kanazawa, Japan
Correspond to Makoto FUJIU(fujiu@se.kanazawa-u.ac.jp)
1

Keywords: Floating Detection, UAV, AI, Mortar Sprayed Surface

36

1. GENERAL INSTRCUTIONSIn Japan, many civil engineering structures wereconstructed during the period of high economic growth.
The mortar spray slope was constructed in the late 1940's
and aging is progressing all at once. At present, themaintenance management of the mortar spray slope iscarried out in accordance with the General Inspection
Implementation Guidelines (Draft) of the Ministry ofLand, Infrastructure and Transport. In Japan, the numberof civil engineering-related staff is decreasing andmaintenance and renewal costs for civil engineering
structures are increasing. So, it will be important toperform more appropriate maintenance within a limited
budget and personnel.
In this research, using an infrared camera mounted on the
UAV grasp the temperature change of an abnormal part
where there is a float and a normal part. Finally aiming at
automatic detection of the float using a machine learning
image analysis system (AI). This paper aims to clarify thefactors that affect the temperature of the slope surface byperforming core sampling of the AI judgment location inorder to improve the accuracy of AI that automaticallydetects the float behind the slope. As a pre-stage of AI
automatic detection, the infrared image is judged byhuman visual inspection, and core sampling is performedat the point where the float is thought to be present. In thisway, the accuracy of the floating inspection of the slopewith an infrared camera is verified.

there is no float.

2.
OVERVIEWOF
CORE
SANPLING
EXPERIMENTIn this study, a core sampling experiment was
conducted for the purpose of understanding the accuracyof the floating inspection of the slope using an infrared
camera. Table 1 shows the target slopes and survey dates
and conditions.
It is considered that there is a high possibility that thepart showing the color with high temperature is floating.
Three locations on each slope were selected: a location
where it is considered there was a float, a location where
it was not clear whether there was a float, or a location
where it is considered there was no float.
Figure 1 shows the infrared image and visible light imageof the slope along prefectural road 10. No. 1 is a place
where it is not clear whether there is a float, No. 2 is aplace where there is a float, and No. 3 is a place where

4. FUTURE TASKSAs a future problem, it was confirmed that the spray’s
thickness varies even on the same slope. When there is atemperature difference on the surface of the slope due tothe difference in spray thickness, there is a possibility that
AI may mistakenly recognize it as a temperature
difference due to floating. Therefore, the relationshipbetween the spray thickness and the surface temperature
is clarified by continuously measuring the temperature of
the mortar where the spray thickness is known.

Table 1. Core sampling experiment conditions

Figure 1. Visible light image and infrared image of slope
along prefectural road 10
3. CONCLUSIONSIn this core sampling experiment, the deterioration of
the slope was diagnosed using an infrared camera, andthree cores with different possibilities of floating werecollected. As a result of the core sampling experiment, it
was confirmed that there were variations in the degree ofconsolidation and spraying thickness even on the same
slope. It was also confirmed that there was a temperature
difference on the surface of the slope even when there wasno float behind the slope.

REFERENCES[1]Ministry of Land, Infrastructure, Transport andTourism, 2013.
https://www.mlit.go.jp/road/ir/ircouncil/pdf/roadstock11.
pdf

DEVELOPMENT OF CRACK DETECTION AND SOUNDNESS DIAGNOSIS SYSTEMFOR REMOTE IMAGING INSPECTION WITH AI
Takahiro MINAMI1, Makoto FUJIU2 , Tomotaka FUKUOKA3 Junichi TAKAYAMA4
Master (Eng), Kanazawa university, Dept. of Environmental Design, taketaka0503@stu.kanazawa-u.ac.jp
2
Ph.D., Associate Professor, Kanazawa university, Geosciences and civil Engineering, fujiu@se.kanazawa-u.ac.jp
3Dr., Informatics, Kanazawa university, Geosciences and civil Engineering, fukuoka@se.kanazawa-u.ac.jp
4Dr., Eng., Professor, Kanazawa university, Geosciences and civil Engineering, takayama@staff.kanazawa-u.ac.jp
1

Keywords: crack detection, soundness of bridge, image recognition technology, Automatic diagnosis, deep learning
1. INTRODUCTION
Recently, the study of extending the service life ofbridges has gained attention. In Japan, there are about
730,000 bridges with a length of 2 m or longer, andmany of these were built during a period of higheconomic growth, and have now reached the end of theirservice life. Therefore, their rebuilding and the extensionof their service life must be considered.
However, among local public organizations, there aresome that have insufficient manpower relative to thenumber of bridges to manage, as well as insufficientfunding for maintenance.
As issues with the continuing close visual inspectionof bridges are surfacing, the remote imaging system is
expected to become a new inspection method that
replaces close visual inspection.
In this study, to develop an alternative method to thecurrent close visual inspection, the practical potential ofbridge inspections using images captured with a superhigh-resolution camera was examined. With image
recognition technology to prepare AI that identifies
cracks, a method that delineates locations with cracks
based on the entire image of a pier was proposed.
Although the automation of the creation of the data ofdamage has been achieved, the automation of thediagnosis of the soundness level has not been conducted.
In order to ensure the objectivity of the diagnosis results,
in this study, in order to automate the soundness levelevaluation, we analyzed the relationship between thedata of damage and the soundness level evaluation value
at the time of periodic inspections in the past.
2. CRACK MAP AT ROUTINE BRIDGEINSPECTION
At routine bridge inspection, inspecters detect crack
and record the crack as crack map. And each crack maps
was diagnosed soundness raiting from 1 to 4. Figure 1
shows crack map diagnosed soundness 1 or 2, in thisstudy, relationship between crack characteristics gained
from these crack map and soundness was analyzed. We
focused on ''Amount of cracks'' and ''Shape of cracks'' ascrack characteristics. Cross point, branch point andendpoint gained from crack map were considered as
shape of crack, and we counted these amount using
pattern matching. Figure 2 shows the result of amount of
cracks for each crack maps, and Figure 3 shows theresult of shape of cracks for each crack maps.

A pier（soundnessⅠ）

B pier（soundnessⅠ）

C pier（soundnessⅠ）

D pier（soundnessⅡ）

E pier（soundnessⅡ）

F pier（soundnessⅡ）

Figure 1

Crack maps used this study

12000
10000
8000
6000
4000
2000
0

A pier

B pier

C pier

0.2㎜ or more

Figure 2
100
90
80
70
60
50
40
30
20
10
0

E pierF pier

0.2㎜ or less

Amount of cracks

A pier

B piercross point

Figure 3

D pier

C pierD pierbranch point

E pierF pierend point

Shape of cracks

3. CONCLUSIONS
Regarding the amount of cracks, it was found that the
total amount of cracks was higher in soundness level II
than in soundness level I, and there was no significant
difference in the amount of cracks with a crack width of
0.2 mm or more. As for the crack shape, it was foundthat the soundness level II was higher than the soundness
level I in the number of cross point, the number ofbranch points, and the number of end points. In addition,
the RC piers diagnosed as soundness degree I had atendency to have one direction with few cross points andbranch points.
REFERENCES
Yeum CM, Dyke SJ (2015) Vision-based automatedcrack detection for bridge inspection. Computer-Aided
Civil Infrastruct Eng Vol.30, pp759–70

37

Electrochemical properties ofreinforcing steel corrodedby carbonation
Sothyrak RATH1, Pakawat SANCHAROEN2, Pitichon KLOMJIT3and Somnuk TANGTERMSIRIKUL4
1
Graduate student, School of Civil Engineering and Technology, Sirindhorn
International Institute of Technology, Thammasat University, Thailand
rathsothyrak2222@gmail.com
2
Research assistant professor, Construction and Maintenance Technology ResearchCenter, Sirindhorn International Institute of Technology, Thammasat University,
Thailandpakawat@siit.tu.ac.th3
Researcher, National Metal and Materials Technology Center, Thailand
4
Professor, School of Civil Engineering and Technology, Sirindhorn International
Institute of Technology, Thammasat University, Thailand
ABSTRACTTo repair corrosion of reinforced concrete structure due to carbonation,
electrochemical properties of reinforcing steel corroded by carbonation is needed to bestudied. In this study, reinforcing steel embedded in different concrete mix proportions
were prepared including different types of binder as well as water to binder ratio.
Specimens were exposed to accelerated carbonation environment and normal
laboratory condition. The four-point probe was applied to investigate the electricalresistivity of concrete. Electrochemical impedance spectroscopy (EIS) and linear
polarization resistance (LPR) were applied to investigate electrochemical behavior ofsteel bar in concrete at different exposure period. Results clearly show the effect ofconcrete mix proportions on carbonation resistance of concrete as well as
electrochemical properties of reinforcing steel. From the results, compatibility design ofpatching repair can be well conducted in the future work.
Keywords: carbonation, corrosion, durability, maintenance, electrochemical,
electrochemical impedance spectroscopy, linear polarization resistance.
1. INTRODUCTION
Corrosion of steel in reinforced concrete is now considered as the major problem
causing premature deterioration of structures, especially for those exposed to aggressive
environment (Bastidas et al., 2007). As a result, this problem leads to the considerable
loss of society due to the maintenance and repair needs.
The embedded steel in concrete usually remains passive due to the formation of ironoxide layer that protect the steel from the chemical reactions. The formation of thislayer depends on pH value in concrete pore solutions, normally in range from 12 to 13.8,
and on electrode potential of rebar (Albani et al., 1990). This passive layer is easily

38

December 2019, Yangon, Myanmar

dissolved when there is the presence of chloride or a drop of pH due to carbonation of
concrete cover (Alonso et al., 2002, Huet et al., 2005).
Carbonation is the progressive neutralization of the alkaline constituents in concretepore solutions by carbon dioxide in the air forming calcium carbonate. This reaction
leads to the decrease of pH value to be around 9 that causes the unstable of passive layer
when the carbonated surface zones reaches the depth of reinforcing steel (Katzer andKobaka, 2006). The role of carbonation in the reinforced concrete deterioration has
increasingly grown interest for two reasons: first, there are many aged RC structuresthat were built before considering durability design standards and have to be maintained.
Second, the aim of reduction CO2 emission, and using the supplementary cementitious
materials (SCMs), such as fly ash (FA), limestone, ground granulated blast-furnace slag
(GGBS) etc., to reduce environmental footprint (Stefanoni et al., 2018). However, theapplication of SCMs as a partial cement replacement material leads to lowering calciumoxide content resulting in reduction of pH of concrete pore solution. This can accelerate
the corrosion initiation, with the presence of oxygen and water on the steel-concreteinterface.
Many researchers (Montemor et al., 2002, Zornoza et al., 2009) has studied about theeffect of carbonation on the corrosion of steel in concrete with and without fly ash
substitution to cement.
The aim of this paper is to study the corrosion behavior of embedded steel bar in OPC
based concrete sample with and without fly ash substitution, and water-to-binder ratios
of 0.4 and 0.6 that are exposed to artificially carbonation (4% CO2 concentration) andnormal laboratory environment (0.03% CO2 concentration). Electrochemical impedance
spectroscopy and linear polarization resistance methods were applied to study the
corrosion behavior of specimens during the carbonation process. The electricalresistivity of specimens during the carbonation process was also studied by using fourpoint probe method.
2. EXPERIMENTAL PROGRAM
Four different concrete mix proportions were studied in this experimental program(Table 1). Ordinary Portland Cement (OPC) type 1, conformed to ASTM C150 (ASTM,
2012), was used. Type 2-b coal fly ash, according to TIS2135, was used as a cement
replacing material. Mix proportions varied water/binder ratios as 0.4 and 0.6 as well as
fly ash replacement ratio as 0% and 30% by weight of binder. The coarse aggregate wascrushed limestone with a maximum size of 10 mm, specific gravity of 2850 kg/m3 andwater absorption of 0.5%. The fine aggregate was river sand with specific gravity of
2670 kg/m3 and 1.51% water absorption. The concrete mix proportion is shown in Table 1.
A grade SD40 deformed steel bar of 12 mm diameter was embedded in prismatic
concrete specimen. The rebar was 150 mm in length, with only 60 mm length left andbeing exposed inside the concrete sample and the other area are coated with epoxy.
There are three types of specimens presented in this study such as: electrical resistivity,
carbonation depth, and electrochemical measurement specimen that are shown in Figure1(a), (b) and (c), respectively. The covering thickness of reinforcement is 20 mm.
All the specimens were coated its surfaces with epoxy on five surfaces (dash line),leaving only one top surface exposed to carbonation (solid line) as shown in Figure 1.

New Technologies for Urban Safety of Mega Cities in Asia

39

Table 1: Concrete mix proportion
Name

Water/
binder

0.4OPC
0.4FA30
0.6OPC
0.6FA30

0.4
0.4
0.6
0.6

Cement Fly ash(kg/m3) (kg/m3)

Water(kg/m3)

397.6
262.1
318.4
212.9

159
149.8
191.1
182.5

0
112.3
0
91.2

Coarseaggregate(kg/m3)1103.41103.41103.41103.4Fine
aggregate(kg/m3)
805.6
805.6
805.6
805.6

The concrete specimens were de-molded 24 h after casting. All specimens were cured inplastic wrap, kept in a normal environment room for 28 days. After finishing the curing
period, the plastic wrap was removed and all specimens were kept in the normal room
environment for other 30 days before exposing to accelerated carbonation (ACC) andlaboratory environment (LAB). The ACC was done with 4% CO2, 50 ± 5 % RH and, 40
0
C, and the LAB (SIIT, Rangsit, Thailand) with 0.03% CO2, 75 ± 5 % RH and, 36 0C.
The carbonation depth was done by spraying phenolphthalein on a freshly verticallysplit section of concrete that recommended by RILEM CPC-18. The average value fromfive points measurement was used.
The electrical resistivity of concrete was measured by the Four-probe resistivity meterby putting its tips on the smooth exposed surface area of specimens. The average of four
points measurement was used.
A standard three-electrode system with working electrode (WE), counter electrode (CE)and reference electrode (RE) was used for electrochemical measurement. The working
electrode was the embedded steel bar with a stainless steel as counter electrode on the
exposed surface of concrete specimen. Copper/copper sulfate (CSE) is used as referenceelectrode that was arranged as shown in Figure 2. A Metrohm Autolab potentiostat wasused for electrochemical measurement.
The assessment of corrosion on steel bars over time was monitored using two
techniques: (i) linear polarization resistance (LPR) to determine polarization resistancevalue (Rp) that is the slope of linear region of polarization curve. LPR measurement was
performed by polarizing the steel ΔE = ±10 mV from open circuit potential (OCP) withthe scan rate of 0.1667 mV s-1. The corrosion current density of steel bar, icorr in μA/cm2,
was determine by using Stern-Geary equation (Stern and Geary, 1957), as shown inEquation (1)icorr = B/Rp

Figure 1: Schematic represents the specimens for: (a) electrical resistivity test, (b)carbonation depth test, and (c) electrochemical test.

40

Electrochemical properties of reinforcing steel corroded by carbonation(1)

December 2019, Yangon, Myanmar

Potentiostat
RE

WE CE

Figure 2: The setup of standard three-electrode system.
where the adopting tentative value B equal to 26 mV for active steel corrosion (Bastidas
et al., 2008) and Rp is the polarization resistance in kΩ; and (ii) electrochemical
impedance spectroscopy (EIS). EIS measurement was performed by applying ac
perturbation of +10 mV from OCP with the frequency range from 105 Hz to 10-2 Hz andlogarithmic sweeping frequency of 10 points per decade. The fitting data of impedance
spectra was conducted by using the commercial software Nova 1.1. Results were theaverage of two replicate specimens with indicated standard deviation of the obtained
results. All the tests were done at the age of 0, 10 and 27 days after exposing tocarbonation chamber, respectively.
3. RESULTS AND DISCUSSION
3.1 Carbonation depth
The carbonation rate of the conventional concrete is described by carbonation rate
coefficient (Kc), in mm/(day)1/2, which is calculated from the parabolic law as shown inEquation (2), where xc is measured carbonation depth (mm), and t is the time (days).

xc = Kc t(2)

Figure 3 shows the carbonation depth versus square root of time for 0.4OPCA, 0.4FAA,
0.6OPCA and 0.6FAA concrete exposed to accelerated carbonation as well as thecalculated carbonation rate coefficient, Kc. The carbonation rate coefficient of fly ash
concrete shows higher value than that of OPC-only concrete, which is consistent withthe trend of results by various researcher (Khunthongkeaw et al., 2006). At the samew/b ratio, the carbonation rate coefficient of fly ash concrete shows the value
approximately two to three times as high as that of OPC concrete. This may be
attributed to the fly ash concrete has lower amount of Ca(OH)2 to react with CO2, that
resulted from the reduction of initial cement content as well as reduction of CH by
pozzolanic reactions. Please be noted that carbonation depth of specimens exposed tonormal environment cannot be measured as the exposure period is short.
3.2 Electrical resistivity
Figure 4 shows electrical resistivity versus time of concrete exposed to accelerated
carbonation (0.4OPCA, 0.4FAA, 0.6OPCA, 0.6FAA) and a laboratory environment(0.4OPCL, 0.4FAL, 0.6OPCL, 0.6FAL). For the same w/b, the fly ash concrete shows
New Technologies for Urban Safety of Mega Cities in Asia

41

higher resistivity than that of OPC concrete. This may attributed to the fly ash concrete
has higher amount of C-S-H that clogs the bigger capillary pores and refining the
microstructure (Mehta and Gjørv, 1982). For resistivity of OPC concrete in laboratory
exposure (0.4OPCL and 0.6OPCL) seems to be slowly increased during the exposure
time. This may be the hydration reactions cause refinement of pore size of concrete. The
resistivity of OPC and fly ash concrete increases noticeably after being exposed toaccelerated carbonation. This increasing may attributed to the deposition of CaCO3 that
reduce the porosity of concrete, which may came from the Equation (3) to (5). The
Equation (4) and (5) are referred to carbonation of fly ash concrete.
Ca(OH)2 + CO2 → CaCO3 + H2O
2SiO2.3CaO.3H2O + 2CO2 → 2SiO2 + 3CaCO3 + 3H2O
4CaO.Al2O3.13H2O + 3CO2 → 2Al(OH)3 + 4CaCO3 + 10 H2O

(3)
(4)
(5)

3.3 Polarization resistance measurement
Figure 5 shows the corrosion rate versus time of embedded steel in concrete exposed toaccelerated carbonation and laboratory environment for 27 days. The Equation (1) wasused to calculate this corrosion rate by adopting the constant value B equal to 26 mV.
The effect of ohmic drop on the polarization resistance was not considered in this study.
Most of the samples were in passive state. No corrosion has been occurred yet, except
0.6FAA and 0.6OPCA that corrosion rate was increased due to progress of carbonation
depth. It should be noted that carbonation depth as shown in Figure 3 is still less thancovering depth. For other specimens, the corrosion state are still in the passive state,even though they were exposed to accelerated carbonation. This is due to higher
resistance against carbonation.
3.4 Electrochemical impedance spectroscopy
The equivalent circuit as shown in Figure 6 is used to fit the results of impedance
spectra. This equivalent circuit consists of two constant phase elements (CPE and CPEP)
to consider two relaxation times. The couple CPE-Rc that performed at high frequency,
referred to dielectric properties of concrete that consist of concrete resistance R c. The
CPEP-RP couple, low frequency range, characterizes corrosion process of steel/concreteinterface that RP is polarization resistance of reinforcing steel. Table 2 includes thefitting results by using equivalent circuit in Figure 6 with the measured impedance

Figure 3: Carbonation depth of concretein accelerated carbonation.

42

Figure 4: Concrete
resistivity
exposedto inaccelerated and normal
environment

Electrochemical properties of reinforcing steel corroded by carbonation

December 2019, Yangon, Myanmar

results during the carbonation process. At high frequency, the concrete resistance, Rc, of
fly ash and OPC concrete increased after accelerated carbonation, evident in Table 2,that this results conform to the trend of results from Wenner probe as discuss in part 3.2.
Compared to the steel embedded in partially carbonated fly ash concrete, the steel
embedded in partially carbonated OPC concrete shows higher polarization resistance forboth w/b ratio. This may attributed to the strength of passive film in which OPC
concrete has higher alkalinity than fly ash concrete.
Comparing the 0.4OPCA to 0.6OPCA and 0.4FAA to 0.6FAA, the concrete with lower
w/b ratio gives higher values of Rp. This may attribute to the higher amount of cementin the lower w/b ratio, as evident in Table 1. The decreasing of polarization resistancewere observed when the accelerated carbonation time increased. This decrease may
attributed to the decrease amount of Ca(OH)2 in concrete by carbonation reaction that
leads to lowering the pH in concrete pore solution which resulted in continuallydegraded the passive film which is represented as a polarization resistance.
For laboratory exposure, the polarization resistance values are continually increased.
This may attribute to the hydration reactions are still continues that generating thehydration product, Ca(OH)2, to reinforce the passive film that resulted in the increase of
corrosion resistance. The RP from OPC concrete are significantly increased, unlike theRP from fly ash concrete. This may be because the OPC concrete has higher amount
CaO than that of fly ash concrete or due to slower hydration reaction of fly ash concrete.
Table 2 shows the comparison between polarization resistance from LPR, denoted as
Rp,LPR, and EIS, denoted as Rp,EIS. From this table, certain differences are evident. Thisdifferences may attributed to the very high IR drop, especially for fly ash concrete,furthermore, since the steel is in a very passive state, then the correlation between
applied potential and measured current is far from linear (unstable of corrosion potential
during the measurement). Therefore, the fitting results from LPR leads to some errors,
as mentioned in previous researches (Kouřil et al., 2006, Serdar et al., 2017).
The comparison between the concrete resistance from Wenner probe test, denoted
Rc,Wenner, and EIS, denoted Rc,EIS, is also shown in Table 2. It seems these two methods
gives a comparable results, except for those of the specimens with higher carbonation
depth. This may attributed to the influence of different layers of resistivity (carbonated-

CPE

CPEP

Rc

RP

Rs

Figure 5: Corrosion rate versus time ofembedded steel bar.

Figure 6: Electrical equivalent circuit
used to fit the EIS data.

New Technologies for Urban Safety of Mega Cities in Asia

43

Table 2: Parameters of the tested results

Name

Sampleage
days

ρc,WennerkΩ cm

Rc,WennerkΩ

Rc,EISkΩ

RP,LPRkΩ

RP,EISkΩLab Acc Lab Acc Lab Acc Lab Acc Lab
Acc
0
12 12.6 0.5 0.53 0.64 0.59 78.2 78.8 368.3 399.1
0.4OPC10
12.5 13.8 0.52 0.58 0.73 0.85 79.4 67.9 474
298.5
2712.7 19.7 0.53 0.82 0.8 2.5 90.8 42.6 546.7 217.50
9.8 9.8 0.41 0.41 0.62 0.62 15.4 15.9 285.9 311.3
0.6OPC10
10.5 11.7 0.44 0.49 0.66 1.16 16.7 13.8 352.9 206.6
27
13.8 15.3 0.58 0.64 0.73 1.5 18.1 9.9 469.1 131.8
027.9 28.8 1.17 1.21 1.29 1.5 57.8 57.4 212.5 209.58
0.4FA
1032.2 41 1.35 1.72 1.35 2.01 59.0 47.2 283.37 147
27
33.5 55.1 1.4 2.31 1.53 2.71 71.0 34.2 399.6 99.21
020.2 17.4 0.85 0.73 1.2 1.38 12.2 12.7 158.7 157.7
0.6FA
10
25.8 31 1.08 1.3 1.48 1.7 13.0 8.9 259.3 86.5
27
32.3 41.2 1.35 1.73 1.8 2.02 14.0 7.1 283.3 56.9
Lab*: laboratory exposure
Acc*: accelerated carbonation exposureand uncarbonated layer) of concrete that distorts the applied current of Wenner probe
test (Gowers and Millard, 1999).
4. CONCLUSIONS
From the experimental results, the following conclusion would be madei. The corrosion rates of embedded steel in OPC concrete were smaller than thoseof fly ash concrete with the same w/b ratio. The corrosion rate increases as anincrease of w/b ratio.
ii. Effects of carbonation on electrical resistivity and polarization resistance ofreinforcing steel can be clearly observed. Formation of calcium carbonate andreduction of alkalinity are the main causes.
iii. From the test results, a further study on compatibility patching repair for
carbonation can be proposed.
ACKNOWLEDGEMENTS
The authors would like to express grateful appreciation to the National Metal andMaterials Technology Center (MTEC) and the Center of Excellence in Material Science,
Construction and Maintenance Technology Project, Thammasat University for theirsupport during this research.

44

Electrochemical properties of reinforcing steel corroded by carbonation

December 2019, Yangon, Myanmar

REFERENCES
Bastidas, D. M., González, J., Feliu, S., Cobo, A., & Miranda, J., 2007. A quantitative
study of concrete-embedded steel corrosion using potentiostatic pulses. Corrosion, 63,
1094-1100.
Albani, O., Gassa, L., Zerbino, J., Vilche, J., & Arvia, A., 1990. Comparative study ofthe passivity and the breakdown of passivity of polycrystalline iron in different alkaline
solutions. Electrochimica Acta, 35, 1437-1444.
Alonso, C., Castellote, M., & Andrade, C., 2002. Chloride threshold dependence ofpitting potential of reinforcements. Electrochimica Acta, 47, 3469-3481.
Huet, B., L’Hostis, V., Miserque, F., & Idrissi, H., 2005. Electrochemical behavior ofmild steel in concrete: Influence of ph and carbonate content of concrete pore solution.
Electrochimica Acta, 51, 172-180.
Katzer, J., & Kobaka, J., 2006. The assessment of fine aggregate pit deposits forconcrete production. Kuwait Journal of Science and Engineering, 33, 165.
Stefanoni, M., Angst, U., & Elsener, B., 2018. Corrosion rate of carbon steel incarbonated concrete – a critical review. Cement and concrete research, 103, 35-48.
Montemor, M., Cunha, M., Ferreira, M., & Simoes, A., 2002. Corrosion behaviour ofrebars in fly ash mortar exposed to carbon dioxide and chlorides. Cement and Concrete
Composites, 24, 45-53.
Zornoza, E., Payá, J., & Garcés, P., 2009. Carbonation rate and reinforcing steel
corrosion rate of opc/fc3r/fa mortars under accelerated conditions. Advances in Cement
Research, 21, 15-22.
ASTM,2012. Astm c150/c150m-12: Standard specification for portland cement. ASTM
International West Conshohocken, PA, USA.
Stern, M., & Geary, A. L., 1957. Electrochemical polarization i. A theoretical analysisof the shape of polarization curves. Journal of the electrochemical society, 104, 56-63.
Bastidas, D., Fernández-Jiménez, A., Palomo, A., & González, J., 2008. A study on thepassive state stability of steel embedded in activated fly ash mortars. Corrosion science,
50, 1058-1065.
Khunthongkeaw, J., Tangtermsirikul, S., & Leelawat, T., 2006. A study on carbonation
depth prediction for fly ash concrete. Construction and Building Materials, 20, 744-753.
Mehta, P., & Gjørv, O., 1982. Properties of portland cement concrete containing fly ash
and condensed silica-fume. Cement and concrete research, 12, 587-595.
Kouřil, M., Novák, P., & Bojko, M., 2006. Limitations of the linear polarization method
to determine stainless steel corrosion rate in concrete environment. Cement andConcrete Composites, 28, 220-225.
Serdar, M., Poyet, S., L'Hostis, V., & Bjegović, D., 2017. Carbonation of low-alkalinity
mortars: Influence on corrosion of steel and on mortar microstructure. Cement andconcrete research, 101, 33-45.
Gowers, K., & Millard, S., 1999. Measurement of concrete resistivity for assessment ofcorrosion. ACI Materials Journal, 96,

New Technologies for Urban Safety of Mega Cities in Asia

45

SUFFUSION BEHAVIOR OF GAP-GRADED SOILS VIA SEGREGATION EXPERIMENTS
A. GHAEMI1, R. KUWANO2, M. OTSUBO3
Master Student, Department of Civil Engineering, The University of Tokyo, Japan,
2
Professor, Institute of Industrial Science, The University of Tokyo, Japan,
3
Research Associate, Institute of Industrial Science, The University of Tokyo, Japan
1

Keywords: Suffusion, Seepage flow, Permeability, Gap-graded soil, Segregation, Particle-size
1. BACKGROUND
Suffusion has been identified as one of the lead causesof failure for many geo-hydro structures, particularly earth
dams and railway embankments. A thoroughunderstanding of the factors affecting suffusion is thus
instrumental in preventing future failures from occurringand designing resilient infrastructure. Previous research
has shown that the response of gap-graded soils
undergoing suffusion is closely linked with the particle
size ratio of the two constituent materials [1], as well as
the percentage of fines in the composition [2]. The
susceptibility of a gap-graded soil is defined by the easewith which the finer particles can be removed from thecomposite matrix. The present paper aims to identify thefactors affecting the segregation behavior of different
composite soils, particularly the effect of varying particle
size ratio and absolute particle sizes.
2. EXPERIMENTAL PROCEDURE
A compacted homogenous layer of the coarser material(250 g) being overlain by a non-compacted homogenous
layer of the finer material (200 g) in a cylindrical
specimen is prepared. The gap-graded soils investigatedare composed of silica sands (diameters from 0.5 to 1.8mm) as the coarse-particle constituent material, in
combination with various finer silica sands or powders.
Greater gap ratios, ranging from 6 to 28, are examined inthis study. These gap ratios are all above the classicalboundary value of 4, which previous research has
identified as the critical value for suffusion to occur [3].
Two types of experiments are performed in this study.
(1) The dry segregation tests: the specimen being
subjected to regular physical blows to the container inroughly equal amount from all sides, and the amount ofmass removed from the specimen via a sieve on thebottom is measured. (2) The wet permeability tests: thefines removed from the specimen from the application ofwater pressure are measured.
3. RESULTS AND DISCUSSION

Figure 1 – Segregation rate under continuous vibrations

46

SS2: Silica sand #2
SS5: Silica sand #5
SS7: Silica sand #7
SS8: Silica sand #8
SS9: Silica sand #9
SSP: Silica powder
GBs: Glass beads
DLC: DL clay

Figure 2 – Permeability test deposited mass and turbidity
Referring to Figure 1, for combinations of both larger
coarse and finer silica sands it can be observed that the
segregation rate gradually increases until it reaches amaximum and then slowly declines. For the largest gapratios all the finer material is segregated from thespecimen within the range of applied vibrations. In
comparison, the gap-graded soils composed of silica sandno. 5 and silica powder or DL clay, which have similar
particle size ratios, show significantly smaller absolutesegregation. This indicates that segregation behavior isgoverned not only by particle-size ratio, but to a greater
extent than anticipated, also by absolute particle size offiner particles.
The permeability tests show that segregation underwater is characterized by an initially large segregation
which rapidly declined. Figure 2 shows that the mass offines removed from the specimen is also significantly
larger for larger relative particle size combinations.
4. CONCLUSIONS
Experimental results show that, additionally to the fines
content and gap ratio, particle size is also a key factor ingoverning segregation behavior. Combinations of larger
absolute particle size materials segregate more easily.
REFERENCES[1] Honjo, Y. et al. (1996) Self-filtration behaviour of
broadly and gapgraded cohesionless soils. Geofilters,
BiTech Publishers, Montreal, Canada, 227-236.
[2] Liu, J. (2005) Seepage control of earth-rock dams:
theoretical basis, engineering experiences and lessons (inChinese), China Waterpower Press, Beijing.
[3] Kedzi, A. (1969) Increase of Protective Capacity of
Flood Control Dikes. Dept. of Geotechnique. TechnicalUni, Budapest, Hungary. Report no. 1 (in Hungarian).

MESO-SCALE DISCRETE ANALYSIS OF CONCRETE DAMAGED BY DELAYED ETTRINGITEFORMATION
K. MATSUMOTO1, Y. MENG2, and K. NAGAI3
1

Associate Professor, Division of Engineering and Policy for Sustainable Environment, Faculty of Engineering,
Hokkaido University, Sapporo, Japan
2
Graduate Student, Department of Civil Engineering, The University of Tokyo, Tokyo, Japan
3
Associate Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
Correspond to Assoc. Prof. K. MATSUMOTO (km312@eng.hokudai.ac.jp)

Keywords: Concrete, Delayed ettringite formation, Meso-scale discrete analysis, Rigid body-spring model, Initial strain
1. INTRODUCTION
Delayed Ettringite Formation (DEF) occurs when
primary ettringite melts under high temperature curing
and reforms to secondary expansive ettringite after theconcrete is hardened, resulting internal pressures. Up tothe present date, the occurrence mechanism of DEF has
been investigated in the material scale, however, thecracking mechanism has not been clarified. This study
aims to investigate the cracking mechanism of concrete
under DEF and its effect on the mechanical characteristics.
A meso-scale discrete analysis method by Rigid BodySpring Model (RBSM), in which coarse aggregates andmortar are separately modeled, is used for reproducing the
expansive behavior in concrete.

Non-uniform
expansion

Uniform
expansion(a) Stress distributions

Non-uniform
expansion

Uniform
expansion(b) Outer cracking patterns

2. OUTLINE OF ANALYSIS
Figure 1 show the model of concrete by RBSM.
Elements are created by Voronoi meshing, in which shapeof the element becomes random. Elements are rigid, butsprings are interconnected between the elements. Coarse
aggregates and mortar are separately modeled as an mesoscale analysis. This study adopted the material
constitutive law used in the previous study [1]. Expansive
strain is given to the mortar elements as an initial strain.
To investigate the effect of non-uniformity of the
expansion, region of the expansion is changed as ananalytical parameter.

Figure 2. Result of analysis after expansion

3. RESULTS AND DISCUSSIONS
Figure 2 shows the inner stress distributions and outercrack patterns when the average expansion strain is about
1%. When the expansion strain is given to only the innerpart, both tensile stresses and cracking from the insideoccur as observed in the experiment. However, when the
expansion strain is given to all the region uniformly,
macro cracks do not occur. It is because interface strength
between aggregate and mortar is comparatively weak,
resulting almost no restriction for mortar expansion.

Figure 3. Stress-strain curves after expansion

Voronoi meshing

Element 1

3 translational DOF
3 Rotational DOF

Figure 1. Model of concrete by RBSM

Element 2

1 normal spring
2 shear springs

Average
expansion
strainFigure 3 shows average stress-average strain curves
obtained by giving forcible displacement in compression
after the concrete is non-uniformly expanded. It indicates
that, with larger expansion, both compressive strength andelastic modulus become smaller.
4. CONCLUSIONS
1) By giving expansive strain to only inner region,
concrete cracks induced by DEF can be reproduced.
2) Meso-scale discrete analysis using RBSM cansimulate reduction of compressive strength and elastic
modulus of concrete due to DEF.
REFERENCES[1] K. Nagai, Y. Sato and T. Ueda, Mesoscopic Simulationof Failure of Mortar and Concrete by 3D RBSM, Journalof Advanced Concrete Technology, 3(3), 385-402, 2005.

47

Effect of stirrup confinement on residual bondperformance of corroded RC by 3D RBSM
PUNYAWUT JIRADILOK1, KUMAR AVADH2 and KOHEI NAGAI3
1
Project assistant professor, Institute of Industrial Science,
The University of TokyoJapan
punyawut@iis.u-tokyo.ac.jp
2
Doctoral Student, Institute of Industrial Science,
The University of Tokyo
Japan
3
Associate Professor, Institute of Industrial Science,
The University of TokyoJapan
ABSTRACTThe surface cracks from expansion of corroded rebar can be easily measured during
field investigations. However, the internal condition and the residual capacity remain
unrevealed. Therefore, it would be a very convenient system if the degree ofdeterioration of bond strength could be predicted by measuring these crack widths. The
cracks induced due to corrosion in reinforced concrete structures are dependent on
numerous parameters such as degree of corrosion, confinement offered by stirrups andconcrete cover etc. Due to various uncertainties involved in corrosion of steel
reinforcement it is very difficult to obtain a unifying relationship and understanding of
the phenomenon from the experimental study. The aim of this research is to understandthe effect of confinement provided by stirrups on corrosion cracks and bond strength
using the 3D RBSM simulation technique. The reinforced concrete models with stirrup
confinement are subjected to uniform corrosion process to induce the corrosion damage.
The pulling-out simulations are then simulated to find the remained bond capacity. The
simulation model is based on the experimental study performed by Lin et al., 2017 inwhich stirrup spacing and concrete cover are varied. The stirrup corrosion is notconsidered in this study. The relationship between the surface crack width, corrosion
damage and the remained bond strength is analysed and discussed.
Keywords: simulation exercise, management by objectives, public relations, common
operational picture, incident action plan
1. INTRODUCTION
Corrosion is one of the important issues in the field of structural monitoring andmaintenance. Once the corrosion occurs, the reinforcement turns into voluminous
corrosion product, which increases the internal pressure, and deteriorates the structure
capacity. Even though several technologies had been developed for the inspection of
the external condition of reinforced concrete structure, the internal condition and theresidual capacity remains unrevealed.
Therefore, it would be useful if the degree of corrosion could be predicted by measuring
the external observable condition of concrete. However, the cracks induced due to48

December 2019, Yangon, Myanmar

corrosion in reinforced concrete structures are dependent on numerous parameters suchas degree of corrosion, confinement offered by stirrups and initial corrosion expansion
damage. Thus, it is important to improve the understanding of relationship between the
corrosion crack damage, stirrup confinement and the residual capacity of damaged bondthrough numerical simulation.
To understand the internal condition of corrosion expansion damaged specimens, thesimulation model is a beneficial tool. In this study, the numerical model called Rigid
Body Spring Model is used to study the relationship between the corrosion expansion
damage and surface crack width. Reinforced concrete models with different initialcorrosion expansion damage and stirrup confinement are formed up for study the effectof each influent parameter. The corrosion expansion damage is induced into the modelby expansive strain method. The pull-out was then performed to measure the residual
capacity. Reinforced concrete models with different control parameters are simulated toinvestigate their effect on corrosion crack patterns. The simulation results werecompared with the previous experiment for verification. The relationship between thesurface crack width, corrosion degree, and the remained bond strength are analyzed anddiscussed. The object of this experiment was to clarify the relationship between eachcontrol parameter and understand the mechanism of bond failure after the corrosion of
main tensile bar in specimens with and without stirrups using RBSM simulation tool.
The paper will also describe the advantages of using RBSM in enhancing the ways tounderstand mechanical behavior or reinforced concrete reinforcing the results obtained
from experimental study.
2. NUMERICAL MODEL
2.1 Rigid Body Spring Model
The numerical model used in this study is 3D RBSM, which is proposed by Kawai et al.
(1977). A 3D reinforced concrete model is meshed into polyhedral rigid elements whose
phases are interconnected by one normal spring and two shear springs (Fig. 1). Eachrigid body has six degrees of freedom (i.e., three translational degrees of freedom andthree rotational degrees of freedom with respect to some point within its interior) (Eddyet al.,2016). The response of the springs provides the interaction between the rigid
elements.
To enable crack propagation in arbitrary directions, a random geometry, based on a
Voronoi Diagram, is used for element meshing. The size of each concrete element ismade approximately 13-23 cm3, in reference to aggregate size, while the size of steel
elements is set according to the geometric complexity of the rebar arrangement.
To represent the reinforced concrete, two types of elements are used, the rebar
elements and the concrete elements as shown in Fig. 2 (a). Fig. 2 (b) shows thegeometry of steel elements which is modelled in an accurate manner to properly accountfor the interlocking between concrete and rebars. The simulation system is developed inprevious studies by Eddy et al. (2016).

New Technologies for Urban Safety of Mega Cities in Asia

49

Rigid body
Element 1

Degrees of freedom
3 Translations
3 Rotations

Rigid body
Element 2

3 springs
1 Normal spring
2 Shear springs

Figure 1: Concrete elements in RBSM(a) Cross-section of steel and concrete elements(b) 3D rebar shape (deformed bar)

Figure 2: Modelling of geometric shape of the rebar
2.2 Expansive strain model
In the 3D RBSM adopted in this study, the expansion resulting from corrosion products
forming around rebars is modeled by inducing a strain at the interface between rebar
and concrete. The expansive strain concept is previously developed by Matsumoto et al.
(2015). This expansive strain is added only to the normal springs at the interface asshown in Fig. 3. Expansive strain concepted has been used to simulate the corrosion
expansion damage of RC structural member in previous studies. (Jiradilok P. et al,
2019)
Concrete elements
Normal spring

Rebar elements

Figure 3: Interface between rebar and concrete and given initial strain
3. MODEL GEOMETRY

50

Effect of stirrup confinement on residual bond performance of corroded RC by 3D RBSM

December 2019, Yangon, Myanmar

Table 1 shows the material properties of simulation model and Fig.4 shows the model
geometry.
The specimen mode in this study is formed based on the previous experiment of Lin H.
et al. (2017). Fig. 4 (a) and Fig. 4 (b) show the general geometry of the analyzed
numerical models for the no stirrup specimen model and stirrup specimen model,
respectively. The size of the model is 330×250×150 mm3. The model contains 22,650
elements for non-stirrup case and 33147 elements for stirrup case. The specimen
reinforced with one D20 rebar and two D8 rebars. The clear cover depth of main rebar
is 30 mm. Unbond length of main rebar is set at 50 mm from the pull-out end and 80
mm from the free end. The stirrup confinement and initial crack damage are varied as
the controlling parameters for this study. Two types of simulation models were formed
up, the specimen with stirrup and without stirrup. In case of stirrups specimens, RB8
stirrups were placed at spacing of 200 mm to provide the confinement. To study theeffect of different initial damage level, the surface crack width is varied from 0.0 mm(sound case), 0.5 mm, 1.0 mm and 2.5 mm. By varying these parameters, 8 simulation
cases are investigated.

(a) Non-stirrup case specimen(b) Stirrup case specimen
Figure 4: Model geometry
Table 1: Simulation material properties
Elastic modulus (MPa)Poisson ratio
Tensile strength (MPa)Concrete
27000
0.15
2.53

Rebar
2000000.25
450

New Technologies for Urban Safety of Mega Cities in Asia51

4. OUTLINE OF SIMULATION PROGRAM
The simulation cases with different control parameters are listed in Table. 2, including
three different crack width with two stirrup confinement condition, LA0 (non-stirrupcase) and LA200 (stirrup case). The simulation program is designed based on theprevious study by Lin H. (2017). To consider the initial damage from corrosion
expansion, the expansion simulation is performed to generate the initial damage before
the pull-out simulation. The simulation process is divided into 2 stages, the expansion
stage and the pull-out stage. During the expansion stage, only the main rebar is
subjected to the expansion (the rebar with red color in Fig. 5).The uniform expansive
strain is continuously given to the rebar-concrete interface along the bond length regionof main bar at rate of 0.00005 strain/step until the crack width on top surface reaches thetarget crack width. Then, the pull-out is performed for finding the residual capacity ofdamage model by using displacement control pull-out simulation. The rebar is pulled at
rate of 0.001mm/step from the side of 50 mm unbond length. The concrete elements at
the pull-out surface are fixed in movement and rotational condition. The crack pattern
for each case and the effect of each parameter on the residual capacity are discussed in
the next section.
Expansion

Pull-out
direction

Figure 5: Simulation condition
Table 2: Simulation cases
Cases
LA0-0.0
LA0-0.5
LA0-1.0LA0-2.5
LA200-0.0
LA200-0.5
LA200-1.0
LA200-2.5

Crack width(mm) Confinement
0.0
0.5
Non-stirrup
1.0
2.5
0.0
0.5
Stirrup
1.0
2.5

5. SIMULATION RESULTS

52

Effect of stirrup confinement on residual bond performance of corroded RC by 3D RBSM

December 2019, Yangon, Myanmar

5.1 Corrosion-expansion simulation
Fig. 6(a) and Fig. 6(b) shows the surface overview after the corrosion expansion
simulation for non-stirrup and stirrup cases. The splitting crack appeared at the top of
specimen along the bond length and 50 mm unbond length side, while the Y-shapecrack can be observed above the unbond length of 80 mm. The similar crack patterns
can be observed from both case specimens.
The crack width pattern along the transverse cross-section is shown in Fig. 7 for various
crack widths. It could be clearly concluded that presence of stirrups reduces the rate ofcracking as higher amount of expansive strain was required to obtain same value ofcrack width on the surface for specimen with stirrups as compared to the one without
stirrup. Fig. 8 shows the expansion strain required for the surface crack achieving thetarget crack widths. In case of stirrup case, the required expansive strain is significantly
higher than the non-stirrup case due to the stirrup confinement proving the counter force
that restrains the opening of the crack. This result is not in accordance with theexperimental study performed by (Lin et al., 2017) however, they have also mentionedthat this requires further clarification experimentally. In previous experimental studies
performed by (Lin and Zhao, 2016) and (Coronelli, Hanjari and Lundgren, 2013) effectof confinement provided by stirrups in reducing the magnitude of crack width for same
degree of corrosion was clearly observed.
Hence RBSM can be effectively used to study the evolution of cracking patterns not
only on the surface but also inside the specimen which cannot be achieved inexperimental studies.
Top surface

Pull-out surface

LA0-0.5

LA0-1.0LA0-2.5(a) Non-stirrup case×10 deformation

New Technologies for Urban Safety of Mega Cities in Asia

53

Top surface

Pull-out surface

LA200-0.5

LA200-1.0

LA200-2.5(b) Stirrup case×10 deformation

Figure 6: Surface overview after corrosion expansion

0.5 mm

1.0 mm

2.5 mm

1.0 mm54

Effect of stirrup confinement on residual bond performance of corroded RC by 3D RBSM

December 2019, Yangon, Myanmar

0.5 mm

2.5 mmFigure 7: Crack evolution inside specimen during corrosion

Figure 8: Required expansive strain for achieving target crack width

5.2 Pull-out simulation
In the experiment, the pull-out test method was performed under displacement control
with a rate of 0.5mm/min applied monotonically. The average crack width was
determined by measuring the longitudinal surface crack at every 20 mm and calculating
it mean. In the simulation the average crack width was determined by measuring the
movement of elements along the same transverse line and determining their average forall pairs of elements along the bonded length.
Fig. 9 shows the load-displacement curve for both the specimens for different crack
widths. As expected and similar to the experimental results the peak load value for
specimen with stirrups is higher for the corresponding crack widths than the specimen
without stirrups. Using RBSM we can clearly visualize the stress distribution inside thespecimen and realize that the red zones corresponding to compressive stress are formednear main tensile rebar and also stirrups. Form Fig. 10 we can compare the stress
distribution for specimen with and without stirrups. Hence, using RBSM we can clearly
study the distribution of stresses and understand the mechanism involved in bond failure.
In this case we efficiently visualized the compressive stresses formed due to presence ofstirrups surrounding the main tensile bar thus effectively providing confinement andenhancing bond behavior. We can clearly see the resistance offered by stirrups to the

New Technologies for Urban Safety of Mega Cities in Asia

55

expansive pressure instigated due to corrosion of rebar which was not possible in theexperimental study.
Table 3 lists the peak load value for the considered crack widths in both specimens. It
was observed that the rate of decrease of peak load for similar crack width is higher inthe specimen with stirrups as compared to specimen without stirrups. This is incoherence with the results given by (Lin et al., 2017) in their paper as in line with theequation provided by them relating residual bond strength and crack width.
160
140

Load (kN)

120
100
80
60

LA0-0
LA0-0.5
LA200-0LA200-0.5
LA0-1

40
20
0
0.000

0.200

0.400

0.600

Displacement (mm)

0.800

1.000

Figure 9: Load displacement curve obtained from simulation

0.5 mm56

1 mm

2.5 mmEffect of stirrup confinement on residual bond performance of corroded RC by 3D RBSM

December 2019, Yangon, Myanmar

0.5 mm

1.0 mm

2.5 mmFigure 10: Internal stress distribution diagrams obtained from RBSM

Table 3: Comparison of peak load and residual bond strength for corresponding crack widths
Crack
Width
(mm)

With Stirrups
Peak
Load
(kN)

ResidualStrength
ratio

0.5

64

0.5

1

47

2.5

31

0

128

Without Stirrups

ResidualStrength from
Equation

Peak
Load
(kN)

ResidualStrength
ratio

0.5

119

0.8

0.37

0.26

100

0.67

0.68

0.22

0.11

70

0.47

0.47

1

1

149

1

ResidualStrength from
Equation

1

0.81

6. CONCLUSIONS
Base on the simulation results, the following conclusion has been made:
1. It could be clearly concluded that the presence of stirrups reduces the rate ofcracking as higher amount of expansive strain was required to obtain same value ofcrack width on the surface for specimen with stirrups as compared to the one
without stirrup.
2. RBSM can be effectively used to visualize crack propagation and stress distribution
inside the specimen, which cannot be done in actual experimental specimens.
3. The reduction in peak load obtained from RBSM simulation is similar to thatobtained from the experimental study and also the equation provided by (Lin et al.,2017). This shows that RBSM can be used effectively to study the mechanism ofbond failure.
4. It can be visibly observed from the plot that the degree of reduction in bond strength
in the specimen with stirrups is much reduced as compared to the specimen without
stirrups. Hence, we can conclude that the confinement provided by stirrups isimportant to reduce the risk of failure. Using RBSM we can clearly identify thezones of compressive stress formed surrounding the main tensile bar thus showing
the increase in confinement because of stirrups. This is also in accordance with theexperimental results obtained.

New Technologies for Urban Safety of Mega Cities in Asia

57

REFERENCES
Coronelli, D., Hanjari, K. Z. and Lundgren, K., 2013. Severely Corroded RC with
Cover Cracking’, Journal of Structural Engineering, 139(2), 221–232. doi:
10.1061/(ASCE)ST.1943-541X.0000633.
Eddy, L., Matsumoto, K. and Nagai, K., 2016. Effect of perpendicular beams on failureof beam-column knee joints with mechanical anchorages by 3D RBSM. Journal of
Asian Concrete Federation, 2 (1), 56-66.
Eddy L. and Nagai K., 2016. Numerical simulation of beam-column knee joints withmechanical anchorages by 3D rigid body spring model. Engineering Structures, 126,547-558.
Kawai T., 1977. New element models in discrete structural analysis. Journal of theSociety of Naval Architects of Japan, 187-193.
Lin, H. and Zhao, Y., 2016. Effects of confinements on the bond strength between
concrete and corroded steel bars. Construction and Building Materials, 118, 127–138.
doi: 10.1016/j.conbuildmat.2016.05.040.
Lin, H., Zhao, Y., Ozbolt, J. and Hans-Wolf, R., 2017. Bond strength evaluation of
corroded steel bars via the surface crack width induced by reinforcement corrosion.
Engineering Structures, 152, 506–522.
Matsumoto, K., Osakabe, K. and Niwa, J., 2015. Effect of shrinkage and strength
development histories on high strength concrete beams in shear. 13th fib Symposium
Proceedings, Copenhagen, Denmark.
Jiradilok, P., Nagai, K., and Matsumoto, K., 2019. Meso-scale modeling of nonuniformly corroded reinforced concrete using 3D discrete analysis. Engineering
Structures, 197.

58

Effect of stirrup confinement on residual bond performance of corroded RC by 3D RBSMSESSION BURBAN SAFETY & DISASTER MITIGATION: DISASTER
MANAGEMENT, RECOVERY AND REHABILITATION PLANNING,
ENVIRONMENT INFORMATICS: TRANSPORTATION/BAGAN HERITAGE

Earthquake Countermeasures of Shinkansen
and their Outcomes
Hiroto SUZUKI1
1
PhD, Disaster Prevention Research Laboratory,
East Japan Railway CompanyJapanh-suzuki@jreast.co.jp
ABSTRACTJapan is an earthquake prone area, and railway operators have been enforcing “hard”
and “soft” earthquake countermeasures. JR East started anti-seismic reinforcement for
viaduct columns, etc. in the wake of the Great Hanshin Awaji Earthquake (M7.3) in
1995. In the Niigata Chuetsu earthquake (M6.8) in 2004, a Joetsu Shinkansen train
derailed but did not overturn, because anti-seismic reinforcement of the viaduct near thederailed point had just been completed. In the Great East Japan Earthquake (M9.0) in
2011, no fatal damage of RC structures occurred on Tohoku Shinkansen, nor did any
commercially-operating Shinkansen trains derail. One factor is that, anti-seismic
reinforcement had been completed for viaducts, etc. of the lowest seismic performance
type in 2008. Enhancing seismic performance of structures is vital for safe train
operation. Furthermore, Shinkansen is protected by the Earthquake Early Warning(EEW) system. The EEW system is a system for early detection of earthquakes,
stopping trains based on observed values of seismometers installed along Shinkansen
lines as well as the coastline. In the Great East Japan Earthquake, coastal seismometersdetected the earthquake and all commercially-operating Shinkansen trains stopped
safety. EEWS is also vital for safe train operation. After this, JR East started using
ocean bottom seismometers in 2017 as a part of EEW system.
Keywords: earthquake, countermeasures, anti-seismic reinforcement, Earthquake Early
Warning System, Shinkansen
1. INTRODUCTION
Japan consists of an island arc located off of the east coast of the Eurasian Continent.
Around Japan, oceanic plates (the Pacific Plate and the Philippine Sea Plate) are
subducted beneath continental plates (the North American Plate and the Eurasian Plate).
Therefore, Japan is one of the most earthquake-prone areas in the world, and disasters
caused by earthquake occasionally occur that incur damage on railways as well.
Earthquake countermeasures are especially important for Japanese railways under suchan environment. To prevent train accidents caused by earthquake, railway operators
have been enforcing “hard” and “soft” countermeasures. Hard countermeasures include
disaster reinforcement work such as anti-seismic reinforcement to help prevent
earthquake disaster. Soft countermeasures consist of earthquake early warning (EEW)

60

December 2019, Yangon, Myanmar

Fig. 1: Viaduct slabs due to viaduct column damage (Right) and bridge beams fell
down due to pier damage (Left) by the Great Hanshin Awaji Earthquake (M7.3)
in 1995.

<

Toughness

Shear-failure preceding typeFlexural-failure preceding typeFig. 2: Damage types of the viaduct columns and the piers
and train operation control in times of earthquake. Soft countermeasures cannot prevent
earthquake disasters, but they can prevent train accidents.
There are seven Sinkansen lines networks in Japan, such as the Hokkaido, Tohoku,
Joetsu, Hokuriku, Tokaido, Sanyou and Kyushu Shinkansen lines. The East Japan
Railway Company (JR East) operates the Tohoku, Joetsu, and Hokuriku Shinkansen
lines. This paper describes earthquake countermeasures and their outcomes, mainly for
the Shinkansen of JR East, based on the experience of four large earthquake, namely as
the Great Hanshin Awaji Earthquake (M7.3) in 1995, the Niigata Chuetsu earthquake(M6.8) in 2004, the Great East Japan Earthquake (M9.0) in 2011 and the Kumamoto
Earthquake (M6.5) in 2016.
2. HARD COUNTERMEASURESThe following describes earthquake countermeasures and their outcomes, for the
Shinkansen of JR East, based on the experience of four resent large earthquakes.
The Great Hanshin Awaji Earthquake (M7.3, inland earthquake) occurred at 5:46 on
January 17, 1995. A maximum of 561 gal was observed by a wayside seismometer
along the Sanyo Shinkansen (JR West). In this earthquake, as shown in Figure 1,
viaducts and bridges of Sanyo Shinkansen suffered serious damage. Viaduct slabs fell
due to column failure and bridge girders fell due to pier failure. Fortunately, no
Shinkansen train accident occurred, because this earthquake occurred early in themorning before Shinkansen trains were operating, as Shinkansen service hours are from6:00 to 24:00. The Sanyo Shinkansen resumed operation 81 days after this earthquake.

New Technologies for Urban Safety of Mega Cities in Asia61Fig. 3: Representative of anti-seismic reinforcement MethodsFig. 4: Damage caused by the Niigata Chuetsu earthquake (M6.8) in 2004. Derailed
Shinkansen train (left), viaduct damage (middle) and tunnel damage (right).

In the wake of this earthquake, JR East started anti-seismic reinforcement for
reinforced concrete (RC) viaduct columns and bridge piers of Shinkansen andconventional lines. Anti-seismic reinforcement was started for viaduct columns andbridge piers of shear-failure type. Such viaduct columns and bridge piers fall in the
category of the lowest seismic performance. As shown in Figure 2, the middle part ofthe viaduct column or bridge pier was damaged, with risk that the viaduct slab or bridge
girder may fall. There are many seismic reinforcement methods for viaduct columns andbridge piers, including those shown in Figure 3 [1]. Among these, the most popularmethod is “Steel Plate Jacketing Method”, which is a method of enveloping up a viaductcolumn or bridge pier by steel plate. In the case of narrow space, “Rib-bar Method” isused, and in the case of existing facilities under viaduct, “Single- Face Method Method”
is used.
Next, the Niigata Chuetsu Earthquake (M6.8, inland earthquake) occurred at 17:56
on October 23, 2004. A maximum of 846 gal was observed by a wayside seismometer
along the Joetsu Shinkansen (JR East). In this earthquake, as shown in Figure 4, a
Joetsu Shinkansen train derailed, being the first derailment of any Shinkansen train.
Damage occurred on the viaduct and tunnel. Joetsu Shinkansen operation resumed 66
days after this earthquake.
The train derailed but did not overturn, because the viaduct near the derailed point
had just completed anti-seismic reinforcement, and no damage was caused to theviaduct. This was an intended effect of the anti-seismic reinforcement. After this, JR

62

Your paper title

December 2019, Yangon, Myanmar

Derailed Shinkansen

Rail conditions after derailment

L-typewheel guide

L-Type wheel guideRail overturning-prevention device

Fig. 5: Status after derailment and countermeasures developed in the wake of the
Niigata Chuetsu earthquake (M6.8) in 2004

Damages of RC structures

Damages of electric poles

Derailed Shinkansen(No commercially operating)Fig. 6: Damage caused by the Great East Japan Earthquake (M9.0) in 2011
East accelerated the pace of anti-seismic reinforcement. Another factor of the train not
overturning was that a protruding wheel part caught on the rail when the train derailed,as shown in Figure 5 (upper left). This part had only been attached on particular railcars.
So an L-type wheel guide [1] shown in Figure 5 (lower left) was developed to prevent
railcars from deviating or flipping from the roadbed after a derailment. JR East started
installing them on all Shinkansen railcars. On the other hand, the derailed Shinkansen
caused the rail to come apart from its fasteners and fall over, as shown in Figure 5(upper right). So a rail overturning-prevention device [1] was developed. This prevented
overturning and deviating of rail in the case of rail fastener damage, which JR East
started installing on railroad tracks.
Next, the Great East Japan Earthquake (M9.0, subduction-zone earthquake) occurredat 14:46 on March 11, 2011. This was a huge earthquake, at magnitude 9 and amaximum of 1,279 gal observed by a wayside seismometer along the Tohoku
Shinkansen (JR East). No fatal damage of viaduct columns and bridge piers occurred on
Tohoku Shinkansen, nor did any commercially-operating Shinkansen trains derail. Only
flexural-failure type viaduct columns and bridge piers, the category of the next lowest
seismic performance, were damaged; as shown in Figure 6 (left). This type of viaductslabs or bridge girders in general do not fall. Many electric poles were damaged, as

New Technologies for Urban Safety of Mega Cities in Asia

63

Fig. 7: Outline of earthquake early warning (EEW) system
shown in Figure 6 (middle). The Tohoku Shinkansen operation resumed 49 days after
the earthquake, regardless of wide range damage.
One reason that commercially-operating Shinkansen trains did not derail is that no
fatal damage of viaduct columns and bridge piers occurred, because anti-seismic
reinforcement for shear-failure type viaduct columns and bridge piers (the lowest
seismic performance type) had been completed in 2008. This was an intended effect of
the anti-seismic reinforcement. After this, JR East accelerated anti-seismic
reinforcement for flexural-failure type viaduct columns and bridge piers in order tofurther improve Shinkansen safety. In this earthquake, one Shinkansen trains not incommercial operation did derail, but did not fall from the roadbed. This train stopped
franks to an L-type wheel guide sandwiching the rail, as shown in Figure 6 (right). In
this way, the L-type wheel guide developed in the wake of the Niigata Chuetsu
Earthquake proved effective immediately.
Next, the Kumamoto Earthquake (M6.5, inland earthquake) occurred at 21:26 on
April 14, 2016. A maximum of 312 gal was observed by a wayside seismometer along
the Kyushu Shinkansen Line (JR Kyushu). Viaducts and bridges of Kyushu Shinkansen
were almost undamaged and cracks occurring only at 33 locations. The Kyushu
Shinkansen operation resumed 14 days after this earthquake.
A major reason that viaducts and bridges were almost undamaged is that they were
designed with the latest seismic design method defined in the wake of the Great
Hanshin Awaji Earthquake. No commercially-operating Shinkansen trains were derailed,although one Shinkansen train not in commercial operation did derail.
JR East has been promoting earthquake countermeasures, the intended effects ofwhich have already appeared. To enhance seismic performance of structures is vital forsafe train operation.
3. SOFT COUNTERMEASURESThe following describes the Early Earthquake Warning (EEW) System [2] that isrepresentative of soft countermeasures. The EEW system is a system for early detectionof earthquakes, stopping trains based on observed values of seismometers. As shown in
Figure 7, when acceleration of a seismic wave observed by a seismometer exceeds
threshold, a warning is issued. The seismometer sends an alarm and power supply is cut
and the emergency brakes are automatically applied and trains stop. There are two
methods for issuing a warning [2, 3] : “P-wave warning” and “S-wave warning.” “Swave warning” is issued when acceleration exceeds threshold and “P-wave warning” isissued according to earthquake information estimated by the initial part of P-wave.

64

Your paper title

December 2019, Yangon, Myanmar

1982
1997
Opening of Tohoku
Opening of Hokuriku
and Joetsu Shinkansen Shinkansen:Wayside seismometer

2007
2012
Expansion of wayside Expansion of inland
seismometer
seismometer:Coastal seismometer

2015
Extension of Hokuriku
Shinkansen:Inland seismogram

Fig. 8: Installation of seismometers on the Tohoku, Joetsu and Hokuriku Shinkansen

Fig. 9: Train location on the
Tohoku Shinkansen at Fig.10: Locations of ocean bottom seismometers
the time of the Great Eastand epicenter of the Great East Japan
Japan Earthquake
Earthquake
In this system, there are three types of seismometers; “wayside”, “coastal”, and“inland.” Figure 8 shows the growth of the seismometer layout in the JR East EEW
System. In 1982, when the Tohoku and Jouetsu Shinkansen lines opened, wayside andcoastal seismometers were installed. Coastal seismometers were installed on the Pacificcoast for early detection of subduction-zone earthquakes off the Pacific Ocean. At thispoint, S-wave detection was adopted, the threshold of which was 40 gal for both
wayside and coastal seismometer. When the Hokuriku Shinkansen (Takasaki-Nagano)opened in 1997, seismometers were added wayside of the Hokuriku Shinkansen andalong the coast of the Sea of Japan. In 1998, a P-Wave Detection System developed by
Railway Technical Research Institute (RTRI) was introduced. The S-wave threshold of
the coastal seismometer rose 120gal. In 2004, Newly P-Wave Detection System [3]developed by RTRI was introduced. In P-wave detection, epicenter and magnitude are
estimated by the initial part of p-wave, and at-risk area, about 80 gal, is estimated by
epicenter and magnitude, and warning is issued. In 2007, wayside seismometers were

New Technologies for Urban Safety of Mega Cities in Asia65

added and the Tohoku Shinkansen between Morioka and Hachinohe was extended. In
2012 inland seismometers were added for early detection of inland earthquakes, and JR
East started using Earthquake Early Warning provided by Japan Meteorological Agency(JMA) as a part of EEW system. In 2015, the Hokuriku Shinkansen between Nagano
and Kanazawa opened, and seismometers were added for this area.
Next is the intended effects of this system in the Great East Japan Earthquake. When
this earthquake occurred, 19 commercially-operating train of Tohoku Shinkansen wererunning. Figure 9 shows their locations. Maximum acceleration was 1,279 gal along the
Tohoku Shinkansen. In this earthquake, a coastal seismometer detected acceleration byearthquake exceeding threshold. A warning was issued 12-22 seconds before waysideseismometers detected acceleration exceeding threshold to suspend operations [4].
Emergency brakes were automatically applied and Shinkansen trains slowed down andstopped, and all commercially-operating Shinkansen trains stopped without derailment.
JR East began using the ocean bottom seismometers (OBSs) data of the Boso-oki(S1) sub-system shown in Figure 10 in November 2017, and data from the Ibaraki-oki
to Kushiro-oki (S2, S3, S4, S5) sub-system in January 2019 for the Shinkansen EEWsystem. OBSs were installed along the Japan Trench by the National Research Institutefor Earth Science and Disaster Prevention (NIED). Subduction-zone earthquakes along
the Japan Trench, such as the Great East Japan Earthquake, may be detected earlier if
the OBSs data are used for the EEW system. The threshold value of OBSs increases
with distance from wayside.
Finally, this is the expected effect by using OBSs data for EEW System. In the caseof the Great East Japan earthquake, by a simple calculation, OBSs are estimated to havebeen able to issue a warning about 25 seconds earlier than the S-wave detection of thecoastal seismometer. Using the archive data observed by the OBSs, the effectiveness ofusing OBSs data for EEW system in the case of an earthquake occurring offshore of
Fukushima Prefecture at 5:59 on November 22, 2016 (M7.4, subduction-zone
earthquake) was verified. OBSs are estimated to be able to issue a warning about 12
seconds early than P-wave detection by a coastal seismometer of the conventional EEW
system [5]. Thus, OBSs are expected to have a great intended effect on the early
detection of subduction-zone earthquakes.
JR East has been using and improving EEW system, the intended effects of whichhave already appeared. To continue improving EEW system is vital for safe train
operation.
4. SUMMARY
This paper describes earthquake countermeasures and their outcomes, mainly for the
Shinkansen of JR East. Earthquake countermeasures implemented so far have beensuccessful in preventing the derailment of Shinkansen and damage to structures, andcontributed to safer train operations in times of earthquake. JR East will continue todevelop hard countermeasures and introduce even more effective soft countermeasuresfor earthquakes.
This paper describs the importance of disaster prevention countermeasures using
Japan’s Shinkansen as an example. In disaster prevention countermeasures, it isimportant to keep humble and learn from experience and implement countermeasuresproperly.

66

Your paper title

December 2019, Yangon, Myanmar

REFERENCES[1] Horioka, K., 2013. Clarification of Mechanism of Shinkansen Derailment in the

[2]
[3]
[4]
[5]

2011 Great East Japan Earthquake and Countermeasures Against Earthquakes, JR
EAST Technical Review-No.27, p13-16.
Nakamura, Y., 1985. Earthquake warning system in Japan National Railways,
Railway technology, Vol. 42, pp. 371-376, (in Japanese).
Iwahashi, H., et al., 2004. Practical use of earthquake quick alarm system, RTRI
Report, Vol. 18, No. 9, pp. 23-28. (in Japanese with English abstract)
Yamamoto, S., and Tomori, M., 2013. Earthquake early warning system for
railways and its performance, Journal of JSCE, Vol. 1, pp. 322-328.
Miyakoshi, H. et al., 2019. Earthquake Early Warning for Shinkansen using Ocean
Bottom Seismometer, 12th World Congress on Railway Research, Printing.

New Technologies for Urban Safety of Mega Cities in Asia

67

The Religious Buildings in Bagan and
The 2016 M 6.8 Subduction Zone Earthquake
In Myanmar
Hla Hla Aung

Senior Researcher
Myanmar Earthquake Committee, Federation of Engineering Societies
MES Building, Hlaing University Campus, Yangon, Myanmar
hhlaaung@gmail.com

ABSTRACTThe ancient city, Bagan (Pagan) is located in the heart of dry desolate desert-like plainsin the Dry Zone of Myanmar, the very center of the country, along the bank of Ayeyarwaddy
River covering an area of a little over 42 square kilometers, in the northwest of Mt.Popa.
Bagan, the land of temples and stupas was shaken by a series of earthquakes since ancient
time and the earliest record is about 25 November, 1372 and another event in 1550 A.D.by
which event Shwe-gu-gyi temple was damaged. In 1975, the largest earthquake within 900
years, hit the city with magnitude 6.8, and many pagodas and temples were damaged within
seconds. Some of pagodas are being left intact and withstand to maintain the role of its
past glory as historical monuments in Southeast Asia. Due to another large earthquake,
the Chauk earthquake in 2016 with M 6.8, approximate numbers of pagodas of (400) weredamaged as the previous 1975 Bagan earthquake. Pagodas left intact and withstand as
before. The 1975 Bagan earthquake and the 2016 Chauk earthquake are intermediatedepth subduction earthquakes and such inland intermediate-depth earthquakes arehazardous earthquakes for the area along the Rakhine Western Ranges (Indo-Andaman
belt) under which the India plate is obliquely subducting beneath the Burma plate. Remotesensing + GIS technologies and geodesy survey are greatly needed for effective
preparedness to keep the religious buildings to be able to withstand future earthquakes.
Keywords: religious building, earthquake, subduction, remote sensing, preparedness

Introduction.
1

68

The ancient city, Bagan or Pagan is located at latitude 21°10’N, Longitude 94°51’E, in
Mandalay Region, on the east bank of the Ayeyarwady River (Fig.1).

Fig.1.Location map of Myanmar in SE Asia showing geographical location of Bagan
city.
Pagan became a capital city of the Burmese Empire and 55 kings ruled Pagan over a long periodof 12 centuries according to local chronicles. Many Buddhist temples and pagodas were built on
the stretches of sandy wind-swept plains and Pagan became a stronghold of Buddhism and waswell known as the seat of Buddhist learning and culture among its contemporaries inSoutheasAsia.Myanmar is consist of five physiographic divisions: starting from the west(1) the
Rakhine coastal plain, (2) the Rakhine ranges in N-S belt, (3) Central Myanmar lowland between
Rakhine ranges and Shan Plateau, (4) Shan Plateau in the east, and (5) Kachin mountains in thenorth and north-east (Fig.2). Among these divisions, the Central Myanmar Basin is a lowland
area and a flat land covered with mainly Tertiary sedimentary rocks of sandstone, siltstone, shaleand clays and Quaternary sequences. Stretches of river alluvium exist in this division depositedby the major rivers of the Ayeyarwady and the Chindwin and their tributaries.

269

Fig.2.Satelliteimage of Myanmar Showing physiographic divisions.
Geological Setting
The Bagan is in a flat land area on the bank of the Ayeyarwady River.The AyeyarwadyRiver flows to the southwest direction from the confluence point of the Chindwin and the
Ayeyarwady River and then to due south through the flat plain of the Dry Zone of Central
Myanmar. There are few sandstone hills and cliffs along the bank of the river. These cliffs
are covered with red gravels and sheets of gravel stretch over the plateau surface for a vast
area indicating that the area must have been once the higher level of the present river.
Beyond the confluence point, at the places of Naung-oo, Pagan, Sale and Chauk area, theriver formed a terrace system consists of 5 terraces. In the section, Terrace 5 is 12 meter
above the level of the Ayeyawady river and upward to Terrace 4, 3, 2, and 1 successively
and at the top is covered with coarse red gravels on hill tops. This terrace system shows
up clearly, particularly in the area between Sale and Chauk. It consists of sand and finesand, similar to the present-day sediment load carried by the Ayeyarwady River, redgravels and red sand. It contains stone implements of the Late Paleolithic, and it is followed
by aeolian sand, the loess-like “Pagan Silt”. The aeolian sediment are formed by theaccumulation of wind-blown silt, sand and less clay. It consists of a pebble-bearing gravelat the base, above which come fluviatile and finally aeolian sands, coarse red gravels of“Nyaung-U-Red Earth” which covers it. This horizon is several meters thick and causes a
370miniature badland topography (Bender,1983). Most of the Buddhist temples and stupas
were built on the stretches of sandy wind-swept plains. Bagan sits on Quaternary strata
above sandstone and shale of the Upper Irrawaddy Group and Pegu Group.
Tectonic Setting
Tectonically Myanmar is made up of a mosaic of tectonostratigraphic terranes: four tectonic
terranes and three accreted belts. They are as follow:(1) Rakhine Coastal Plain terrane (RC),(2) Rakhine Western Range terrane (RWR),(Indo-Andaman Belt)(3) Central Burma Basin terrane (CBB),(4) Shan Massif terrane (S) and,(5) Kachin terrane (K)(6) Shan Boundary Belt
(7) Than Lwin Belt
The geology of Bagan area consists of Holocene surficial deposits of gravel, sand, silt andclay. The underlying rock formations that crop out around the Bagan area are mostly sandstone,siltstone and shale of the Pegu Group of Oligocene-Miocene and the Irrawaddy Group of
Pliocene-Pleistocene. In the west of Bagan, there is the steeply dipping eastern flank of the N-S
extent of 2000 km long strip of Rakhine Western Ranges which was produced by collision
between the India and Burma plates at about 46 Ma. India plate is subducting obliquely beneath
Burma plate along Sunda subduction zone. Northward and northeastward movement of India
oceanic crust is the most important part for tectonics of Myanmar in Tertiary time.

Fig.3. Satellite image showing epicentral
Location of 2016 Chauk earthquake.
A large amount of the motion is driving the uplift of the Rakhine Western Ranges since the
Miocene time. The northeastward convergence of the Indian oceanic crust beneath the Burmacontinental plate is still active. This active tectonic activity below Rakhine ranges has beencausing the intermediate focus seismicity along the belt from the Naga Hills in the north to theChin Hills and the Arakhan ranges to the south. The Yakhine Western Range is a subduction‐
related outgrowth continent, composed of two different geologic units, normally a broad flysch
belt which constitutes the main section, and a narrow, intermittently out‐cropping zone ofmetamorphic rocks and ophiolite.This ophiolites were considered to be the remnants of Neo‐
4

71

Tethys seafloor obducted during subduction. Structural trend swings from the NE‐SW directionin the Naga Hills to NW‐SE along the Rakhine Range and Chin Hills. Kabaw Fault Systemdemarcated this terrane from Central Myanmar Basin terrane. The Central Myanmar Basin orCentral Lowland area is a flat land covered with mainly Tertiary sedimentary rocks of sandstone,siltstone, shale and clay.
Archaeological Techniques & Religious buildings in Bagan
The stupas and temples were erected mostly from the 11th to 13th centuries but the Bagandynasty began from 108 A.D. ruled by 55 kings for 12 centuries according to local
chronicles. But epigraphically evidence supported that the dynasty began with the reign ofKing Anawrahta (1044-1077 A.D.). Some believed that most of the temples and stupas in
Bagan must have been built during a few centuries about more than 13,000 stupas andtemples, but today only about 5000 (recorded 4474 structures) are remained but total 3122
in the list of the archaeological department. The rest structures must have been disappeared
due to weathering through times and some believed to have dismantled a considerable
number of monuments to collect materials for building forts by invaders. Since then thegreat mass of the religious edifices were left to decay and ruin some by human vandalism.
Technology of many multi-storeyed temples and stupas was technically most advanced asthese temples and stupas in Bagan area still intact to the original locations. The structures
are not only advanced in engineering aspects but also soil mechanic aspects. The kind of
construction techniques, typical of Bagan period which were not found in middle ages allover the world involved the use of load bearing system which can resist the weight of thestately religious buildings, the use of vaults and arches to create lighting effects

Fig.4. A photo showing a proportionate geometry between the height of the structure andthe depth of foundation
inside the buildings with changing effects between darkness and brightness through sunlight.
The foundation geometry of ancient buildings in Bagan area has all essentials with very deep
foundation with a proportionate between the height and depth of the structure as seen in the
figure(Fig.4) and for an example of Me-Taw-ya temple with a foundation of 3 meter-5 meterdeep (Fig.5). The temples are built using a multi-layered technique in order to maintain thestability of the temples and stupas for long term in the future. Apart from the best preserved
temples but also they are elegant and harmonious dimension of the architectural style.
572

Fig.5. A photo of a temple Me-taw-ya showing the height and the depth of foundation( 3m-5m) (Maria Leitzia et al.2018)
Earthquake Disaster & Preparedness
Bagan, the land of temples and stupas was shaken by a series of earthquakes sinceancient time and the earliest records are about 25 November, 1372 , 14 July 1485 A.D. andanother event in 1550 A.D.by which event Shwe-gu-gyi temple was damaged. In 1975, thelargest earthquake within 900 years, hit the city with magnitude 6.8, and many pagodas andtemples were damaged within seconds. Some of pagodas are being left intact and withstandto maintain the role of its past glory as historical monuments in Southeast Asia. The 8th
July1975 Bagan earthquake of magnitude 6.8 occurred at 21°50’ N and 94°70’E is anintermediate-depth subduction earthquake with a depth of 112 km (ISC) and focal
mechanism is reverse faulting (USGS). Due to another large earthquake, the 24th August
2016 Chauk earthquake at latitude 20°919’N – longitude 94°579’E with M 6.8, approximate
numbers of pagodas of (400) were damaged as the previous 1975 Bagan earthquake.
Focal mechanism was reverse faulting (USGS). Due to this event, damage to the ancientmonuments was about 90 per cent and it was felt through the Central Myanmar, Rakhinearea, northeastern India and Bengladesh.

673

Fig.6. Epicentral locations of significant inland subduction zone earthquakes along
Rakhine Western Ranges in Myanmar.

Fig.7. A section across latitude 20°N Showing intermediate-depth earthquakes within the
India oceanic plate and surface profile from west to east through Central Myanmar Basin.
In Bagan and its environs, upper portion of stupa, temples and pagodas have fallen down.
By judging the damages of the religious buildings only at the uppermost part and felt reportof local people in Bagan indicate that the ground motion was strong enough to fling up thearea as the fault moved vertically beneath it. The April 2016 Mawlaik earthquake (M 6.9,134
km depth ) ruptured the Tripura segment, the August 2016 Chauk earthquake (M 6.8,
84.1km depth) and the January 2018 Kauk-tu earthquake (M 4.9,76.1km depth) ruptured the
Arakan segment and the October 2016 Tamathi earthquake (M 4.8, 97.5 km depth) ruptured
774

the Naga segment respectively (Fig.6 and 7). Each of the segments corresponds to thesegments of Sunda megathrust segments as follow (from north to south): the Naga segment,
the Tripura segment and the Arakan segment (Dasgupta et al.1984). Such deformation style
may be characteristics of the environments under the extensional or compressional stresses
that occurred within the downgoing slab of the India plate..
Discussion
Myanmar region is resting on three plates: India, Burma and Indochina so that many areas
in Myanmar area at risk from future earthquakes. The inland intermediate-depth earthquakes arehazardous earthquakes for the area along the Rakhine Western Ranges (Indo-Andaman belt)
under which the India plate is obliquely subducting beneath the Burma plate. To mitigate theseismic risk to these stupas and temples in Bagan, effective earthquake preparedness andrecovery, rehabilitation, reconstruction should be introduced for Build-Back-Better. In
preparedness, acquired satellite imagery and geospatial information will be carried out toproduce rapid maps that can support government, disaster management agencies and first
responders for damage assessment especially in remote areas and overall picture during and postdisaster situation. In that case, we need to develop a way of detecting earthquake source fromsatellite image and to apply the same technique to detect the damages.
References

1. Aung,H.H., 2013. Tectonic Styles and Deformation Patterns of Terranes in Myanmar. Watah Press,

Yangon, Printed in Myanmar
2. Aung,H.H., 2015. Myanmar Earthquakes History, Wathan Press, Yangon, Printed in Myanmar
3. Curray, J.R., et al.2005, Tectonics and history of the Andaman Sea region,J.Asia Earth ScienceXX1-42
4. Kyaw Lat: Art and Architecture of Bagan and historical back ground with data of important
Monuments.Mudon Sarpay, No 501-D, Mahabandula Housing, Yangon
5. 5.Leyton,F., Javier Ruiz, Jaime Campos, Edger Kausal, 2001: Intraplate and interplate
earthquakes in Chilean subduction zone: A theoretical and observational comparison, Physics ofthe Earth and Planetary Interiors,175(1): 37-46, June, 2009.
6. Maria Letizia Amadori et al. (2018) Integrated scientiﬁc investigations on the constitutive
materials from Me-taw-ya Temple, Pagán Valley, Burma (Myanmar), Measurement, vol.131,
January2019, pg.737-750
7. Mukhopadhyay, M. and Dasgupta, S.1988, Deep structure and tectonics of the Burmese Arcs
constraints from earthquake and gravity data, Tectonophysics,149 (1988) 299-322 Elsevier
Science Publisher B.V, Amsterdam, Printed in the Netherlands.
8. Mondal, M.; Cecillia M.G. Mchugh; Goodbred, S.; Akhter, S.H 2014.; Paleoseismic Records of1762 and similar Prior earthquakes along the SE coast of Bengladash: Conference paper AGU
Fall Meeting 2014
9. Rangin C.,1996-1999.Deformation of Myanmar, Results of GIAC Projects, GIAC Conf.
(Yangon,Myanmar)
10. Ruff, L.J., 1996, Large Earthquake in Subduction zones: segment interaction and Recurrence Time
Department of Geological Sciences,University of Michgan, Ann Arbor, Michigan
11. Satyabala, S.P.,2003 The Historical Earthquakes of India, National Geophysical ResearchInstitute, Hydrabad-500 007, India

875

12. Steckler, M. et al., 2008, Collision of the Ganges Brahmapudra Delta with the Burma Arc:
Implication for earthquake hazard; Earth and Planetary science Letters 273 (3-4): 367-378
Sept.2008
13. Stein,S.and Wysession,M., 2003,An Introduction to Seismology, Earthquakes and Earth StructureBlackwell Publishing,350 Main Street, Malden, MA 02148-5020, USA
14. Syed Humayun Akhter, the 5th International Workshop on Seismotectonics and Earthquake Risk
Management 2015, Abstract Volume,Yangon, Myanmar
15. Pictorial Guide to Bagan ,Ministry of Culture, Archaeology and National Museum
Department ,The Union of Myanmar, Yangon.
16. Thein Lwin, Deputy DG, Department of Archaeology and National Museum, Nay Pyi Taw,
Myanmar Symposium on Earthquake and Related Risks Reduction 2016 .
17. Tettoni: Burmese Design & Architecture, published by Periplus Editions (HK) Ltd.2000, Printed
in Singpore.

976

Investigation on Ancient Brick Masonry andRepair Mortar Properties in Post-Earthquake
Rehabilitation Process of Ancient Bagan
Monuments
T.M. SAN1, K.KYAW2
PhD, Civil Engineering Department,
2
Professor, Civil Engineering Department,
Yangon Technological University,
Myanmareimon007@gmail.com1, kyaw.u.kyaw@gmail.com2
1

ABSTRACT
Most of the monuments in Bagan are Brick masonry and few are stone masonry. Allof these monuments are vulnerable to both disaster and natural degradation. After2016 Chauk Earthquake, most of the monuments were damaged and post-earthquake
rehabilitation work is required. In order to make proper conservation and repairing
work, it is important to know the properties of ancient bricks and repair materials.
Therefore, the physical, and mechanical properties and Energy Dispersive X-ray
analysis of the ancient bricks from different monuments of 11 AD, 12 AD, 13 AD and
18 AD were investigated. It is important to use the similar materials in the repairingof ancient monuments so that the physical properties and chemical characterizationof the new brick from the modern brick mill near Bagan was also performed. Then,the chemical properties and acid digestion tests of ancient mortars were experimented
in the laboratory. The evaluation of the physical properties results showed thatancient bricks were in good range of water absorption. The compressive strength of
the ancient bricks were various due to the location of the sample, but most of theancient bricks have high compressive strength. The chemical characterization results
showed that the composition of the ancient bricks and modern bricks were similar but
not identical. The chemical composition results of ancient mortar showed that limebased mortar was used in ancient mortars. The binder to aggregate ratio of mortar
samples was different on the purpose of usage. Based on the results, the suitableproportion of mortar was proposed and, the properties of repair masonry properties
were scientifically experimented.
Keywords: ancient monuments, brick masonry, physical properties, mechanicalproperties, chemical properties, repair mortar.

77

December 2019, Yangon, Myanmar

1. INTRODUCTIONIn Myanmar, earthquakes frequently occur and these bring little to severe damage toancient monuments in Bagan so that conservation work has been carried out from thecolonial period to until now. After 2016 Chauk earthquake, 389 numbers of monuments
was listed as damaged monuments as shown in Figure 1. However, only 39 numbers
were considered in severe conditions [1]. Reviewing the lessons learned from the Chauk
earthquake, it can be seen that the compatibility of new and old materials is very
important in conservation work. Not only for the rehabilitation of damaged monuments
but for seismic risk analysis of ancient monuments, but the actual material properties ofancient materials are required. The ancient bricks and mortars from damaged
monuments were collected and experimented in Structural Engineering laboratory of
Yangon Technological University. Physical and mechanical properties of ancient bricks
such as unit weight, absorption rate, compressive strength and flexural strength were
investigated. The chemical properties of ancient bricks were also analysed by Energy
Dispersive X-Rays analysis. Then, the chemical properties of ancient mortar such as
chemical composition, and morphology were also examined. After that, acid digestion
tests of ancient mortar samples were carried out in order to know the proportions. In
practice, there is a proportion used by mason of repair work in rehabilitation although
the scientific investigation is lack in this repair mortar. Reviewing the acid digestion
tests results and Bagan style mortar used in reconstructed work, the suitable proportionis proposed and the experiments for physical and mechanical properties of repair
mortars and bricks is carried out.

Figure 1. Location Map of Damage Monuments

Investigation on Ancient Brick Masonry and Repair Mortar Properties in Post-Earthquake
Rehabilitation of Ancient Bagan Monuments78

2. CHARACTERIZATION OF ANCIENT BRICKS
The ancient bricks from Bagan monuments have different sizes. The average size ofancient bricks varies from (400 mm × 180 mm × 40 mm) to (290 mm × 160 mm × 30mm). Modern brick’s size in Myanmar is generally (225 mm × 115 mm × 75 mm).
That is why the size of modern brick is unsuitable with repair work of damaged
monuments. Then, another point should keep in mind is that the compression or bearing
capacity of repair mortar should have a compatibles strength with brick. The ancient
brick sizes vary from monuments to monuments. Even in the same monument, the bricksizes are different from the purpose of usage. Some of the bricks have a concave surface
at the base and plain surface at the top. The depth of the curve varied from 2.5 to 3 cm.
Although the bread and width of the modern brick are smaller than the ancient bricks,
the depth of the modern brick is greater than the old ones. In Table 1, the list of samples
is presented. The physical properties of bricks such as unit weight and absorption rate ofancient bricks and new bricks experimented according to ASTM C-67 and the results
were shown in Figure 2.
Table 1. Sample Lists of Ancient Bricks and Modern BrickNo

Monument
nameConstructe
d period

Sample description

1

Abae
Yadanar (AY)

11AD

Only one brick of full size
(ancient brick)2

Ananda-OkKyaung(AOK)(17761785)

3

Mingalar
Zedi (MGL)

13AD

broken bricks (some are more than the half size ofthe actual brick size of the monastery) (ancient
brick)
Broken bricks under the ground which are larger
than the half of the original size(definitely ancient
brick)

4

MyayPonTharPhayarHla 12AD
(MPT)

full-size bricks appropriate for tests (not certain
ancient or new brick)5

Pu Htoe Thar 13 AD
Myar (PHTM)

Full-size bricks appropriate for tests (ancient
brick)

6

Pyat Sa Shwe 12 AD
Gu (PSSG)

Half-size brick appropriate for the test (ancient
brick)

7

SatanarGyi
(STG)

13AD

Full size and half size of bricks free from cracks(ancient brick)8

Sulamani(SLMN)

13AD

full-size bricks and half size bricks appropriate for
tests(ancient brick)9

Modern Brick(MB)

Currently,use

full-size bricks appropriate for tests (new brickfrom mail)79

December 2019, Yangon, Myanmar(b)(a)
Figure 2. Physical Properties of Ancient and Modern Bricks(a) Unit Weight (b) Absorption Rate
The mechanical properties of ancient bricks are concerned for the structural analysis ofancient monuments. So, the compressive strength of ancient bricks and modern bricks
were also examined and the results were shown in Figure 3.

(a)

(b)

Figure 3. Mechanical Properties of Ancient and Modern Bricks(a) Compressive Strength (b) Flexural Strength
In order to know the quantitative results of the chemical composition of brick, EnergyDispersive-X-ray-Fluorescence (EXDRF) test is performed on the bricks. The results ofmost of the bricks showed a very high amount of silicon dioxide followed by aluminium
oxide, iron III oxide, and potassium oxide. The chemical compositions of ancient andmodern bricks are similar.
2. CHARACTERIZATION OF ANCIENT MORTAR
Ancient mortar samples from damaged monuments were collected and chemical
analysis such as EDXRF analysis, acid digestion tests, and Scanning Electron
microscopy experiments were carried out. From the EDXRF results, most of the ancientmortars contain Calcium oxide as the main constituents followed by silicon dioxide,
Sulphur trioxide, and Iron III oxide and potassium dioxide. The average comparison
results for ancient stucco, mural painting plaster and cement mortar from rehabilitation
work are shown in Figure 4.
Investigation on Ancient Brick Masonry and Repair Mortar Properties in Post-Earthquake
Rehabilitation of Ancient Bagan Monuments

80

Figure 4. Oxide Compositions of Ancient Plasters andCement Mortar from Intervention Work
Form the SEM images, the morphology of ancient mortar showed that the present oflime. Due to these results, the ancient mortars were considered as lime-based mortar.
Then, acid digestion tests on different samples are carried out and the binder toaggregate ratios are presented in Table 2.
Table 2. Samples of Acid Digestion Tests
Monument nameLocation andConstructed appearance
periodSula Mani(SLMN/LM)

12 AD

Ananda-Ok-Kyaung(2162/ LM)(17761785)

448(448-/LM)

13 AD

Aggregate Binder
percentage percentage

from the south wallof level 1

68%

32%

from the southernwall of monuments

49%

51%

from intervention
place

82%

19%

3. EXPERIMENTAL STUDIES ON REPAIR MORTAR PROPERTIES AND
MASONRY UNITS
From the chemical composition and the acid to binder proportion results of ancientmortar form Bagan monuments; one can notice that the results differed depending on
the purpose of usage. Moreover, the plenty of monuments for rehabilitation and repair
works and the management problem brings to use the different proportion of materials

81December 2019, Yangon, Myanmar

in repair mortar. The lack of scientific investigation on repair mortar in practical works
brings various problems such as the difference in colour, mechanical properties,
physical properties of old and new masonry works. This condition can lead to serious
damages in natural disasters such as earthquakes because of the different earthquake
resistance of the old and new mortar and bricks. In order to overcome such problems,
the preparation of repair mortar based on experimental results and current practice ofmortar proportion in Bagan was carried out. The major materials of mortar such as lime,
sand, brick dust and organic materials from Bagan were collected from reconstruction
sites of some monuments. The required test on raw materials from Bagan was carriedout and the results showed that these materials are good for repair work. To prepare
mortar, the ingredients such as lime, sand, brick ducts, U-shit fruit, and jaggery wereprepared first. Brick prisms were made with bricks of same sizes of ancient ones which
are purposely manufactured for reconstruction and repair parts.
3.1 Experimental studies on repair mortar properties and masonry units
For compressive strength and bending strength of bricks, 5 specimens for each test wereprepared according to ASTM C-67. For mortar cube strength, 50 mm cube of mortar of
15 specimens were prepared for 28 days, 45 days and 60 days results. A period of 28days, the mortar samples were at the stage of forming solid so that tests were carried out
for 45 days and 60 days periods. The compressive strengths of brick and mortar are
shown in Table 3.
Table 3. Compressive Strength of Brick and Mortar
Specimen

Compressive Strength (MPa)BrickMortar45 days

60 days

1

7.3

0.7

0.9

2

11.0

0.7

1.2

3

2.2

0.7

0.9

4

14.3

0.7

1.1

5

8.0

0.7

0.5

For the compressive strength of masonry, 5 solid unit prism specimens (305 × 305 ×
152 mm) of height to thickness ratio 2 were prepared and tested according to ASTM
C-1314. The bricks of the same size with ancient bricks and the repair mortar were used
to construct these prisms. The construction sequence of prisms, transporting of prisms,
curing, and preparation for testing was conducted according to standards. The testingprocedure is also according to ASTM C 1314. The compressive strength of all of theprisms with respective strain values is presented in Figure 5. The compressive strength
Investigation on Ancient Brick Masonry and Repair Mortar Properties in Post-Earthquake
Rehabilitation of Ancient Bagan Monuments82

of masonry prisms varies from 0.5 MPa to 2.3 MPa with the minimum strain values of
0.009 to maximum strain value of 0.025.

Figure 5. Stress-Strain Curve of Compressive Strength Test of Prisms
For the flexural test, 5 prisms with the length of 480 mm” were prepared and tested
according to ASTM C-518. For diagonal shear strength, 5 prisms were prepared andtested according to ASTM C-519 but the sample size is small enough to fit the testingmachine. The sample size of 305 × 305 × 152 mm walls was tested for diagonal shear
test. The loading apparatus for flexural test and diagonal shear test of the masonry
prisms are shown in Figure 6.

(a)

(b)

Figure 6. Loading Apparatus (a) Flexural Test (b) Diagonal Shear Test

83

December 2019, Yangon, Myanmar

The flexural strength of specimens was shown in Table 4. This value of repair masonryis very much lower than that of other type of mortar.
Table 4. Flexural Strength of Masonry Units
Specimen

Flexural Strength (MPa)

F1
F2
F3
F4
F5

0.03
0.07
0.07
0.05
0.10

From the test results, the diagonal shear strength of masonry prisms is very small. The
values of 5 samples were shown in Table 5. The experimental results show that thestrengths of masonry units with traditional lime mortar were very much less than that ofother types of masonry units with different mortar.
Table 5. Diagonal Shear Strength of MasonrySpecimens

Shear Modulus (MPa)Shear Stress (MPa)Shear Strain

D1
D2
D3
D4
D5

16
37
20
13
52

0.23180.37980.34250.20730.18000.01490.01030.01690.01600.0034

4. CONCLUSION
Most of the compressive strength of ancient bricks is higher than that of modern bricks.
The chemical analysis results of ancient mortars show that lime-based mortar was usedin the ancient monuments. The use of organic materials in ancient mortar cannot be
traced from chemical analysis of this study. However, the binder to aggregate ratios ofmortar is different based on the purpose of usage. So, Bagan style repair mortar
composed of lime putty, sand, brick dust, and organic material which is used inrehabilitation work of Post-earthquake Bagan monuments have also experimented inlaboratory. The compressive strength and flexural strength of repair mortar and masonryunits showed that they are compatible in strength with ancient masonry units for local
repair work.
REFERENCES[1] Myanmar Earthquake Committee, “Rapid visual survey for damages of monuments
and buildings due to Chauk Earthquake,” Report of Myanmar Earthquake
Committee, 2016.
[2] “ASTM. Standard test method for sampling and testing bricks and structural clay tile.
C 67-02, ASTM International,” West Conshohocken, United States, 2002.
[3] “ASTM. Standard Test Method for Examination and Analysis of Hardened Masonry
Mortar. C 1324-03, ASTM International,” West Conshohocken, United States, 2003.
Investigation on Ancient Brick Masonry and Repair Mortar Properties in Post-Earthquake
Rehabilitation of Ancient Bagan Monuments

84

LESSONS LEARNT FROM THE DAMAGE AND RESPONSE
OF THE 2016 KUMAMOTO EARTHQUAKE IN JAPANK. MEGURO1
Director/Professor, International Center for Urban Safety Engineering (ICUS),
Institute of Industrial Science (IIS), The University of Tokyo (UTokyo), Tokyo, Japan,
meguro@iis.u-tokyo.ac.jp
1

Keywords: 2016 Kumamoto Earthquake in Japan, foreshock, main shock, aftershock, Level 1 and 2 ground motions,
Disaster response activities
1. 2016 KUMAMOTO EARTHQUAKE DISASTER
At 21:26 (Japan local time) on Thursday, April 14, 2016,an earthquake (M6.5), which was thought main shock atthat time but later was called the foreshock, occurred in
Kumamoto Prefecture, Kyushu Island, Japan. Due to theearthquake, severe ground motion with seismic intensity
7 of JMA (Japan Metrological Agency) scale, the highest
among 10 levels of the scale, was recorded. At 1:25 (Japan
local time) on Saturday, April 16, 28 hours later, anotherearthquake (M7.3) attacked the area affected by the foreshock with again, seismic intensity 7 of JMA scale. With
these two earthquakes and other a series of aftershocks(seismic intensity 6+: twice, seismic intensity 6-: 3 times),
approximately 200,000 buildings were damaged. Totally,
50 persons were killed and among them, 10 were due tolandslide and 37 were due to building damage (7 by aforeshock, 30 by a main shock). Furthermore, over 200
people were killed by indirect causes, such as stress andaggravation of illness during the life in refugee centers. In
this paper, I will introduce the lessons learnt from damage
due to the 2015 Kumamoto Earthquake and its disaster
response activities.
2. EFFECTS OF A SERIES OF STRONG MOTIONSWith Japanese aseismic design code of infrastructure
and building structures, we consider two different levelsof ground motions i.e. Level 1 and Level 2. The Level 1
ground motion may attack the structure once or twice
while it is in use. But the structure must be functional evenafter the earthquake. While the Level 2 ground motion, it
is considered the ever severest motion attacked the target
area in the past. Therefore, we assume that the Level 2
ground motion may not attack the target structure morethan twice during the time of its use. And the structure
may have some damage but should not injure and kill theusers. Seismic intensity 7 of JMA scale is considered
Level 2 ground motion. However, in case of the
Kumamoto earthquake, a series of strong ground motions
including twice seismic intensity 7 ground motion,
attacked the affected area and many structures weredamaged. Therefore, from now on, we should consider thephenomena that multiple very strong ground motions
attack the structure and development of a methodology
and implementation system for quick and accurate
inspection to evaluate the remaining seismic capacity of
exposed structure by these ground motions. While, theidea that a series of strong ground motions increased thenumber of fatalities is not correct. According to thequestioner survey (CIDIR Newsletter, Vol. 32, 2016.6.1)

carried out for the people in the affected area, it was found
the following facts. At the time of the fore shock (9:26 PM
on April 14), 87.2 % of the people were at their own
homes (people at company or school: 4.3%, people on theway to the home:4.0 %, etc.). While at the time of main
shock (1:25 AM April 16), 22.0 % of the people were attheir own homes (people at public refugee camp: 28.7 %,people at their friends’ home: 11.3 %, people outside of
their home including staying in their cars at parking, etc.:
31.2 %). This is the evidence that many people withdamaged residential houses (relatively lower seismic
capacity ones) moved to public refugee camps and friends’
houses (relatively higher seismic capacity ones) andevacuate to outside of the structures for fear of additional
damage due to strong aftershocks. If the main shockattacked the area in midnight on the 16th without theforeshock on the 14th April, nearly 100% of the residents(most of them were sleeping), were in their residentialbuildings, including low earthquake resistant capacity.
Although in both the foreshock on 14th and the main
shock on 16th, seismic intensity 7 of JMA scale wasrecorded, it was found based on the analysis that main
shock ground motion was much stronger than theforeshock motion. Main shock ground motion had powerthat could make similar magnitude damage due to the
combined power of the foreshock and main shock groundmotions. Therefore, when we estimate the number ofdeaths in this situation from the total number of buildings
collapsed (approximately 8,400 buildings) assuming thesame ratio between the number of collapsed buildings(approximately 105,000 buildings) and that of death toll
(approximately 5,500) in case of the 1995 Kobe
earthquake, the number of deaths becomes 440.
Moreover, when the occurrence time of the earthquake isconsidered (Kobe 5:46 am, Kumamoto 1:25am), thenumber of death might become more as search and rescue
condition of the Kumamoto earthquake was worse. Basedon these facts, it can be told that the foreshock on 14th
contributed a lot to reduce the casualties and it has great
meaning of an alert to the people.
3.LESSONS LEARNT FROM DISASTERRESPONSE ACTIVITIES(1) Lessons on “push-type support”
In the Kumamoto earthquake disaster, the national
government of Japan implemented “push-type support”
for the first time to support human resources and supplies851) Lessons for both supporter and recipient・ Standardization of disaster response operations (country, prefectures, municipalities) and training

2) Lessons for supporting side・ Undeveloped criteria for implementation of "push-type support"
・ About relief supplies:a) Simplification of complicated procedures from procurement to shipmentb) Examining the method of transporting relief supplies to the affected areasc) Securing the goods tracing method to grasp their position in transit and the inventory status of goodsd) Planning and development of the last one mile from the regional logistics base to the evacuation
centere) Construction of a logistics system that allows country, prefectures, municipalities, manufacturers, andlogistics operators to share information on order status, manufacturing status, transportation status,
etc., and practical training for implementationf) Development of a supply capacity map by goods to enable efficient transportation of goods fromnearby areas.
・ About human resources support:a) Inadequate advance care for temporary staff(on-site dispatch with insufficient prior explanation
regarding work contents)b) Issues related to temporary staff's working environment, living environment, working conditions, etc.
c) Development and maintenance of a temporary staff list including past disaster response experience,
information on work place and place of birth (persons who are from affected area or had work
experience in the area could work efficiently)

3) Lessons for recipient・ Insufficient capacity to receive support due to lack of experiencea) Lack of extraction of disaster response work that the recipient wants external supporters to dob) Securing space for external support activitiesc) Improvement of living environment for supporters in the affected areas

Figure 1 Lessons learnt from the 2016 Kumamoto Earthquake Disaster and Its Response Activities
without waiting for requests from the affected areas. This
support has achieved certain degree of the results, such as
promoting disaster response of the confused local
governments and resolving the shortage of major supplies
such as water and food in the affected areas. However,from a series of reviews, various issues as shown in Figure
1 can be pointed out.
(2) Impact of Merge of municipalities in Heisei Era
In addition, the effects of merge of municipalities in the
Heisei Era have had a major impact on the issues related
disaster response as described below.
The number of the municipalities in Japan was about
3,350 at the end of the Showa Era (late 1980'), become
1,741 due to the merger in Heisei Era. The number
becomes nearly half and area becomes large, but in termsof population, the municipalities with a population of
100,000 or less is 85% of the total, with the population ofless than 30,000 is 53% and with a population less than
10,000 is 27%. The number of governmental officials has
been reduced by the merger, and their number per
population has decreased from before the merger. As aresult, the current number of officials working at disastermanagement department in municipalities is around 10 for
a population of 100,000, about 2 to 4 for 30,000, and 1, 2
concurrent staff working at other department at the sametime for less than 10,000.
Earthquakes, typhoons, and heavy rains (called hazards)
occur regardless of the spatial extent and administrative
boundaries of the basic municipality. The merger has
reduced the resources for disaster response, but thefrequency and scale of hazards has not decreased. Rather,
it is increasing considering the current seismologicalenvironment surrounding Japan and the dangers of
extreme torrential rains and huge typhoons associatedwith global warming.
Comparing the current disaster response conditions
based on the population of local governments, the numberof disaster-stricken population decreases in local

86

governments with a small population. However, since thepopulation density is low, it is often widely distributed, so
the damage distribution is wide for the number of affected
population. Also, damaged areas including infrastructuredamage, landslide disasters, forests and farmland are often
widespread even if the population is small. Therefore, inJapan, a society with a declining birthrate and an aging
population, the disaster response of small population
municipalities will inevitably become stricter in the future.
In this situation, the points I consider important aredescribed below from the perspectives of “damage
reduction” and “future disaster response enhancement”.
・ To reduce damage in future
The first is the viewpoint of future damage reduction.
According to Mr. Hiroya Masuda, the population of local
municipalities will continue to decline in the future, andmarginal settlements will occur in various places and face
the danger of disappearance. Under such circumstances,instead of letting the change in population naturally leave
the number and distribution of conventional villages as
they are, the risk of disaster in each region is evaluated,
and it is important to guide the people from high risk areas
to lower risk areas. This measure can be implemented
effectively in a society with a declining population, andthis will make it possible to create a happy environment
for both people who move in and who receive them.
At this time, the important point is that it will bedifficult for both the government and citizens to make a
big financial burden. Therefore, it is important to movethem to the spaces with low risk of disaster that become
open due to depopulation, at the timing such as whenmoving or rebuilding houses in citizens' life plans. In thisway, even if there is no special countermeasure cost or
budgetary measure, the disaster risk and damage amountof the local government as a whole will be greatly reduced,
and the disaster response environment will be greatly
improved. Different from the past, considering thefinancial condition of Japan, it is impossible to takemeasures to protect a small number of people, living inareas with a high disaster risk, spending an enormous cost.
・ To strengthen disaster response capabilities
Next is the strengthening of disaster response
capabilities. My conclusion is that we should revise theDisaster Basic Act and establish a new system thatchanges the responsibility for disaster response frommunicipalities to prefectures. Based on the experience ofthe 2011 Great East Japan Earthquake Tsunami Disaster,
despite the jurisdiction moved from the Ministry of Health,
Labor and Welfare to the Cabinet Office, the prefectural
governor is still responsible for responding to the Disaster
Relief Act.
Actual experience is important for appropriate disaster
response, but even in Japan, which is often called adepartment store for disasters, the frequency is not high if
the time and area are limited. Therefore, it is difficult forthe municipality officials of disaster management
departments in each municipality to have actual
experience during their several years working term at the
department. As a result, large-scale disaster response inmunicipalities is “always the first experience” and starts
with the situation “I don’t know what to do”. Given theenvironment surrounding the current and future
municipalities, there is no question how difficult it is toaccumulate and inherit disaster response experiences andlessons individually in over 1,700 municipalities in Japan.
On the other hand, a prefecture that bundles dozens ofmunicipalities experiences at least one or two disaster
responses per year. Even for a term of several years, allpersons of the disaster management department canexperience of disaster response from several to ten times.
Pre-disaster countermeasures should be promoted mainly
by municipalities that know the region well because thereis time. However, in the local government with a small
population, it is not easy to appropriately manage up totens of times more people than the persons who regularly
manage, including external support staffs and volunteers,
for the first time disaster response. In the future, disaster
response know-how and lessons should be accumulated
and inherited in prefectures, and a system should be built
to manage disaster response in the affected municipalities.
However, since the number of persons at disastermanagement departments in prefectures is small, it isimportant to secure the number of personnel byexchanging personnel with municipalities and to build ahuman network through exchanges during normal times.
When a disaster occurs, the prefecture will visit themunicipality and manage the disaster response, and themunicipality will be responding to the disaster under thecontrol of the prefecture, with the people who haveexperienced personnel exchanges as the contact. It isnecessary to establish such a system on the scale of thenation and to connect prefectures with each other for thehuge disasters, due to such as Tokyo Metropolitan inland
earthquake and Gigantic earthquake along the Nankai
Trough earthquake.
Also, out of the disaster response work that the local
government is currently in charge of, consider theexperience and expertise, it is also important to extract thework that can be outsourced, and entrust this to aprofessional contractor or highly specialized volunteer.

By doing so, it becomes possible to reduce the disaster
response work that the local government should tackle.
Reforming awareness is also important when
dispatching support staff to the affected areas. In otherwords, damaged area support is important not only for theaffected area, but also as an opportunity for local
government officials, who are dispatched to the affected
area, to learn disaster response. On the other hand, whe alarge number of officials are dispatched, the work of thedispatching local government becomes difficult, so anationwide system that uses healthy OBs and OGs (retired
staff) to make up for this should be constructed.
Nishihara Village was a successful example in the
Kumamoto earthquake disaster response. Village staffs
dispatched to Higashimatsushima City, one of the severely
damaged areas by the Great East Japan Earthquake andTsunami disaster, could play an active and important rolein this earthquake disaster response. They engaged indisaster response in Higashimatsushima City and learnt alot disaster response and built a network with affectedmunicipality. When the Kumamoto earthquake occurred,mayor of the Nishihara village moved them, who were
working other departments, back to the disastermanagement department to respond earthquake disaster.
In addition, immediately after the earthquake, Higashi
Matsushima City officials came to Nishihara Village tosupport disaster response activities. This is the reason why
Nishihara Village's disaster response has become more
efficient despite the severe damage.
In order to enhance the disaster response capabilities ofthe entire country, it is important for people outside thedisaster-stricken area to learn by sharing past lessons andsupporting disaster-stricken areas when disasters occur invarious places. If this is not successful, we should
recognize that the future disaster response for hugedisaster, such as the Tokyo metropolitan inland earthquake
and Gigantic earthquake along the Nankai Trough, will be"a tough battle without practice".
4. TOWARDS FUTURE LARGE-SCALE DISASTERRESPONSE
We learned many challenges and lessons from thedamage and disaster response in case of the 2016
Kumamoto earthquake. However, the biggest lesson isthat there is no way to achieve an efficient disaster
response for expected huge earthquake disasters, such as
due to the Tokyo Metropolitan inland earthquake and thegigantic earthquake along the Nankai Trough, by only
reviewing a series of responses to the Kumamoto
earthquake disaster (Figure 2). For disasters of thesescales, we should consider both the available resources
and the scale of the damage as well as the season, the timeof occurrence, multiple large earthquakes with a certain
time interval, complex disaster combined with otherdisasters, etc. Based on these conditions, it is necessary toplan and implement drastic measures, including themeasures described in Chapter 3 of this paper.

87

(a) Death Toll (direct)
x1（100）x10（101）x100（102）

x1,000（103）x10,000（104）Times(b) No. of Collapsed and Burned buildings
x1（100）x10（101）x100（102）

x1,000（103）x10,000（104） Times(c) Economical Loss
x1（100）x10（101）x100（102）

x1,000（103）x10,000（104）Times(d) Damaged Area (No. of Severely Damaged Prefectures)x1（100）x10（101）x100（102）

x1,000（103）x10,000（104） Times

Figure 2 Comparison of the Kumamoto earthquake damage with other earthquake damages in Japan88

MICROMECHANICAL INSIGHT INTO STABILITY OF SUBSURFACE CAVITY
M. OTSUBO1, U. ALI2, and R. KUWANO3
1

Research Associate, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan,
Graduate Student, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan,
3
Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan,
Correspond to Dr. M. OTSUBO (otsubo@iis.u-tokyo.ac.jp)

2

Keywords: Subsurface cavity, Cave-in, Discrete element method, Laboratory model test
1. INTRODUCTION
Modern cities face an increasing number of road cavein problems, primarily due to defects in buried structurescaused by damaged or aged sewer pipes, or by improper
works during poorly controlled constructions. Such
defects in underground structure may trigger internal
erosion of surrounding soils due to seepage action by
underground water or heavy rainfall, eventually resulting
in formation of subsurface cavities.
To prevent catastrophic road cave-in accidents, nondestructive technique such as ground penetrating radar(GPR) that can find a subsurface cavity and visualize its
shape is often used in practice. However, our current
knowledge is insufficient to judge confidently whether anexisting cavity is stable or about to collapse due to lack offundamental understanding on the stability of the groundhaving a subsurface cavity. The present research aims todevelop a numerical simulation method to assess stabilityof subsurface cavity based on its geometrical information
obtained using GPR technique.
2. MODEL TEST OBSERVATION
Prior researchers have investigated how a subsurface
cavity is formed and expanded influenced by water flowusing laboratory model test (Fig. 1) [1]. Ohara (2019) has
reported that the stability of the ground with a cavity isrelated to both the width of cavity and the depth of the soil
cover above cavity, and the geometrical data can be used
for a risk assessment [1]. However, the observation fromthe model test was limited to the ground deformation andthe resistance against vertical loading; thus, fundamental
understanding of mechanical responses, e.g. stiffness orstrength, is required.

Figure 1. Subsurface cavity observed in model test
experiment (after Y. Ohara, 2019)

3. DISCRETE ELEMENT METHOD
Discrete element method (DEM), is a powerful tool toanalyze responses of individual particles. To hold asubsurface cavity firmly, this research implemented a newcontact model that considers inter-particle capillary forceswhere the degree of saturation is an additional input
parameter [2] in LAMMPS code [3].
DEM simulations were performed using assemblies ofboth spherical and non-spherical particles in a rectangularbox where the particles located inside a specified regionof specimen were deleted to mimic the formation of acavity (Fig. 2). The results revealed that inter-particle
capillary force, particle size and shape are keys to assess
the stability of soil structure with a subsurface cavity.

Figure 2. Example of present DEM simulation.
3. CONCLUSIONSThe present study aims to develop a numerical method
to evaluate the stability of the soil having a subsurface
cavity. The DEM simulations can effectively capture themicroscopic response observed in the model test. Physicalparameters relating to the particle-scale responses thatcannot be measured from the model test will be analyzed
further in the on-going research to improve the risk
assessment technique for cave-in problems.
REFERENCES[1] Y. Ohara (2019) A study on the process of expansion
and collapse of subsurface cavities for risk evaluation ofroad cave-ins, Master Thesis, The University of Tokyo.
[2] U. Ali, M. Otsubo, R. Kuwano (2019) Implementationof suction-tension model for cavity simulations using
DEM. Proceedings of 54th Japan National Conference on
Geotechnical Engineering, 809-810.
[3] Plimpton, S. (1995) Fast parallel algorithms for shortrange molecular dynamics. Journal of Computational
Physics. 117, No. 1, 1-19.

89

ANALYSES ON LANDSLIDE EXTRACTION BY SYNTHETIC APERTURE RADAR SINGLELOOK COMPLEX IMAGES
P. GE1, H. GOKON2, K. MEGURO3, and S. KOSHIMURA4
Ph.D. Student, Meguro Laboratory, Institute of Industrial Science, the University of Tokyo, Tokyo, Japan,
Associate Professor, School of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa,Japan,
3
Professor and Director, ICUS, Institute of Industrial Science, the University of Tokyo, Tokyo, Japan,
4
Professor, International Research Institute of Disaster Science (IRIDeS), Tohoku University, Sendai, Japan,
Correspond to Ms. P. GE (gepl@iis.u-tokyo.ac.jp)
1

2

Keywords: landslide, synthetic aperture radar (SAR), single look complex (SLC), intensity, phase, receiver operating
characteristic analysis (ROC)
1. INTRODUCTION
The 2018 Hokkaido Eastern Iburi Earthquake, which
occurred on September 6, triggered more than 6,000
landslides over an area of 20×20 km [1], disrupting
transportation, communication, as well as electricity andpower service. A rapid mapping of the massive
earthquake-induced landslides was important for directing
rescue efforts and limiting resource allocation delays.
Synthetic aperture radar (SAR) is a potential tool for quick
landslide mapping even in harsh weather due to its large
cover, quick response, no contact, as well as light andweather independence capabilities. However, relevant
studies were still limited to individual landslides orcatchments with limited accuracy [2]. This study analyzed
the potential of SAR single look complex (SLC) images
acquired before and after the disaster for the massive
earthquake-triggered landslide extraction.
2. RESEARCH AREA AND DATA
The research area was around Atsuma Town, Iburi,
Hokkaido, where numerous landslides were induced in the2018 Hokkaido Eastern Iburi Earthquake. Applied SAR
dataset were two pre-event and one post-event ALOS-2
images acquired in the affected areas with an off-nadir
angle of 37.8 degree from left looking. All three images
were L1.1 SLC products represented by complex I and Q
channels to preserve magnitude and phase information.
The image acquisition mode was stripmap ultra-fine mode
single polarization (UBS), with a 3m spatial resolution
and a HH polarization mode. What is more, a landslide
inventory map created by [3] was employed as groundtruth data for result evaluation.
3. PARAMETER CALCULATION
Potential parameters that can be derived from the three
SAR images and have the capability to measure groundchanges were first selected according to SAR imaging
principals. Determined parameters included the intensity
difference, correlation coefficient, correlation coefficientdifference, and normalized coherence difference. SNAP
software was then employed to process the originalcomplex images for basic intensity and coherence
information extraction. And ArcGIS 10.5 was thenapplied for the final calculation of these potential
parameters.

90

4. PARAMETER ANALYSIS
After calculating the potential parameters, qualitative
observation was first performed by overlapping thelandslide ground truth data to the calculated SARparameter images. It indicates that the intensity difference
displays clear lower and higher values in landslide areas(Figure 1) as triggered landslides smoothed the hillside
areas and roughened the foothill areas. Besides, thecorrelation coefficient, correlation coefficient difference,and normalized coherence difference images all show
lower values in landslide regions due to the landslideinduced ground changes. Quantitative analysis was thenexecuted through receiver operating characteristic (ROC)
analysis to evaluate and compare the landslide mapping
performance of these parameters. It demonstrates that theintensity difference and correlation coefficient difference
have better capability for landslide mapping in these forest
areas compared with other parameters.

Figure 1. Intensity difference image overlapped by groundtruth landsides (red color: ground truth landslides)
5. CONCLUSIONSSAR SLC images have certain capability for massive
landslide detection as several derived parameters,
especially the intensity difference and correlation
coefficientdifference,
showedclear
different
characteristics in landslide and non-landslide areas.
REFERENCES[1] H. Yamagishi, F. Yamazaki, Landslides 15 (2018)
2521–2524.
[2] T. Konishi, Y. Suga, Eur. J. Remote Sens. 51 (2018)
205-221.
[3] S. Zhang, R. Li, F. Wang, A. Iio, Landslides 16 (2019)
1691-1708.

A FEASIBILITY STUDY ON THE SCALING OF OPERATIONAL MODE SHAPES OF BUILDINGUSING A SHAKER
G.K. Chaitanya1, M. Numada2, and K. Meguro3
Project Assistant Professor, Institute of Industrial Science, University of Tokyo, Japan,
2
Associate Professor, Institute of Industrial Science, University of Tokyo, Japan
3
Professor, Institute of Industrial Science, University of Tokyo, Japan
Correspond to G.K. Chaitanya (chaitugk@iitbombay.org)
Keywords: Operational Modal Analysis, FDD, Identification, mode shape scaling
1

1. INTRODUCTION
There are many methods to support numerical modelingof existing structures for understanding the condition of
the structures [1]; however, there is high uncertainty inestimation of the material properties. Estimating material
properties and conditions of structures from vibration tests
are gaining popularity, and one of the challenging aspects
is obtaining scaled mode shapes [2]. This research
explains a procedure for scaling of mode shapes withwhich operational mode shapes could be scaled to satisfy
the unit modal mass property of the system.
2. METHODOLOGY

system at one location in the building, and the input andoutput are recorded. This response is further used toestimate the scaling factors (Fig. 3) for the operationalmodes calculated earlier.
3. RESULTS AND DISCUSSIONS
The determination of scaling factors is done, and it can beseen that the accuracy of estimation has been evaluatedwith its variation with amplitude of shaking, duration of
shaking, and RMS ratio of response from the simulationand measured, as shown in Fig. 4.

Fig. 3 Scaling of mode shapes using shaker response
Fig. 1 Overall methodology of scaling of mode shapes

Fig. 1 shows the overall methodology where ambient
vibration tests are conducted to obtain the operationalmode shapes. As the outcome of these results are unscaledmode shapes, a method for scaling with a minimal forced
vibration test using a shaker.

Fig. 2 Measurement and experimentation of a building

A simplified numerical model is developed with a massspring-damper system for a four storey building (Fig. 2).
Whitenoise of 0-300Hz is applied, and the amplitude of
the response equivalent to measured response using
microtremor for buildings in Nepal. The natural
frequencies and operational mode shapes are obtainedusing frequency domain decomposition (FDD). The
shaker excitation (white noise) is applied in the same

Fig. 4 Parametric study of RMS ratios and error in scaling

The results show that longer duration of shaking andmeasurement is critical in reducing the scaling error, andhigher amplitudes do not contribute to the accuracy ofscaling; however it is essential in this case of a building toensure an RMS ratio to be higher than unity for scaling.
4. CONCLUSIONSA minimalist procedure using a vibrating shaker issuggested for modal testing to scale operational modeshapes obtained from the operational modal analysis. We
recommend this procedure for further evaluation anddevelopment of a multi-frequency shaker.
REFERENCES[1] Klaus G T and Norris S. (1995) Non-destructive damage evaluationof a structure from limited modal parameters. Earthquake Engineering& Structural Dynamics, 24(11):1427.
[2] Heylen W., Lammens S., and Sas P. (1997). Modal analysis theory
and testing Leuven, Belgium.

91

A STUDY ON THE METHODS OF UNDERSTANDING
VULNERABLE PEOPLE’S NEEDS USING SATELLITE SAR IMAGE
YUMA MORISAKI1, MAKOTO FUJIU2, RYOICHI FURUTA3,
TAKASHI SAKAI4, KAZUHIRO NAGAKI4, JUNICHI TAKAYAMA5, and YUTO SHIOZAKI6
Doctoral Course Student, Dept. of Environmental Design, Kanazawa University, Japan,
Associate Professor, Geosciences and Civil Engineering, Kanazawa University, Japan,
3
Remote Sensing Technology Center of Japan, Japan,
4
Master Course Student, Dept. of Environmental Design, Kanazawa University, Japan,
5
Professor, Geosciences and Civil Engineering, Kanazawa University, Japan,
6
Specially Assistance Professor, Dept. of Environmental Design, Kanazawa University, Japan,
Correspond to Ass. Prof. Makoto FUJIU (fujiu@se.kanazawa-u.ac.jp)
1

2

Keywords: large-scale earthquake disaster, vulnerable people, satellite SAR image, understanding location informationand needs
1. BACKGROUND OF THIS STUDY
In Japan, large-scale earthquake disasters frequently
occur. When a large-scale earthquake disaster occurs, it
becomes difficult to collect the victim’s needs, and at thesame time the realization of detailed support for thevictims also becomes difficult. Especially, vulnerable
people, for example elderly person, sick person, pregnant,
it is necessary to quickly grasp the location informationand needs. And efficient system is needed about quick anddetailed assistance from third party to vulnerable people.
In this research, we propose a method of understanding
various vulnerable people's needs and location
information using satellite SAR images. In this analysis,
as a basic study for understanding location informationand needs, we proposed an object with a shape and sizethat can be recognized by SAR.
2. ANALYSIS PROCEDURE OF THIS STUDY
In this research, satellite images acquired from
ASNARO-2 are used. ASNARO-2 is a SAR satellite
operated by NEC. In this analysis, satellite images
observed from Spotlight mode with 10km observation
width and 1m resolution are used. In this study, as a basic
study for a major research goal, we propose a target thatcan be observed by ASNARO-2.
Figure 1 shows the target proposed in this study. The
proposed target has an aluminum disk on the bottom anda petal-like partition on it. When the interval (inner angle)of the partition is set to 60 degrees and 40 degrees,
hexagonal or nonagonal “petals” are formed. Unlike theshape of a typical corner reflector, this shape has very little
direction dependency. These targets were devised and set
at the ASNARO-2 observation. The experiment date isJune 25, and the target is ideally arranged for the angle ofincidence of the microwave emitted by ASNARO-2.
3 RESULT OF EXPERIMENTS
Figure 2 shows the results of a target visibility
experiment. The visibility of the hexagonal andNonagonal targets can be confirmed. In addition,comparing the visibility of hexagonal and nonagonal

92

Hexagonal target

View from above

View from side

Nonagonal target

Shape with less direction
dependency
Bottom：Diameter 100cm
Height：50cm

Figure 1. Target details

Nonagonal target

Hexagonal target

Figure 1. Target details
targets, there is a difference in the backscatter indicating
the reflection intensity.
4 CONCLUSION AND FUTURE WORKS
As a result of experiments and analysis, the object
which we proposed was able to be recognized in SAR
observation.In the future, we will conduct experiments invarious areas considering land surface condition,
geographical features, etc. in order to examine theversatility of the object. In addition, we aim at theconstruction of bulk management visualization systemthat information of location information and needs.

SURVEY OF RECONSTRUCTION PROJECTS IN JAPAN AND MAKING THE DATABASEFOR DISASTER RESPONSE WORK
1

R. ITOH1, K. MEGURO2, and M. NUMADA3
Graduate Student, Department of Civil Engineering, The University of Tokyo (UTokyo), Tokyo, Japan,
2
Director/Professor, International Center for Urban Safety Engineering (ICUS),
Institute of Industrial Science (IIS), UTokyo, Tokyo, Japan,
3
Associate Professor, ICUS, IIS, UTokyo, Tokyo, Japan,

Keywords: Reconstruction, Recovery, Restoration, Construction cost, Disaster response, Local government
1. GENERAL INSTRCUTIONSWhen local governments suffer large-scale natural
disasters, they should first estimate the costs to make plans
for recovery and reconstruction after assessing the damage.
The cost estimation work for reconstruction will benormally carried out by the government officials. But due
to lack of experience of disaster response, it is usually very
difficult for them to do properly.
Japan is sometimes called department store of natural
disasters. Even in Japan, it is practically impossible for all
officials to have actual experience of disaster response,
considering the relation among the frequency of big
disaster, area of municipality, and their working durationof disaster management section. Also, it is very rare thatthe local government had similar disaster experiences andtheir records. Moreover, the number of local government
staff is decreasing due to the decrease in public works,
then when a disaster attacks certain municipality, many
staff from other municipalities are dispatched to disasteraffected municipality to support it [1]. When they suffer
damage, they look for past construction cases forrestoration work of individual damaged parts, build up
construction costs based on them, and estimate a cost forreconstruction. This work is very time-consuming and is
one of the causes of delaying the initial movement ofdisaster recovery. A delay in the initial recovery fromdisasters not only promotes the anxiety of the people in
the affected area, but may also delay the completion ofrecovery and increase construction costs.
In addition, in the areas where large-scale earthquake
and tsunami damage is currently expected, it is consideredthat prior reconstruction is necessary. However, thediscussion of plans in the absence of a specific amount ofbudget lacks feasibility.
Table 1. Number of dispatched local government staff inthe 2011 Great East Japan Earthquake andTsunami disaster [2]Number of officials
dispatched
Date
Cumulative
Currently
numbernumber
1st Jul. 2011
56,9232,460
1st Oct. 2011

73,802

1,211

1st Jun. 2012

79,107804

2. OBJECTIVE
In this research, we aim to support local governments
for disaster response operations or making a priorreconstruction plan that can quickly and easily create costestimates for disaster recovery. For that purpose, weinvestigate the contents and amount of budget of eachconstruction of the reconstruction projects in the pastlarge-scale disasters, such as the 2011 Great East Japan
Earthquake and Tsunami disaster.
3. METHODOLOGYFirst, as a preliminary survey, we investigate businesses
that are relatively easy to obtain materials. Usually,
governments release the contents of the bid and contract.
We extract the work related to disaster recovery andreconstruction from all the construction works. From thepublicly available information, the name, location, type ofindustry, amount of budget, etc. of each construction canbe obtained. We examine the forms of damages,
construction methods, and types of materials related toconstruction, etc.
Next, we collect the information not disclosed. Since
the format and contents differ depending on theorganization, we need to collect the missing information
by asking the organizations to provide inquiry materials.
In addition to public information, we also collect detailed
information about each construction, such as accumulated
contents and damage status of the construction site. Create
questionnaires that make it easy to get answers whensurveying each local government and to summarize at thetime of tabulation.
Finally, we create the database. By linking damage
scale and construction scale, construction scale and cost,
the cost of recovery and reconstruction work can becalculated from the damage situation. Unit price anddamage scale will be variables for construction costcalculation.
4. CONCLUSION
Study results and conclusion will be introduced at
USMCA 2019 in Yangon.
REFERENCES[1] Mori Yoshihisa (2015), Recent efforts in public
procurement, JICE report, No.28, pp. 64-67
Reference to a website:[2] “Efforts by the Ministry of Internal Affairs andCommunications to support local governments
affected by the Great East Japan Earthquake”,
Ministry of Internal Affairs and Communications,
http://www.soumu.go.jp/menu_kyotsuu/important/70131.html (accessed 2019-9-28)

93

A STUDY ON ANALYZING ROAD NETWORK PATTERNS AND PROXIMITY GRAPHSIN TERMS OF EFFICIENCY IN ROAD TRANSPORTATION
Daisuke WATANABE
Associate Professor, Department of Logistics and Information Engineering,Tokyo University of Marine Science and Technology, Japandaisuke@kaiyodai.ac.jp
Keywords: Road network patterns, Proximity graphs, Route Factor

2. MODEL DESCRIPTION
A graph defined by the proximity of points on a plane
exemplified by DT and a minimum spanning tree(MST)
is generally called a proximity graph and there are many
applications in engineering, particularly to morphologicalproblems[1]. By creating a proximity graph based on road
points extracted from an existing road network and thencomparing a graph edge to an actual road network, we canclarify the principles for creating a road segment[3].
Ten cities representing the east coast, inland, and west
coast regions were chosen for this study. The Census
TIGER/Line is used as the data source for the inner cityroad networks of U.S. cities.
Network Distance is calculated as the distance ofshortest path of two points on the Network. Route
Factor(RF) that is the major index for travel efficiency is
calculated as the ratio of Network Distance to Euclidean
Distance[2]. Demand points are 1000 points which are
randomly generated along road network. Travel Demandis defined as the pair from all nodes to all nodes except
oneself (Total: n(n-1) =999000 OD pairs)
3. CONPUTATIONAL RESULTAs shown in Figure 1, Route Factor(RF) in All Cities
shows the following relationships: RF(DT) < RF(GG) <RF(Road) < RF(RNG) < RF(Rectilinear). Route Factor on
Road network is intermediate of that of GG and that of
RNG in almost all cities. Travel Efficiency on Road
network is intermediate of GG and RNG except San Diego.
The highest city in travel efficiency is New York. High
travel efficiency correlates with High connectivity andHigh density road network.
As shown in Figure 2, the distribution of Route
Factor(RF) of Road network in New York is the

94

1.3

1.25

1.2

Route Factor

1. INTRODUCTION
The road transportation system under the disastersituation is very important for emergency vehicles like fireengines and ambulances and trucks for relief supplies,
and the road network pattern directly affect the efficiency
for the movement of them. The purpose of this paper is toevaluate the travel efficiency of road network patternusing Route Factor by considering relationship between
neighborhood intersections. The proximity graphs like
Delaunay triangulation (DT), Gabriel Graph(GG) and
Relative Neighborhood Graph(RNG) are used to analyze
the road network pattern of major cities in United Statesof America as network construction model.

Road

1.15

RNG
GG

1.1

DT
Rectilinear

1.05

1

Figure 1. Route Factor of each graphs in all cities
0.3
0.25
0.2

GG

0.15

Road Network

0.1

RNG

0.05
0

1

1.05

1.1

1.15

1.2

1.25

1.3

1.35

1.4

1.45

1.5

Figure 2. Distribution of Route Factor(RF) in New York
intermediate of that of RNG and that of GG. This factshows that travel efficiency on the road network in New
York is very close to that on RNG and GG.
4. CONCLUSION
In this research, we evaluate the Road Network Patterns
in US major 10 cities using Proximity Graphs with Road
intersections in terms of travel efficiency. As a result,travel efficiency on Road network is very similar to thaton some proximity graph like RNG and GG.
REFERENCES[1] A. Okabe et al: Spatial Tessellations: Concepts andApplications of Voronoi Diagrams, Wiley, 2000.
[2] D. Watanabe: Evaluating the configuration and thetravel efficiency on proximity graphs as transportation
networks, FORMA, 23(2), 81-87, 2008.
[3] D. Watanabe: A Study on Analyzing the Grid Road
Network Patterns using Relative Neighborhood Graph,
Lecture Notes in Operations Research, 12, 112-119, 2010.

Statistical Analysis of Relation between Seismic
Motion and Viaduct Damage in Considering
Efficacy of Seismic Reinforcement
Shoichi Uemura, Hiroto Suzuki and Hiroyuki Miyakoshi 1
1
R＆D Center of JR East group,
East Japan Railway Company,Japans-uemura@jreast.co.jp
ABSTRACT
East Japan Railway Company has been conducting seismic reinforcement of reinforced
concrete viaduct columns and piers. In order to ensure the safety of a train when an
earthquake occurs, train operation control such as stopping and/or restricted speed are
carried out based on observed values of seismic motion. Train operation control
criteria is based on eathquake resistance of structures. Therefore, if the eathquake
resistance of structures is improved by seismic reinforcement, train operation control
criteria value may be increased. So, for this research, we used statistical analysis toevaluate the relation between seismic motion and structural damage and how structural
reinforcement may have improved eathquake resistance. As a result, reinforcement may
be a major factor in improving the structures to seismic motion and reduced potential
for damage.
Keywords: railway, seismic reinforcement, seismic motion, train operation control
1. INTRODUCTION
East Japan Railway Company (hereinafter called “ JR East ” ) started conducting
seismic reinforcement of reinforced concrete viaduct columns and piers (hereinafter
called “RC columns) in the wake of the 1995 Southern Hyogo Prefecture Earthquake(Great Hanshin-Awaji Earthquake) as a “hard” earthquake countermeasure. Seismic
reinforcement for tens of thousands of RC columns has been completed, withconstruction still in progress. Seismic reinforcement of a viaduct is to strengthen theshear and resilience by enveloping the RC columns in a steel plate, RC, etc. In order toensure the safety of a train when an earthquake occurs, train operation control such as
stopping and/or restricted speed are carried out based on observed values of seismic
motion as a ”soft” earthquake countermeasure. Train operation control criteria is basedon eathquake resistance of structures. Therefore, if the eathquake resistance ofstructures is improved by seismic reinforcement to RC columns, train operation control
criteria value may be increased. So, for this research, we used statistical analysis toevaluate the relation between seismic motion and structural damage and how structural
reinforcement may have improved eathquake resistance.

95December 2019, Yangon, Myanmar

2. OUTLINE AND METHOD OF EARTHQUAKE COUNTERMEASURES
2.1 Seismic reinforcement (“hard” earthquake countermeasures)(1) Seismic reinforcement design
Seismic reinforcement to RC columns is designed so that conditional expression 1 and 2
are satisfied against two directions of seismic motion (Figure 1).

γi・μrd／μdd ≦ 1.0 
γi・Vd／Vud ≦ 1.0        (1) (2)where μ rd ：design response plasticity, μ dd ：design toughness rate,γ i ：structure
factor, Vd：design shearing force(＝Mu/La) , Mu：flexural capacity, La：shear spanand Vud：design shear capacity. μrd is calculated by equation 3
μrd＝1/2・(KhE2/Khy2+1)(3)

where  KhE ： response acceleration in case of elastic behavior and Khy ： design
horizontal seismic coefficient.
Reinforcement (L)Reinforcement (C)L direction

C direction

Figure 1: Seismic reinforcement concept of conditional expression 2(2) Seismic reinforcement method
A seismic reinforcement method, enveloping the RC columns in a steel plate as shownin Figure 2(a), has been adopted at many sites. However, in cases where there are
obstacles attached to RC columns that are difficult to remove, or where equipment thatis difficult to relocate is in close proximity, a one-sided seismic reinforcement method isadopted (Figure 2(b)). If structural requirements are satisfied, three-sided seismic
reinforcement (Uemura, 2013) can be adopted to RC columns integrated with retaining
wall.
Reinforcing steel
Steel barReinforcing steel    D    Figure 2: A seismic reinforcement method

96

E 



New Technologies for Urban Safety of Mega Cities in Asia

2.2 Train operation control (“soft” earthquake countermeasure)
Spectrum intensity (Housner, 1952) (SI) is used in train operation control as an index ofseismic motion highly correlated to damage. The interval between seismometers along arail line is in the order of tens of kilometers. Table 1 shows operation control
classifications and operation control threshold values for conventional lines inearthquakes. Seismic design sections are those where structures were designed andconstructed under the seismic design standard established in 1979 (hereinafter called“1979 standard”), having high eathquake resistance. Rockfall sections are mountainous
sections with a risk of rockfall in earthquakes. Ordinary sections are those that do not
fall under either rockfall sections or seismic design sections, and sections made of
viaducts designed and constructed under standard prior to the 1979 standard areclassified as ordinary sections.
Table 1: Operation control classification and operation control threshold value forconventional lines in earthquake
2SHUDWLRQFRQWUROFODVVLILFDWLRQ

5RFNIDOOVHFWLRQ

2UGLQDU\VHFWLRQ

6HLVPLFGHVLJQVHFWLRQ

6SHHGUHVWULFWLRQ NLQH

WRXQGHU

WRXQGHUWRXQGHU

2SHUDWLRQVXVSHQVLRQ NLQH

RUJUHDWHURUJUHDWHURUJUHDWHU

3. ANALYSIS METHOD
Structures analyzed were rigid frame and girder RC viaducts on JR East conventionaland Shinkansen lines designed and constructed under standards prior to 1979. Study
was carried out in the following procedure.
・Establishing structural unit of viaducts as a basic factor of analysis
・Selection of earthquakes as subject of study
・Classification of structural unit based on seismic conditions, namely eathquake
resistance of RC column, seismic motion and seismic structural damage
・ Tabulation of structural units falling under each seismic condition
・ Analysis of relationship between seismic motion and seismic damage due todifference in the eathquake resistance of RC column
4. SETTING STRUCTURAL UNIT OF VIADUCTThe concept of establishing a structural unit for the viaduct is shown in Figure 3. Rigid
frame viaducts are composed of integral structures made up of columns, beams, andslabs (these structures hereafter called, “blocks”) and adjustment girders, so we
considered blocks and adjustment girders to each be a distinct classifications in thisresearch. For girder RC viaducts, we considered a span to be a distinct classification.

Statistical Analysis of Relation between Seismic Motion and Viaduct Damage in Considering
Efficacy of Seismic Reinforcement97December 2019, Yangon, Myanmar

Figure 3: Concept of viaduct classification in statistical analysis
5. SEISMIC CONDITION OF STRUCTURAL UNIT
5.1 Selection of subject earthquake
In this study, we used the five earthquakes shown in Table 2 beginning with the 2004
Mid Niigata Prefecture Chuetsu Earthquake in which damage to JR East railway
facilities was suffered.
Table 2: Earthquake studied(DUWKTXDNHQDPH

0RPHQWPDJXQLWXGH'DWHRIRFFXUUHQFH

0LG1LLJDWD3UHIHFWXUH&KXHWVX(DUWKTXDNH2FW

&KXHWVX2IIVKRUH(DUWKTXDNH-XO,ZDWH0L\DJL1DLULNX(DUWKTXDNH-XQ*UHDW(DVW-DSDQ(DUWKTXDNH PDLQVKRFN0DU*UHDW(DVW-DSDQ(DUWKTXDNH DIWHUVKRFN$SU

5.2 Eathquake resistance of RC columns
The structural units are classified into three types based on eathquake resistance of RC
column: ”reinforced,” ”reinforcement unnecessary,” and ”requiring reinforcement.”
Structural units confirmed to have RC columns with certain eathquake resistance inseismic assessment were classified as “reinforcement unnecessary.” Structural units inwhich seismic reinforcement was conducted on all RC columns were classified as“reinforced.” Structural unit in which seismic reinforcement was not conducted on anyof the RC columns despite need for reinforcement were classified as “requiringreinforcement.”
5.3 Seismic structural damage
Structural units are classified based on seismic structural damage caused by the fiveearthquakes shown in Table 2. Structural units suffering seismic structural damage
obstructing train operation is classified as “damaged.” Other structural units areclassified as “undamaged.” The total number of “damaged” structural units was 128.

98

New Technologies for Urban Safety of Mega Cities in Asia

5.4 Seismic motion
In order to evaluate the seismic motion of each structural unit, it is effective to use amethod of estimating spatial distributions of seismic motion (Yamazaki, 1998). Figure 4
shows an image of estimating spatial distribution of seismic intensity. First, we
calculated seismic intensity at engineering bedrock by dividing seismic intensity
observed in the individual earthquakes by site amplification. Then, we spatiallyinterpolated seismic intensity at engineering bedrock to find spatial distribution. Spatial
interpolation was performed by the Simple Kriging method (Wackernagel, 2003), which
can take into account the tendency of seismic motion to attenuate according to the
distance from the hypocenter. Finally, we multiplied the area-wide distribution ofseismic intensity at engineering bedrock by site amplification to estimate spatial
distribution of seismic intensity at ground surface. For seismic intensity, we used SI
values that JR East uses in train operation control. For values observed by seismometers,
we used those of the K-NET and KiK-net strong-motion seismograph networks of the
National Research Institute for Earth Science and Disaster Resilience (NIED) and thosefor train operation control used by JR East. For site amplification, we used site
amplification factors (Fujimoto, 2006) of the subsurface ground per 250 m mesh for allof Japan estimated from geomorphologic classification (Wakamatsu, 2013). As forstructural units classified into SI values of less than 10 kine, not even slight damage
occurred, so they were omitted from statistical analysis. As a result, seismic motion was
evaluated for a total of 23847 structural units.
Estimated value

×Site amplification÷Site amplification

Observed value

Ground surface

Engineering bedrock

Figure 4: Image of estimating spatial distribution of seismic intensity
6. ANALYSIS OF RELATIONSHIP BETWEEN SEISMIC MOTION AND
DAMAGE
Figure 5 shows the relation between damage rate and SI value for the eathquake
resistance of each RC column classification. Damage rate is the ratio of the number ofdamaged structural units to the total number of structural units and defined by thefollowing equation.
Damage rate(SI)＝ (Number of damaged structural units less than SI value)/(Number of structural units less than SI value)×100

Statistical Analysis of Relation between Seismic Motion and Viaduct Damage in Considering
Efficacy of Seismic Reinforcement

(4)

99

December 2019, Yangon, Myanmar

Damage rate is lowest in the classification “reinforced” and heightens in the order of“reinforcement unnecessary” and “requiring reinforcement.”
Lower-limit value of damage is 26.7 kine for “requiring reinforcement,” 36.6 kine
for“reinforcement,” and 28.8 kine for “reinforcement unnecessary,” The classification“reinforced” showed the highest lower-limit value of damage, becoming lower in theorder of “reinforcement unnecessary” and “requiring reinforcement.” Moreover, thelower-limit values of damage above were higher than the 21.8 kine lower-limit value ofdamage investigated when setting current operation threshold values of ordinary
sections(Shimamura, 2004) shown in Table 1. From the above results, we found thatreinforcement may be a major factor in improving the structures resilience to seismic
motion and reduced potential for damage.
0.5

lower-limit value of damage whensetting current operation control criteria

Damage rate （%）

0.4

0.3
0.2
0.1
21.8kine

0.0
10

20

30

requiring reinforcement

40

50
60
70
SI value (kine)
rainforced

80

90

100

reinforcement unnecessary

Figure 5: Relation between SI value and damage rate
7. CONCLUSION
To increase train operation control criteria value in viaduct sections where seismic
reinforcement has been completed, we used statistical analysis to evaluate the relation
between seismic motion and structural damage and how structural reinforcement may
have improved eathquake resistance. Analysis was carried out by classifying structural
conditions as “reinforcement unnecessary,” ”reinforced,” and ”requiring reinforcement”
for railway structures experiencing seismic activity from five relatively recent
earthquakes, producing the following results:
・Damage rate is lowest in the classification “reinforced,” and heightens in the orderof “reinforcement unnecessary” and “requiring reinforcement.”
・The classification “reinforced” showed the highest lower-limit value of damage,
becoming lower in the order of “ reinforcement unnecessary ” and “ requiringreinforcement.”
From above results, it was found that reinforcement may be a major factor in improving
the structures resilience to seismic motion and reduced potential for damage. In the
future, we intend to clarify the physical aspects by structural analysis using thenumerical model.

100

New Technologies for Urban Safety of Mega Cities in Asia

REFERENCES
Fujimoto, K., Midorikawa, S., 2006. Relationship between Average Shear-Wave
Velocity and Site Amplification Inferred from Strong Motion Records at Nearby Station
Pairs (in Japanese), Journal of Japan Association for Earthquake Engineering, Vol. 6,
No. 1, 11-22.
George W. Housner, 1952. Spectrum Intensity of Strong Motion Earthquakes,
Proceedings of 1952 Symposium on Earthquake and Last Effects on Structures, 72-88.
Hans Wackernagel, 2003. Multivariate Geostatistics, Morikita Publishing Co., Ltd.
Shimamura, M., Suzuki, H., 2004. Railway Traffic Control Based on Earthquake
Monitoring (in Japanese), Proceedings of the 11th Japan Railway Engineering
Symposium, 2289-2292.
Uemura, S., Tukisima, D., Koda, K., 2013. Seismic reinforcement of viaduct columns
integrated with retaining walls (in Japanese), Summary of the 68th Annual Conferenceof the Japan Society of Civil Engineers, 157-158.
Wakamatsu, K., M.Matsuoka, 2013. Nationwide 7.5-Arc- Second Japan Engineering
Geomorphologic Classification Map and Vs30 Zoning, Journal of Disaster Research,
Vol. 8, No. 5, 904-911.
Yamazaki, F., Onishi, J., Tayama, S., Takano, T., 1998. Development of Fragility
Curves for Expressway Structures in Japan (in Japanese), Proceedings of the 10th
Earthquake Engineering Symposium, 3491-3496.

Statistical Analysis of Relation between Seismic Motion and Viaduct Damage in Considering
Efficacy of Seismic Reinforcement

101

SESSION CURBAN SAFETY & DISASTER MITIGATION: DISASTER
MITIGATION & URBAN PLANNING / EMERGENCY RESPONSE

EVALUATION OF EVACUATION PATH DURING EARTHQUAKE DISASTERCONSIDERING RISKS OF A FALLING OBJECT AND CROWD CONDITION
K. TAKADA1, K., MIYAUCHI2 and M. NISHINO3
Professor, Tokyo Denki University, Hatoyama-tyo, Japan;
Doctoral Student, Tokyo Denki University, Hatoyama-tyo, Japan;
3
Undergraduate Student, Tokyo Denki University, Hatoyama-tyo, Japan
Correspond to Prof. K. TAKADA (takada67@gmail.comg)
1

2

Keywords: earthquake disaster, falling objects, crowd condition, evacuee assignment
1. BACKGROUND
Falling object from walls and roofs may injure
evacuating people during earthquake disaster. Meanwhile,density of evacuating people on the road would be a key
factor to decide safety level of evacuation route. Therefore,
the safety level of evacuation route should be evaluated byconsidering the risk of falling objects and the density ofevacuating people on the road.
In this study, Senju district in Adachi ward, Tokyo is
focused on because there would be congested by theevacuating people after an occurrence of Tokyo
metropolitan earthquake. An index presenting the risk
level of falling objects was developed. Moreover, theevacuation route choice model was estimated by applying
multinomial logit model and probability to be chosen for
the evacuating route was calculated by the estimatedmodel. In consequence, it is shown that decrease indensity level could contribute to increase safety level inthe evacuation.
2. DEVELOPMENT OF INDEX
Figure 1. shows the ideal situation during earthquake
disaster. h[m] and b[m] indicate height and width ofbuilding respectively, L[m] and W[m] indicate length andwidth of road respectively, and V[m/s] indicates moving
speed of evacuating people. Influenced area of falling
objects is shown by shaded rectangles in Figure 1.
The influenced area of falling objects depends on heightof the buildings as described in eq. (1). The initialhorizontal speed is assumed to be 1.11[m/s] as mentioned
in the report [1]. By integrating eq. (1) regarding theheight, the risk of falling object from whole surface of thewall is derived as shown in eq. (2).
𝑥𝑥 = √ℎ⁄2(1)
1
3
R(h) = √ℎ(2)3Moving speed is assumed by eq. (3) by utilizing a
concept of Fruin [2]. Here, D is derived by eq.(4). Q is
number of evacuating people on road link.
V=1.36-0.341D(3)
D=Q/WL(4)
Finally, the risk of falling object of road link is derived
by eq.(5). 𝐾𝐾0 is unit risk per second and T[s] is duration
while evacuation people stay in the road link.
1
𝐾𝐾 = 𝐾𝐾0 T = (∑ √ℎ3𝑏𝑏) 𝑇𝑇
(5)
3

104
避

Figure 1. Ideal situation during earthquake disaster3. EVACUATION ROUTE CHOICE
Questionnaire survey was conducted. Each respondent
was requested to fill in the expected evacuation path on
the map under certain conditions as shown in Table 1.
Evacuation path choice model was estimated bymultinomial logit model. Shortest path, a path throughnational road, and other path which was mentioned byrespondents were included in choice set. The estimation
result is shown in Table. 2.
Table 1. Condition setting
Road congestion○✕✕○

Condition 1
Condition 2
Condition 3
Condition 4

Spreading fire✕○✕○

Falling objects✕✕○○

Table 2. Evacuation path choice model
Explanator variables

congestion

spreading
fire

unit

Estimates

ｔ-value

Path length for female

km

-5.78

-1.17

Total length of the road with more than 5.0m width

km

13.65

2.31

Detour rate for the shortest path for female

%

-0.19

-0.32

Path length for female

km

-4.6

-0.72

Total length of the road with less than 3.0m width

km

-8.62

-3.71

Detour rate for the shortest path for female

%

1.05

2.15

-0.81

-1.04

13.12

2.43

1.6

2.34

Risk of falling object
falling

Total length of the road with more than 5.0m widthkm

objectDetour rate for the shortest path for elder person%(over 70)
Log-likelihood

0.43

Samples148

Hit ratio%

61.5

REFERENCES[1]The Japan Building Disaster Prevention Association[2]Fruin, John J. Pedestrian Planning and Design. New
York: Metropolitan Association of Urban Designers andEnvironmental Planners, Inc., 1971.

A case study on land-use and transport
relationship in Yangon
Hnin Su Mon WIN1 and Theingi SHWE2
Ph.D. Candidate, Department of Architecture,
Yangon Technological University,
Myanmarhninsu.hsmw.ytu@gmail.com
2
Professor and Head, Department of Architecture,
Yangon Technological University,
Myanmar
1

ABSTRACTAs Yangon is one of the busiest and major commercial cities with the most populated division
throughout the country, it suffers lots of pressures for the city’s development, especially forcity’s transportation and land utilization issues. This article describes a study on the current
planning of land utilization and transport relationship in Yangon. The paper begins with an
examination of the continuing tensions between land-use and transport planning and contains
identifying issues of planning frameworks by the local government. Then, the linkage between
transportation and land use evaluation process applied urban volume rate and road area ratio.
The result suggests that the existing land-use and transport planning system needs to integrate
to achieve better city planning design and minimize the current traffic problems.
Keywords: Land-use Planning, Transport Planning, Urban Volume, & Split Model
1. INTRODUCTION
Because of the accelerated process of urbanization and demand for urban transportation systems
has been dramatically increased and changes in land utilization is a major phenomenon
especially in the major cities. Currently, Yangon faces a high tension of traffic pressure for thedevelopment of the city and lack of integration between land-use and transportation. This paper
is aiming to research this area to realize the current condition of the urban transport systems,
effective coordination and interaction between land-use and transportation system and mutual
relations system are significant.
Like other major cities from developing countries, it generates four major issues for thedevelopment of Yangon city: increased population, housing demand, employment locations andmovement problems which are inter-related each other. Among these four issues, a linkage
between transportation system and land-use regulation system of Yangon city has been studied
in this paper to examine the current tensions as well as finding out the existing condition
between supply _ the capacity of road networks, and demand while a study on the land
utilization frameworks and transport planning. However, there are several methodologies andvaluation tools have been advocated to assess the case studies, research methodology toevaluate the coordination between transportation and land-use will be calculated with urban
volume rate and road area ratio calculation methodologies to identify the supply and demandconditions of transport network situation.

105

December 2019, Yangon, Myanmar

1.1. Physical Growth Pattern and Population of Yangon
Since 2005, Yangon, the former capital of Myanmar, had been officially marked as the second
capital city of Myanmar after the development of the new capital city: Nay Pyi Taw which isan administrative capital city is located in lower Myanmar. According to the historical records,
the city had been founded by King Alaungpaya after conquered Dagon, a small fishing village,in 1755 and retitled it “Yangon – means the end of strife”. After being a colonized country by
the British in 1885, they constructed Yangon (formerly known as Rangoon) as a new city design
with a grid plan on delta land by a Bangel Engineer Lit. Fraser. The city was only 86.20sq.km
in 1940 and it was originally planned for only 50,000 populations. And then it was expanded
towards the north and became 208.51sq.km in 1974. Later, it grew towards east and west
directions with 346.13sq.km in 1985 (Moe, 1992 & YCDC, 2012) as shown in (Figure 1). The
physical development of the city has been strongly affected by its original location andgeography which is located between the Hlaing River, Pazundaung Creek, and Yangon River.
The city population has increased also increased from 50,000 populations in 1941 to nearly 5.2
million people in 2018.

Figure 1: Physical Growth Pattern of Yangon City (DHSHD, 2000)
2. NATURE OF LAND-USE AND TRANSPORT RELATIONSHIP AND APPLIEDMETHODOLOGY
As many scholars claim that land use and transportation has a strong link where people settlein certain places where facilities are closely located such as houses and workplaces, amenities
as well as health care and educational facilities. However, the choice of settling places is notsatisfactory when the levels of transportation facilities are poor and unreliable, squatters andinformal settlements occur. Besides, the level of income, mode of choice and route choice, trip
distribution and travel duration between two destinations points influence the mechanism of theentire urban transportation system. Nonetheless, travel behavior plays a vital role as it may
change the result of the entire framework between land use and transportation by the nature ofits society.
According to Mackett (1985), he defines a framework as shown in (Figure 2) for land use andtransportation cycle based on form, function, land use and transport. He also claims that
activities may change rapidly when policy change while the physical infrastructure has a slow
response during the mismatch responses of planning stages. Moreover, (Figure 3) represents
the relationship between land-use and transport system.

106

New Technologies for Urban Safety of Mega Cities in Asia

Land Use
Transport

Forms
Buildings & PhysicalInfrastructure
ChannelFunctions
Activities (Residing, shopping,working, travel, etc.)
Flows

Figure 2: Framework for analysis of cities (Mackett, 1985)

Activity

Transport
SystemLand
Use

Accessibility

Figure 3: Land-use Transport Cycle
Similarly, based on the findings of Ewing et al. (1994) sprawl dwellers compensate for poor
accessibility by linking more trips in multipurpose tours. Also, gender difference and dual
worker households may affect travel activity patterns. Trip-chains are, therefore, an example oftravel behavior that could be investigated to better understand the land use and transportation
linkage.
However, it can be argued that people who live near the transits oriented or neo-traditional
development generate shorter trips and frequent usage than the outer urban rings or outskirts
areas while neo-traditional design contains a town center, connected grid street patterns,
proximity between land use, on-street parking for narrow residential streets and small
residential lots with public parks and open spaces. Many studies identify that there is a strong
relationship between land use characteristics and travel behavior. Kitamura et al (1997) argue
that person trip generation is largely determined by demographic and socioeconomic
characteristic but not associated with the land-use characteristics. In contract, Frank and Pivo
(1994) and Cervero and Radisch (1996) indicate that density and mixed land use area related tomode choice for both work and shopping trips while neighborhood characteristics were found
to exert their strongest effect on local non-work trips including walk trips as substitutes for auto
trips. According to the elements of a city plan by Frederick Law Olmsted, Jr. mentions the threemain divisions of city planning and which are circulation of both transportation andcommunication, the lands devoted to all other public purposes, and the land to private
ownership.
To calculate urban volume (equation 1) and road area ratio (equation 2) has been utilized
as followings:
𝐶𝐶𝐶𝐶
𝑅𝑅𝑅𝑅1 = 𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 , where,(1)
𝐶𝐶𝐶𝐶𝑏𝑏𝑏𝑏𝑙𝑙𝑙𝑙𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏

𝑅𝑅𝑅𝑅1 =urban volume rate, 𝐶𝐶𝐶𝐶𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 =urban building area (𝑚𝑚𝑚𝑚2 ), 𝐶𝐶𝐶𝐶𝑏𝑏𝑏𝑏𝑙𝑙𝑙𝑙𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 = urban land area (𝑚𝑚𝑚𝑚2 )𝐶𝐶𝐶𝐶

𝑅𝑅𝑅𝑅21 = 𝐶𝐶𝐶𝐶 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 , where,
𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏(2)

𝑅𝑅𝑅𝑅2 =road area ratio, 𝐶𝐶𝐶𝐶𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 =road-used land (𝑚𝑚𝑚𝑚2 ), 𝐶𝐶𝐶𝐶𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏𝑏 =urban-used land area (𝑚𝑚𝑚𝑚2 )A Case Study on Land Use and Transport Relationship in Yangon

107

December 2019, Yangon, Myanmar

Model split indicator has also been applied to investigate the interaction between mode of
choices, and the study of existing land-use mapping from YCDC to understand the formationof trip attraction points to move around the city.
3. INSTITUTIONAL DEVELOPMENT
PLANNING IN YANGONOFLAND-USEAND

TRANSPORT

Land-use zoning map of Yangon contains major six categories: residential, commercial,industrial, agriculture, government and institutional, special zonings such as religious, green
and blue, heritage, etc. Land-use planning of Yangon can trace back till the development ofRangoon Development Trust Act (RDT Act-1920) which can be divided into four periods:
from 1920 up to Second World War, post-war Independence period (1948-1962), the period
from 1962-1988, and 1988-1992 (Moe, 1992).
After 1988, largest land use development projects in the history were planned and implemented
in 1990, compromising four new suburban townships each accommodation over 150,000
populations by the State Law and Order Restoration Council and the scheme was responsibleby the Department of Human Settlement and Housing Development (DHSHD) which was
similar to that of the late 1950s squatter resettlement programs, except the scale and themagnitude. In addition, Thein Gyi Shopping Center Project was implemented by YCDC toprovide over 100,000 sq.ft for both shopping space and office space similarly and completed in
1994. Although wholesale business center and warehousing used to be located in the west endof CBD, starting from 1990, these activities have been moved toward the north and north-east
area. Private sector housing can be found in inner urban areas such as Sanchaung, Ahlone,
Tamwe and Pazundaung Townships with new 3-4storey walk-up apartments although it isoriginally intended for low-density single family houses. Another transport-related project is
Yangon International Airport and runway extension project as well as bridges across Bago and
Hlaing Rivers which have a significant impact on the city.
Transport planning of Yangon city can be divided into three major functions: Transport
Infrastructure, Operation, and Traffic Management under the management of Urban andRegional Planning Division of DHSHD and later Roads and Bridges Department of YCDC.
The Yangon City Transport Management Committee (Central) has the highest authority
especially for the public transport provision operations in the city which is now chaired by
Mayor of Yangon City and responsible for the overall public transport system in the city on
daily basis.
4. STUDY ON THE CURRENT
TRANSPORTATION IN YANGONSITUATIONOF

LAND-USE

AND

Current Yangon City is composed of 4 districts with 33 townships under the management of
Yangon City Development Committee (YCDC) whereas the whole Yangon region contains a
total 45 townships. The Central Business District (CBD) area, the old Fraser Plan, with 6
townships, has 33.2 sq.miles. The current land utilization of 15 townships including CBD, isshown in (Figure 4). Residential and employment densities also influence the transport andland-use interaction as well as trip length, mode of choice and trip frequency.
Although there is different mode of transport systems in the city, the majority of the city’stransport share is owned by public bus transport system and it is managed by Yangon Region
Transport Authority (YRTA). The model share of transportation in Yangon City is shown in

108

New Technologies for Urban Safety of Mega Cities in Asia

(Table 1) while water-bus transport service is private investment, unlike, sub-urban rail andcircular rail transportation which is managed by a government sector, Myanma Railway.

Descriptions
1
A
Low Rise Residential
1
B
Mid Rise Residential
1
C
High Rise Residential
1D
Mix Use Residential
2
Commercial
4
A
Port & Related
4
B
Government &Institute
4
C
Military
5
A
Green & Blue
5
D
Religious

Figure 4: Current Land Use Map of 15 Townships in Yangon (Kyi, 2017)
Table 1: Mode of Transportation & Model Share (YCDC & DRTA, 2000) (JICA, 2014)
Mode ofTransport
Buses (Public
Transport)
Sub-urban
Rails &
Circular Rails
Water Bus &FairiesModel Share(%) [2000]
87.7%

Model Share(%) [2014]
63%

2.1%

1.4%

1.3%

3.2%

4.

Motorcycles

N/A

9.3%

5.
6.

BicyclesTaxi &
Private cars
Others

N/A
8.9%

N/A
21.4%

N/A

1.7%

No.
1.
2.
3.

7.

Current Mode of Transport
Remarks
Over 300 routes with over 5000 buses– over 1.2millions passengers/day
38 stations 29.5 miles for circulartrain – nearly 92000 commuters/day
7 stops (from CBD to Insein
Township – 7 stops + weekend
special trips to Kyauktan
Limited use – 31 out of 33 townships
legally prohibited
Limited use inside CBD
Available but more expensive thanany others
Limited use of trishaws inside CBD

As a result of the dominant use of buses for transport communication, most of the traffic
solutions occur especially on the road networks. While many people moving towards CBD andinner urban area and old suburb area to access a variety of facilities such as better job
opportunities, shopping centers, movie theatres, and other recreational facilities from the new
suburb area as well as peripheral areas where accessible amenities are less favorable.

Figure 5: Trip Generation and Trip Attraction by Urban Area (YUTRA, 2014)
A Case Study on Land Use and Transport Relationship in Yangon

109

December 2019, Yangon, Myanmar

4.1 A Case Study of CBD Area
Taking CBD area (6 townships) as an example to validate the model, and the result is as shownin (Table 2) although the Seikken Township data is not available as the majority of the land use
categories is for port, factory, and storage areas. Table 3 describes the result of the townshipdata for urban volume rate and road area ratio by utilizing ArcGIS Earth, visual survey analysis
methods has been applied and is shown in (Table 2).
Table 2: CBD Area Urban Volume Rate and Road Area Ratio

TownshipLanmadaw
Latha
Pabedan
Kyauktata
Botahtaung
SeikkenTotal Urban
Land Area(𝒎𝒎𝒎𝒎𝟐𝟐𝟐𝟐 )(MIMU,2019)
1300000
6030006170007010001170000
2600000

Total Street
Area (𝒎𝒎𝒎𝒎𝟐𝟐𝟐𝟐 )(ArcGIS Earth)133253.6
118758.976907.989785.2
136717
N/A

Building
Coverage
Area (𝒎𝒎𝒎𝒎𝟐𝟐𝟐𝟐 )

1166746.4
484241.1
540092.1
611214.8
1033283
N/A

Urban
VolumeRate (𝐑𝐑𝐑𝐑 𝟏𝟏𝟏𝟏 )

0.90
0.80
0.88
0.87
0.88
N/A

Road
Area
Ratio
(𝐑𝐑𝐑𝐑 𝟐𝟐𝟐𝟐 )
0.10
0.20
0.12
0.13
0.12
N/A

4.2 Problems resulting from the Fragmented Land Use and Transport Planning
When a city’s population grows, its physical boundaries need expansions and there is nodifference in Yangon. The overall distance from the CBD to pre-1980s peripheral settlements
were at the manageable level which is around a 7-mile radius. Later it has been expanded
especially to the north and north-east area was less the physical barriers than others and after
1988, development of new peripheral settlements along the north, northeast and north-west
area: Shwe Pyi Thar, Hlaing Thaya and Dagon Myothit including both north and south and also
Shwe Paukkan. As these developments are originally targeted for industrial land use with about1000 acres each although these developments are not fully establishment-level yet resulting in
the excessive journey to work time for those who have been living in these areas whatever theirreasons. Also, the employment opportunities in these townships are especially for the bluecollar workers: construction labours, textile workers, and others who need manual labour jobs
causing the job market still much depend on CBD and inner urban areas. Unlike, people wholive in suburbs area have their private transport in the developed world but Yangon incompletely contrast and majority of people entirely to rely on public transport system while thetravel cost is also higher and lack of basic social facilities and demand on the transport systems
and (Table 3) shows the data of travel distance and travel duration between CBD and its new
suburbs areas. Nearly 25 percent of a day has been used for travelling is not a healthy solution
for the city as well as for the residents.
Table 3: Travel duration and cost between CBD & new peripheral Areas
Distance Maximum Travel Durationfrom CBD(Peak & Off-peak)1
Shwephithar
16 miles
3hr & 2hr2
Hlaingtharyar
14 miles
3.5hr & 2.5hr
3Dagon Myothit (North)
14 miles
3.2hr & 1.7 hr
4Dagon Myothit (South)
12 miles
2 hr & 1.5hr
Note : Peak hour – between 7am - 9am and 5:15pm – 6:30pm
No.

110

TownshipTravel Cost
200-300 kyats
200-300 kyats
200-300 kyats
200-300 kyats

New Technologies for Urban Safety of Mega Cities in Asia

5. CONCLUSIONSIn summary, land-use and transport planning practices need to integrate for the sustainable
development of the city planning, for example, the later development of Yangon city is facing
lots of pressure on the transportation as a result of neglecting on the land-use categories anddevelopment plans by both government and private sectors. Utilization land-use transportmodels are essential to spatial planning of urban area for all type of land uses.
REFERENCES
Frederick Law Olmsted, Jr. 1916. Introduction, Basic Principles of City Planning John Nolen(ed.), City Planning: A Series of Papers Presenting the Essential Elements of a City Plan, NY:
D. Appleton and Company, 1-18.
ALMEC Corporation, Oriental Consultants Co., Ltd and Nippon Koei Co., Ltd (2014) Project
for Comprehensive Urban Transport Planning of the Greater Yangon (YUTRA) Final Rreport,
Vol 1.
Srinivasan, S., 2000. Linking Land Use and Transportation: Measuring the Impact of
Heighborhood-scale Spatial Patterns on Travel Behaviour. PhD Dissertation. Department of
Urban Studies and Planning, Massachusetts Institute of Technology: USA.
Than Moe. 1992. Integrated Land Use Transport Planning in Yangon. MSc. Dissertation.
University of Wales College of Cardiff. Department of City & Regional Planning: Wales.
YCDC, 2012. Facts about Yangon.
Yujie Sun, Wenxin Qiao, Yongsheng Zhang and Yang Yang, 2015. GIS-based urban land use
and traffic coordination evaluation system, Applied Mechanics and Materials, Vol 738-739
Trans Tech Publications, Switzerland, 204-208.
Zaw Zaw Aye, 2001. The Transportation Management System in Yangon: A Focus on Easing
the Traffic Congestion. Master Thesis, Asian Institute of Technology, School of Environment,
Resource & Development: Thailand.

A Case Study on Land Use and Transport Relationship in Yangon

111

BASIC ANALYSIS OF AIRCRAFT DIVERT DESTINATION SELECTION
DURING LARGE-SCALE NATURAL DISASTERS USING AIR TRAFFIC CONTROL DATA~CONSIDERRING THE VULNERABILITY OF THE AIRPORT~
R. FUJII1, M. FUJIU2, Y. MORISAKI3, J. TAKAYAMA4, and Y. SHIOZAKI5Undergraduate Student, Dept. of Environmental Design, Kanazawa University, Kanazaawa, Japan,
Associate Professor, Geosciences and Civil Engineering, Kanazawa University, Kanazaawa, Japan,
3
Doctoral Course Student, Dept. of Environmental Design, Kanazawa University, Kanazaawa, Japan,
4
Professor, Geosciences and Civil Engineering, Kanazawa University, Kanazaawa, Japan,
5Specially Assistant Professor, Geosciences and Civil Engineering, Kanazawa University, Kanazaawa, Japan,
Correspond to Makoto FUJIU (fujiu@se.kanazawa-u.ac.jp)
1

2

Keywords: Airport, Aircraft, Divert, Disaster
1.

INTRODUCTION
In recent years, there have been many natural disasters
in Japan, causing tremendous damage. Among them,damage to the airport function has also occurred. Due toTyphoon No. 21 on September 4, 2018, KansaiInternational Airport was flooded, and it took 10 days torecover the domestic flight due to the damage of the power
outage. Also, on September 6, 2018 at 3:07:59, the
Hokkaido Iburi Eastern Earthquake occurred, and the
maximum seismic intensity recorded seismic intensity 7.
New Chitose Airport became inoperable due to thedamage caused by large-scale blackouts and earthquake
damage, and it took time to recover. If an airport isdamaged in the aviation field where high safety standards
are required, it will have a major impact not only on the
airport facilities but also on the operation of the aircraft.
Based on the above, more effective measures such as
reselection of divert destinations and improvement of CIQ
facilities are required. As a pre-stage for the constructionof these countermeasures, it is considered necessary to
grasp the flight status of the aircraft at the time of thedisaster. Therefore, the purpose of this study was tounderstand the flight situation of the aircraft using theaircraft track data and clarify the danger at the time ofdisaster occurrence. As an example, we analyzed based on
the assumption that Tokyo International Airport was
damaged.
2.

ANALYSIS
In this analysis, we analyzed Tokyo International
Airport, which has the largest number of aircraft
departures and arrivals among airports in Japan, in orderto understand the aircraft that should be dealt with in theevent of a disaster.
CARATS Open Data was used as usage data. CARATS
is an abbreviation for Collaborative Actions for
Renovation of Air Traffic Systems. This is a wake ofaircraft nationwide created from radar data, etc., andincludes data for approximately 640,000 flights for 24
weeks from 2012 to 2015. Reserch and development is
expected to realize the long-term vision of CARATS,
which is used for applications such as discovery ofproblems and facts useful for improving the operation of
air traffic management, analysis of factors, and evaluationof proposed operation improvement methods.

112

Figure 1. Aircraft Flight Position
It was assumed that New Chitose Airport was hit by alarge-scale blackout due to the Hokkaido Iburi Eastern
Earthquake last year, but Tokyo International Airport wasin the same state. The analysis was carried out based on
the assumption that the control work would be impossible
due to a power outage at 22:30, targeting the 22:00 range
with many landing aircraft at Tokyo International Airport.
We used all flight data from 18:00 to 24:00 on March 7,2013 from CARATS Open Data. The data of the aircraft
heading to Tokyo International Airport at 22:30 was
extracted from a huge amount of aviation data.
3.

CONCLUSIONS
Figure 1 shows the flight position of the aircraft near
Tokyo International Airport at 22:30. The control area of
each airport is within a radius of 9km. In this analysis, at
22:30, 2 aircraft were in control of Tokyo International
Airport and 18 aircraft were flying to Tokyo International
Airport. If the control tower of Tokyo International
Airport becomes temporarily inoperable, 2 aircraft inflight in the control zone are waiting for instructions suchas landing, so immediate action is required. Since theother 18 aircraft cannot land at Tokyo International
Airport, it is necessary to allocate a divert destination.
Assuming that the control work becomes impossible due
to a power outage, etc., the assumption is insufficient,suggesting the need to take immediate measures. As
future tasks, we will expand the target time and analyze atother airports to understand the flight status of the aircraftin more detail.
REFERENCES[1] Ministry of Land, Infrastructure, Transport andTourism, http://www.mlit.go.jp/common/001264807.pdf

DEVELOPMENT OF AGENT-BASED FLOOD EVACUATION SIMULATIONFOR SUPPORTING LOCAL GOVERNMENT EVACUATION PLANNING
J.H. KIM1, T.S. EDA2, I.P. HARADA3, K.H. AYUKAWA3, T.H. MUKAI4, T.A. KATO5
Project researcher, KATO Takaaki Lab(Social Safety System),Institute of Industrial Science, the University of Tokyo, Tokyo, Japan,
Research Fellow, KATO Takaaki Lab(Social Safety System),Institute of Industrial Science, the University of Tokyo, Tokyo, Japan,
3
Senior Reseacher, Intrabasin Communications Division,Foundation of River & Basin Integrated Communications, Japan
4
Director, Intrabasin Communications Division,Foundation of River & Basin Integrated Communications, Japan
5
Professor, International Center for Urban Safety Engineering(ICUS),Institute of Industrial Science, the University of Tokyo, Tokyo, Japan,
Correspond to J.H. KIM (kimjah@iis.u-tokyo.ac.jp)
1

2

Keywords: Flood evacuation analysis, Evacuation planning, Planning support system, Individual evacuation timeline, Agent-based simulation
1. INSTRCUTIONS
The recent precipitation pattern shows increase in occurrence ofconcentration rainfall and the intensity of rain is getting stronger.
Furthermore, due to the influence of recent climate change, there are
greater worries toward more flood damages and large-scale damages.
To prevent such damages, considering the experience of flood
damage mentioned above and prospect of climate change, the central
and local governments are reviewing various measures to prevent
large-scale flood damage. However, there are no quantitativeevaluation or verification method or tools for quantitative analysis
needed to establish evacuation plans in local government level, there
are great difficulties for each local government to establish concreteand comprehensive evacuation plans.
Thus, the purpose of this study is to develop a flood damage
evacuation simulator that can support the establishing of evacuationplans by local governments through evaluation of the characteristics ofthe area such as the status of the shelter, population density, road network
structure, etc. and quantitative assessment of evacuation timing.

Figure 2. Evacuation Plan Establishment Using Flood Evacuation
Simulation

2. BUILD SIMULATION MODEL
The simulations built in this study were conducted on the entire
municipalities and surrounding areas in order to consider wide-area
evacuation from the results of previous studies, which were mostly
conducted on a part of the area or analyzing evacuation capacity within
the area. In this way, it was possible to express large-scale evacuationaccording to the occurrence of large-scale flooding and to verify theevacuation situation according to evacuation timing by enabling
quantitative analysis according to the timing of evacuation.
Concretely we choose to find a shelter by car and walk on foot.We
make it considerably in the capacity of shelter by classifying district
internally and externally. Also, we make it review the status of refugein accordance with traffic jam and congestion with numbers ofrefugees by considering the capacity of refuge flow with the road
network's structural characteristics.

4. CONCLUSIONSThis study developed a simulator that makes a quantitative
measurement of evacuation conditions possible, considering spacecharacteristics of regions such as shelters, road networks, population
distributions on the rate of timing in beginning evacuation, in order tosupport establishing proper evacuation plans while reviewing those of
massive flood damage.
From the scenario analysis of JOSO City derived from this simulator,
we were able to identify the maximum capacity of an ideal(safe)
evacuation on foot and via cars taking into account the structuralcharacteristics of the city. This is considered to be an important indicatorin establishing an evacuation plan. Based on this, various evacuation
measures, such as a reduction in evacuation demand or the dispersion ofevacuees across time and space, were reviewed. This is expected to help
local governments establish a practical evacuation plan.

Figure 1. Building a Simulation Model: Evacuation Behavior Flow
3. COMPOSITION OF THE SIMULATIONThis study bases on three-step analysis to establish evacuation plans.
The first step is to carry out basic analysis with GIS in order to understandregions. The second step is to implement analysis(simulation zero) that
introduce the worst case using simulation, and to understandcharacteristics of regional evacuation problems.
On third step, figure out(simulation A) the city structural feature
for the capacity of evacuation and the flow, and act, and execute theverification(simulation B)on each scenario for establishing ideal
evacuation plans such as evacuation tools, demand control on its
target population and the timing, and so on, based on it.

REFERENCES[1] Toshitaka Katada, Noriyuki Kuwasawa, Satoru Shida, Masaru Kojima,
Scenario Analysis on Evacuation Strategies for Residents in Big Cities
During Large-Scale Flood,Journal of Japan Society of Civil Engineers, Ser.
B1 (Hydraulic Engineering), Vol. 69Issue1,April, 2013.
[2]Jyun-ichiTomatsu, Michiyuki Hirokane,Tanaka yuudai,Evaluationof
The Validity for Flood Disaster Measures by An Evacuation Simulation,
Japan Society for Fuzzy Theory and Intelligent Informatics 28th Fuzzy
System Symposium,September, 2012.
[3] Cabinet Office, Large-scale flood measures guidelines in themetropolitan area, 2012.

113

HOW MUCH DOES SOCIAL NETWORKING SERVICE AFFECT THE EVACUATIONEFFICIENCY? - A STUDY USING AGENT-BASED SIMULATION
T. MINAMI1, T. KATO2
1

Graduate Student, Department of Urban Engineering, School of Engineering, the University of Tokyo, Japan,
2
Professor, Institute of Industrial Science, the University of Tokyo, Japan,
Correspond to T. MINAMI (minami-t@iis.u-tokyo.ac.jp)

Keywords: evacuation, decision making, agent-based simulation, social networking service
1. INTRODUCTION
Recently SNS (Social Networking Service) is widelyused when people communicate with each other. It is also
applicable to post-disaster situations. At 2011 Great East
Japan Earthquake, 16.7 % of people living near Tokyo
used Twitter to get information about evacuation centers[1]. While SNS can be helpful in finding uncrowded
centers, there are also some risks that a specificinformation is explosively spread in short time, which
contrarily brings disorder.
In this research, by running a simulation model ofpeople’s evacuation behavior which includes informationexchanging activity, we investigate the effect of SNS on
the overall efficiency of the evacuation.
2. METHODOLOGY
We create an agent-based evacuation simulation model
where each person agent will evacuate to an evacuation
center, introducing in it an SNS-like informationexchanging system. By running it for some SNS use
scenarios, we examine the change of the efficiency insome aspects.
3. SIMULATION DESIGNIn 500x500 space, we place 5,000 people and 25
evacuation centers randomly (Fig.1). When a disasteroccurs, each person starts to find an evacuation center tobe in. Only 20% of the people know the nearest center atthe beginning and the remainder will follow the leader.

user, he/she will also decide whether to send thecongestion report to the followers or not.
SNS users can also read the timeline where posts frompeople whom they follow are listed. Based on thecongestion information there, they can change thedestinations. They can also repost (forward the post he/she
received to his/her followers) some information, whichenables a single congestion report to reach many people.
4. RESULTS
In order to evaluate the effect of SNS, we change the
SNS utilization rate 𝑅𝑅𝑅𝑅𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 from 0% to 100% by each 10%.
We run each scenario in 10 different patterns of evacuation
center distribution (D.P. = Distribution Pattern).
The average evacuation time (AET) tends to decline
when 𝑅𝑅𝑅𝑅𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 goes from 0% to 20%. However, when it goesto higher than 20%, AET stays flat or sometimes increases.
The maximum evacuation time (MET) has the same trend,
and the gap between the most and the least timeconsuming D.P. is reduced as 𝑅𝑅𝑅𝑅𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 increases (Fig.2).
For the population balance among centers, the final
variance 𝜎𝜎𝜎𝜎𝑓𝑓𝑓𝑓 clearly becomes lower in every D.P. as 𝑅𝑅𝑅𝑅𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢
goes up. In particular, the D.P. 6, where the variance is thehighest at 𝑅𝑅𝑅𝑅𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 = 0%, has the largest decrease (Fig.3).
These results indicate that the initial disparity amongareas which derives from the geographical characteristics
can be flatten by the information spread through SNS.

Figure 2. 𝑅𝑅𝑅𝑅𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 - MET relation Figure 3. 𝑅𝑅𝑅𝑅𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 -𝜎𝜎𝜎𝜎𝑓𝑓𝑓𝑓 relation

Figure 1. An example of the simulation execution
𝑅𝑅𝑅𝑅𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢 is a parameter which stands for the SNS
utilization rate. A person who uses SNS can communicate
the congestion information to his/her followers.
When an evacuee arrives at a center, he/she decides
whether to enter or not, considering the crowdedness. If
the congestion rate exceeds his/her tolerance, he/she does
not enter and sets the new destination. If he/she is an SNS

114

5. CONCLUSIONSIn this research, we gained the following conclusions:1) SNS can help to redress the population balance amongevacuation centers.
2) SNS can also reduce the evacuation time when its
utilization rate is low. However, it sometimes brings theadverse effect when the utilization rate is high. We needto take it into consideration to make an evacuation plan.
REFERENCES[1] T. Kawai, H. Fujishiro, Use of Twitter in the disaster
information after the Great East Japan Earthquake.
Corporate communication studies, 17 (2013) 118–128.

COLLAPSE ANALYSIS OF R.C BUILDINGS SUBJECTED TO BLAST LOAD USING AEM
M. Pavan Kumar1, G.K. Chaitanya2 and K. Rambabu3
Ph.D Scholar, Department of Civil Engineering, Andhra University, India,
2
Project Assistant Professor, Institute of Industrial Science, University of Tokyo, Japan
3
Professor, Department of Civil Engineering, Andhra University, India,
Correspond to Prof. M. Pavan Kumar (pavanidea@gmail.com)
Keywords: Collapse analysis, AEM, blast load, debris analysis
10.03 Sec

0.4635 Sec

1.236 Sec
3 Sec
Fig.1 Collapse analysis of a building
A typical RC building as a case study has been
considered, which has 6 storeys and 4 bays in eachdirection, a bay width of 4m, storey height of 3m, andfoundation depth of 3m. The numerical analysis is basedon AEM. The input blast load was fixed surface blast
load of charge weight 2500kg TNT at a range of 10m.

Storey Level [m]60∫a2 dt [1000]

1. INTRODUCTION
There is a considerable demand to study the blast
phenomenon to understand the mechanism and provide
essential guidelines on keeping critical buildings blast
resistant or blast-proof. One of the principal activities inthis field is to study and understand the behavior of abuilding when subjected to a blast. This study provides amethodology to study the collapse behavior of a building.
2. METHODOLOGY
We propose a comprehensive collapse assessment
method by simplifying numerical blast mechanism into
(1) collapse of the structural component; (2) debris
analysis and (3) residual capacity of remaining building.
2.1 Collapse evaluation of the structural partIn this study, the energy absorbed by the building due toblast load is calculated using ∫ a2 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 . This form ofintensity represents the overall duration, amplitude andfrequency change of building due to blast.
2.2 Debris analysis of the building
The debris is calculated using the number ofdisintegrated elements from the building. In this analysis,
the percentage of the collapse of the structural part of thebuilding at every storey level is obtained. Further, thevelocities of disintegrated elements are studied
2.3 Residual capacity of the undamaged partTo understand the residual capacity of the undamaged
frame, inter storey drifts are calculated at each storey.
3. NUMERICAL SIMULATION30
00.00 1.00 2.00
Time [Sec]Fig. 2 Collapse

20
10
0
0

15 30
Drift [mm]Fig. 3 Residual

4. RESULTS AND DISCUSSIONSThe overall damage could be seen in Fig. 1. The
Collapse analysis is shown in Fig. 2 where, themaximum energy is absorbed before 0.1 and is further
saturated. A jump in energy release at 1.15 seconds and1.70 seconds which attributes to heavy damage andphysical collapse of components. The debris analysis asinTable 1, shows that the structural debris is from slabs.
This is due to exposure of slab directly to blast. Residual
Capacity is shown in Fig 4 and the maximum inter storey
drift ratio in this case is 1.15% which is lesser than 4%,
recommended by FEMA 356 for collapse prevention.
Table 1: Debris of structural part of SFR
Beam

Debris (%)
Columns

Slabs

Plinth Lvl.
Stilt floor

20.01
19.72

20
20

N/A
25

Gr.floor

19.72

20

25

1st floor

19.72

20

25

2nd floor

19.72

20

25

3rd floor

19.72

20

25

4thfloor

19.72

20

25

Storey Level

5. CONCLUSIONSIn this research a comprehensive method has been
proposed to analsyse the blast which addresses thecollapse part, severity of flying debris, blockage, andalso the strength and integraty of undamaged building.
This assessment has various applications especially inproviding guidelines for blast protection of RC buildings.
REFERENCES[1] B.M. Luccioni, R.D. Ambrosini and R.F. Danesi, “Analysis of
Building Collapse under Blast Loads”, Engineering Structures, Vol. 26,
Issue 1, January 2004, pp. 63 – 71, ISSN: 0141-0296.
[2] T. Ngo, P. Mendis, A. Gupta and J. Ramsay, “ Blast Loading andBlast Effects on structure”, The University of Melbourne, Australia,
2007.

115

EVALUATION OF URBAN SUNSHINE ENVIRONMENTBY SHADOW SIMULATION
Hiroko WATANABE1, Yudai HONMA2, Kentaro HONMA3 and Kotaro IMAI4
1

Student, Graduate School of Engineering, the University of Tokyo, Tokyo, Japan,
2
Associate Professor, ICUS, IIS, the University of Tokyo, Tokyo, Japan,
3
Associate Professor, IIS, the University of Tokyo, Tokyo, Japan,
4
Professor, IIS, the University of Tokyo, Tokyo, Japan

Keywords: sunshine environment, shadow simulation, skyscraper
1. INSTRCTION
In this study, to clarify the sunshine environment
formed by multiple buildings, we create a shadow
simulation to analyze the city’s sunshine environment.
We focus on the overlap of the shadows of skyscrapers andother buildings and evaluated quantitatively.
In Japan, the sunshine is regarded as important as aliving environment. In the high economic growth periodof the 1960s, the construction of condominiums spreadthroughout Japan. Many middle- high-rise buildings werebuilt and conflict occurred between the inhabitants andconstruction companies concerning the right to sunshine.
Hence, as a measure to provide a right to sunlight the
Building Standard Law was revised. As a result, disputes
concerning the rights to sunlight have subsided and now
are on a downward trend. However, even now, middlehigh-rise buildings and skyscrapers are being built and the
problem with sunlight has not disappeared. Therefore, it
is meaningful to know how the sunlight environment incities changes due to the presence of the middle-high-risebuildings and skyscrapers that are increasing in urban
areas.
2. SIMULATION
A shadow simulation is conducted in the NishiShinjuku area of Tokyo. Candidate points that may causea shadow of the target building group are placed on thegrid at 1 m intervals. Next, each candidate point issubjected to shadow judgment based on the result ofintersection judgment between the sun position and thebuilding wall at that time. These are not limited tobuildings that bring shadow directly, but by judging allbuildings. Here, building height is calculated from number
average floor height of 3.5 m in 23 wards of Tokyo [1] by

0
0

8[hours]
500[m]

figure 1. The equal time shadow
diagram116

the number of floors data. We acquire necessary data fromthe building GIS data and ZmapTownII (2016) [2] in therelevant area. We set the target date and time from 8:00
am to 4:00 pm on the winter solstice day and accumulate
the measured values every 15 minutes.
We consider the influence of shadow by skyscrapers
from the viewpoint of both increase time and overlap time.
Figure 1 shows the equal time shadow diagram. Figure 2
shows the addition-time-shadow diagram, and Figure 3
shows the superposition-time-shadow diagram.
3. CONCLUSIONSIn this study, we focus on the composite shadow madefrom skyscrapers and low to high-rise buildings. We
evaluated the effect of skyscraper shadow on the sunshine
environment of the block in terms of both the additiontime-shadow and the superposition-time-shadow.
First, superposition-time-shadows has a stronger
impact to congested buildings area than addition-timeshadow does. Second, the effect of superposition-timeshadow is almost as same as that of addition-time-shadow
in throughout the day.
REFERENCES[1] Yasunobu Ashie, and Takayuki Tokairin: Examinationof building heights for various building types in Tokyo 23wards: laser measurement data, Air-conditioning andSanitary Engineers of Japan (Transactions of the Societyof Heating), 2006, 31(115), pp.51-54, 2006 (In Japanese).
[2] Housing map database Zmap-TOWNII, Official
homepage.https://www.zenrin.co.jp/product/category/gis/basemap/zmaptown/index.html, May 17, 2019.

0
0

4+[hours]
500[m]

figure 2. The addition-time-shadow
diagram004+[hours]
500[m]

figure 3. The superposition-timeshadow diagram

NUMERICAL STUDY ON EFFECT OF NEW SEISMIC RETROFITTING METHOD TOMITIGATE THE DAMAGE IN NON-DUCTILE RC FRAME WITH MASONRY INFILL WALLS
S.C.SADINENI1, K.MEGURO2
1

PhD student, Department of Civil Engineering, the University of Tokyo, Japan
Director/Professor, ICUS, IIS, the University of Tokyo, Japan
Correspond to S.C.SADINENI (silpa@iis.u-tokyo.ac.jp)

2

Keywords: Non-ductile, reinforced concrete, masonry infills, seismic retrofitting, disaster risk mitigation
1. INTRODUCTION
Reinforced concrete (RC) frame with masonry infill
wall construction is the most common type of
construction in urban India (Figure 1). Majority of thesebuildings are insufficiently designed and detailed.

Table 2: Collapse simulation of the building withdifferent infill arrangements
Case
1

Intial stage

Final stage

Bare
Frame

2
(a) Roof material(b) Wall material
Figure 1. Census urban housing data, India, 2011
Past earthquakes exposing the seismic deficiencies ofthese collapse prone buildings have increased thenecessity for cost effective and adaptable retrofitting
methods. Considering the challenges, a new method has
been proposed (Figure 2) to improve the seismic
performance of these buildings by a) eliminating theundesirable frame-wall interaction and b) providing thePP-band mesh in out-of-plane direction.

Tight- fit
Infill3

Isolated
Infill4

Retrofitted
InfillFigure 2. Layout of PP-band mesh detailed wall
isolation method
2. NUMERICAL SIMULATIONSIn this study, seismic performance of four non-ductile
2-story frame buildings with different infill arrangement(Table 2) subjected to ground motion (Kocaeli
earthquake) was determined using the three-dimensional
Applied Element Simulation [2].
Table1.Non-ductile detailing of the RC frame
Section Dimensions Longitudinal Tie
(mm)
bars
Column 230×230
4#12mm#8mm@200
Beam

230×300

4#12mm#8mm@200

Based on the primary survey, typical features of 2story RC buildings in India have been used for the
analysis (Table 1). As shown in Table 2, Case (1) & (2)failed due to the brittle failure of columns. In Case (3),out-of-plane collapse of the walls was observed and nosevere damage in Case (4).
3. CONCLUSIONS
Results showed that the infill arrangement withproposed retrofitting method prevented the brittle shear
failure of the columns and out-of-plane collapse of walls.
REFERENCES[1] National Disaster Management Guidelines – Seismic
Retrofitting of Deficient Buildings and Structures,
Government of India, 2014.
[2] Meguro, K. & Tagel-Din, H. S. (2002). Applied
Element Method Used for Large Displacement Structural
Analysis. J. Nat. Disaster Sci. 24, 25–34.

117

DEVELOPMENT OF GROUT FOR FILLING SUBSURFACE CAVITY
T. TAN1, R. KUWANO2, N. KOSAKAI3, and M. KINJOU4
1

Student, Department of Civil Engineering, Graduate school of the University of Tokyo, Tokyo, Japan,
2
Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan,
3
Executive Officer, Cement-Related Product Department, Sumitomo Osaka Cement, Chiba, Japan,
4
Cement-Related Product Department, Sumitomo Osaka Cement, Chiba, Japan.

Keywords: Grout, Subsurface Cavity, Permeation, Unconfined Compression Test, Re-excavability
1. BACKGROUND
Sinkholes often occur in Japan due to aging ofunderground infrastructure such as sewer pipes. As acountermeasure, backfilling using excavation method has
been carried out to repair them. However, this method
takes huge amount of time and cost. Hence, maintenanceusing backfilling with cavity filling material is relatively
cost-effective. The performance of grout (cavity fillingmaterial mixing with water) is highly affected by its
material fluidity and the strength. In this study, permeation
behavior of grout to surrounding ground was investigatedto ensure there is no leakage into sewer pipes. Besides,
formulation design of grout with unconfined compression
tests were carried out and the optimum strength was aimed
to ensure the re-excavability. The main objective is todevelop new grout for filling subsurface cavity.

Silica No.5

Silica No.3

Relative Density, Dr (%)

50

80

50

80

Void ratio

0.81

0.73

0.83

0.73

Permeation Distance (cm)

0.3

0.2

1.0

0.8

Graph 1. Unconfined Compressive Strength Trends
150.0

Figure 1. Ground Model

2.1 Procedure
Cylinder-shaped groundmodel was built with 50%
and 80% of relative density.
Next, the grout was poured
into the model to a height of
Figure 2. Permeation Test
20 cm. The permeation
distance was measured after 8 hours. As shown in Figure
2, by adjusting the density of ground model, the loosening
ground between sinkhole and sewer pipe can be simulated.
3. UNCONFINED COMPRESSION TEST
In order to discover strength trends due to difference indesign formulation, unconfined compression tests withdifferent conditions have been carried out. Condition 1 inwhich different composition of main mixture andadmixture (calcium carbonate or fly ash) were mixed,
while curing methods of air curing or water curing arevaried in condition 2. Unconfined compressive strengthsof specimens were measured in 3 days, 7 days and 28 days.

118

Table 1. Test Conditions and Permeation Distance

Uniaxial Compressive Strenght, qu(kN/m²)

2. PERMEATION TESTIn the cross section ofground model shown in
Figure 1, backfilled grout
permeated through thesurrounding ground anddrained into the sewer pipe.
This condition is simulated
through one-dimensional
column permeation test
shown in Figure 2.

3.ANALYSIS ON RESULTIn permeation test, difference in relative density did notshow significant difference in permeation distance.
However, the effect of particle size is not negligible aspermeation distance increased with the particle size.
In the unconfined compression test results shown in
Graph 1, formulation where only main mixture was usedshows a relatively higher strength. Besides, curing method
did not show a big difference in the strength.

140.0

Case2,
Main mixture(Water curing)

130.0
120.0
110.0
100.0

Case1,
Main mixture(Air curing)

Case1,
Main mixture(Air curing)

90.0
80.0

Case2,
Main mixture(Water curing)

70.0
Case3,
Main mixture + CaCO₃(Air curing)

60.0
50.0
40.0
30.0

Case4,
Main mixture +CaCO₃ (Water curing)

20.0
10.0
0.0

Case3,
Main mixture+ CaCO₃(Air curing)
Case4,
Main mixture+ CaCO₃(Water curing)

0

5

10

15

20

25

30

Curing Days

4.CONCLUSIONS
Permeation of grout did not show a big permeation
distance. Grout do not drain into sewer pipe if thedamaged part is covered with sand. However, this is only
limited to homogeneous sand particles. On the other hand,formulation with only main mixture showed a higher
strength compared to admixture design. Further researchsamples are needed to determine the optimal compressive
strength in order to ensure the re-excavability of grout.
REFERENCES[1] W. Fukatani, T. Sakakibara, Study on the Use of Mortar Mixed Backfill Soil for Sewer Installation, Technical
Note of NILIM, No.531, pp. 34-60.

RETURNING HOME BEHAVIOR ANALYSIS OF
NEW CHITOSE AIRPORT USERS WHO WERE AFFECTEDBY THE 2018 HOKKAIDO EASTERN IBURI EARTHQUAKE
G. HAYAMIZU1, Y. MORISAKI2, T. MINAMI3, M. FUJIU4, Y. SHIOZAKI5, and J. TAKAYAMA6
Master Course Student, Dept. of Environmental Design, Kanazawa University, Kanazawa, Japan,
Doctoral Course Student, Dept. of Environmental Design, Kanazawa University, Kanazawa, Japan,
3
Doctoral Course Student, Dept. of Environmental Design, Kanazawa University, Kanazawa, Japan,
4
Associate Professor, Geosciences and civil Engineering , Kanazawa University, Kanazawa, Japan,
5
Assistant Professor, Geosciences and civil Engineering , Kanazawa University, Kanazawa, Japan,
6
Professor, Geosciences and civil Engineering , Kanazawa University, Kanazawa, Japan,
Correspond to Makoto FUJIU (fujiu@se.kanazawa-u.ac.jp)
1

2

Keywords: The 2018 Hokkaido Eastern Iburi Earthquake, blackout, Traffic paralysis, Questionnaire survey, Traffic
behavior
1. INTRODUCTION
In Japan, the 2018 Hokkaido Iburi Eastern Earthquake
is a disaster that caused many traffic problems. The 2018
Hokkaido Iburi Eastern Earthquake occurred at 3:07 on
September 6, 2018, with the Middle East of the Iburi
region as the epicenter. A maximum seismic intensity of 7
was observed in Atsuma town. In addition, in Hokkaido,
it was the first earthquake disaster in which seismic
intensity 7 was observed. Due to the influence of thisearthquake disaster, Blackout is occurred across Hokkaido.
As for traffic, all JR lines in Hokkaido, including the
Hokkaido Shinkansen, were stopped operation. As foraviation, the collapse of the ceiling and water leakage
occurred in the terminal building (New Chitose Airport
Building Co., Ltd 2018) due to the seismic intensity of 6
upper hit the New Chitose Airport. As a result, all flights
were stopped operation on September 6(Cabinet Office inJapan 2018). From the above, it can be said that Hokkaido
was isolated area after the disaster due to difficult to get
traffic information. New Chitose Airport is a very
important airport in the domestic aviation network. The
reason is that New Chitose Airport has routes to 22
airports in Japan. According to the result of the 5th
Nationwide Intercity Person Trip Survey conducted in2010. The transportation share is 95% by air, 3% by rail,and 2% by ship when moving central Hokkaido to outside
Hokkaido. From the above, it is considered that a lot of
people who planned to move to outside Hokkaido using
New Chitose Airport were existed.
2. SUMMARY OF QUETIONNAIRE SURVEY
In this study, web-based questionnaire survey was
conducted using monitors of Macromill, Inc. The target ofthe questionnaire survey is a very limited people because
they are victims of a sudden disaster and live outside
Hokkaido. Therefore, we used web-based web-basedquestionnaire survey that can expect many samples in ashort survey period. to secure as many samples as possible.
The survey period was from October 3rd to October 12th,2018. Screening was performed on 30,000 samples, andthe number of samples in this survey was 49 samples.

3. BASIC TABULATION OF QUESTIONNAIRESURVEY
Figure 1 shows the difference between the plannedmeans of transportation outside Hokkaido and the actual
means of transportation outside Hokkaido after thedisaster. The questionnaire screening is limited torespondents who were scheduled to take an air flight from
New Chitose Airport to their home on September 6-8,
2018.
Planned transportation
before the disaster

49
1

1
Transportation after thedisaster

33

4

2
1

0%

10%

20%

30%

40%

50%

60%

70%

4

80%

3
90%

Aviation(New Chitose Airport)

Aviation(Okadama Airport)

Aviation(Asahikawa Airport)

Aviation(Obihiro Airport)

Taxi

Bus

Ferry

Train

100%

Figure 7. difference between the planned means oftransportation and the actual means oftransportation outside Hokkaido
3. CONCLUSIONSThe 2018 Hokkaido Iburi Eastern Earthquake occurredat 3:07 on September 6, 2018, with the Middle East of the
Iburi region as the epicenter. In this study, A web
questionnaire survey was conducted immediately after thedisaster. A survey target lives in outside Hokkaido who
had planned to use New Chitose Airport. In Figure 7, after
the disaster, 16 out of 49 respondents (about 32.7%)
moved outside Hokkaido using various transportation
other than New Chitose Airport. From the two viewpointsof cost and time to return home, it became clear that thetime and cost were greatly changed due to the change oftransportation until going home.
REFERENCES[1] New Chitose Airport Building Co., Ltd (2018), Reportof The 2018 Hokkaido Eastern Iburi Earthquake[2]Cabinet Office in Japan (2018), Annual report of The
2018 Hokkaido Eastern Iburi Earthquake

119

BASIC STUDY ON THE DIFFICULTY OF EVACUATION IN THE REGION THAT CONSIDEREDGEOGRAPHICAL CHARACTERISTIC
T. SAKAI 1, Y. MORISAKI 2, M. FUJIU 3, J. TAKAYAMA4, Y. SHIOZAKI5, K. YANAGIHARA6, T. NISHINO3,
M. SAGAE7 and K. HIRAKO8
Master Course Student, Dept. of Environmental Design, Kanazawa University, Kanazawa, Japan,
Doctoral Course Student, Dept. of Environmental Design, Kanazawa University, Kanazawa, Japan,
3
Associate Professor, Geosciences and Civil Engineering, Kanazawa University, Kanazawa, Japan,
4
Professor, Geosciences and Civil Engineering, Kanazawa University, Kanazawa, Japan,
5Specially Assistance Professor, Dept. of Environmental Design, Kanazawa University, Kanazawa, Japan,
6
Associate Professor, Dept. of Health Science, Kanazawa University, Kanazawa, Japan,
7
Professor, Dept. of Economics and Management, Kanazawa University, Kanazawa, Japan,
8Specially Assistance Professor, Organization of Frontier Science and Innovation, Kanazawa University, Kanazawa,
Japan,
Correspond to Takashi SAKAI bass0418@stu.kanazawa-u.ac.jp)
1

2

Keywords: large-scale earthquake disaster, KDB data, vulnerable people, evacuation difficulty, regional evaluation
1. Introduction
In the 2011 off the Pacific coast of Tohoku Earthquake,mortality rate of elderly people over 60 years old were
accounted for 66% of the overall mortality rate in Iwate,
Miyagi, and Fukushima Prefecture. In the event of a largescale earthquake disaster, there are major problems with
evacuation for the elderly and people with disabilities. On
the other hand, it was obliged to create a list of people who
needed special assistance for evacuation in the event of adisaster. However, it was not used in the 2016 Kumamoto
Earthquake. In other words, there are still problems in theevacuation system for those people. To improve thissituation, it is indispensable to examine the actual
situation of evacuation, such as “how much live in whicharea” and “what kind of difficulties may be hit by during
evacuation”. Therefore, in Komatsu City, Ishikawa
Prefecture, we used the National Health Insurance
database to examine the number of people who wereconsidered difficult to evacuate at the time of disaster.
2. Visualization of evacuation difficulty
In this analysis, “Distance from house to designatedrefuge”, “Percentage of roads with a slope of 8% or morein roads in town”, and “Number of intersections per 1 mof road” were used as geographical difficulties during
evacuation. Principal component analysis was conducted
for these three variables. Figure 1 shows a visualization of
the first principal component. The primary principal
component score was defined as representing “evacuationdifficulty”. The “ratio of roads with a slope of 8% orhigher in roads within town letters” was selected withreference to Nitta et al[1].
There are 365 people in Imae town, 259 people in Ataka
town, 187 people in Mukaimotoori town, and many
people who need assistance for evacuation. Therefore, itis necessary to deal with a large number of supporters whoneed evacuation behavior at the time of disaster. Further,
Imae town and Ataka town, which are located in urban
areas and have many supporters who need evacuation
action, have a low evacuation difficulty in Komatsu City.

120

Ataka
Kamimugikuchi

Mukaimotoori

Arashi
Mugikuchi Nakanotouge

Imae

Hiyou
Akase
Principal component
analysis

Evacuation difficulty index-2.27 - -2.00-1.99 - -1.00-0.99 - -0.00
0.01 - 2.00
2.01 - 4.00
4.01 - 6.00
6.01 - 7.08
No da taFigure 1. Visualization of evacuation difficulty
On the other hand, Nakanoiso town, Arashi town and
Akase town are located in the suburbs, and there are few
people who need evacuation action. However, it became
clear that evacuation difficulty was high in those areas.
3. CONCLUSIONSIn this analysis, we conducted principal component
analysis using KDB data and the geographical difficultyindex during evacuation. And, we conducted a regional
evaluation on the difficulty of evacuation during a disaster.
The relative difference of geographical difficulty in theregion became clear. However, we used three regionaldifficulty variables. Therefore, we would like to increase
the number of variables in the future in order to evaluate
geographic difficulty in more detail.
REFERENCES[1] Y. Nitta, K. Koyama, H. Inoi, A. Nakahira: The burdenof elderly and disable walker on a slope, Proceedings ofCivil Engineering Planning (CD-ROM), 2004.

SESSION D
SPECIAL SESSION: SATREPS/ DISATER MANAGEMENT /DISASTER MITIGATION AND URBAN PLANNINGDetermination of site condition based on
microtremors survey in three selected townships of
Yangon, Myanmar
Tun NAING1, Su THINZAR2, Aung Myo ZAW2,
1
Professor, Department of Engineering Geology,
Yangon Technological University, Myanmar
tunnaing1972@gmail.com
2
Assistant Lecturer, (Engineering Geology), Department of Petroleum Engineering,Technological University (Mandalay), Myanmar
3
Ph. D Student, Geology Department, University of Yangon, Myanmar
ABSTRACT
Site condition is one of the major issues during an earthquake especially for the cities which
are situated in young sedimentary rock and recent alluvium areas like Yangon. Most of thetownships of Yangon are located in soft alluvial plain which is mainly composed of sand, silt
and clay, underlain by young sedimentary rock. Moreover, the seismogenic Sagaing Fault ispassing through about 40 km in the east of Yangon and it had experienced several destructive
earthquakes in the past. Studied townships: Mingalartaungnyunt, Dagon and Ahlon are major
townships of Yangon with high historical value besides their dense population. To understandthe potential site condition or site effects in those townships during an earthquake, themicrotremors survey and analysis had been conducted at 136 sites. The analysis reveals thatthe fundamental frequency of horizontal to vertical spectral ratio (HVRs) of microtremors is
generally ranging from 1.25Hz to 2.65 Hz, while the peak amplitude is between 0.7 and 3.9.
Based on combined analysis of secondary boring data and the inversion process fromfundamental frequency and peak amplitude of microtremors HVRs, the sediment thickness is
between 45m to 125m in general and the shear wave velocity of upper 30m depth (Vs30) is
ranging from 200m/s to 680m/s. The outcomes of this research are major input parameters
for future seismic risk analysis and development of township level earthquake resiliencemanagement system in Yangon.
Keywords: site condition, microtremors, HVRs, fundamental frequency, Vs30
1. INTRODUCTION
Yangon is the most socio-economically important city of Myanmar besides its highest densityof population especially in downtown area. The old and historical buildings are concentrated
in major parts of Yangon including the studied townships. The major seismogenic Sagaing
Fault is passing through 40 km east of Yangon and it had caused several destructive
earthquakes in the past. The damage and losses will be high due to its old buildings andsubstandard structures if there is an earthquake in future generated by the nearest Sagaing
Fault segment to Yangon. The local soil effect or site effect is one of the important factors forobserved damages during an earthquake. The adequate information of subsurface soil

122

December 2019, Yangon, Myanmar

condition is one of the important requirements for determination of the site effects andmicrotremors survey had been carried out in Mingalartaungnyunt, Dagon and Ahlon
townships to fulfill this requirement.
2. LOCATION AND SIZE OF RESEARCH AREA
Yangon is situated at the confluence of Hlaing River and Bago River on the eastern margin of
the Ayeyarwady delta. The studied townships; Mingalartaungnyunt, Dagon and Ahlon shownin Figure 1 are major townships of Yangon City regarding to their population density, socioeconomic conditions and existence of Yangon Region Government Head Office andShwedagon pagoda.
According to the 2014 Myanmar Population and Housing Census, 2015, MingalartaungnyuntTownship has the areal coverage of 5.06 km2 and population of 132,494. Dagon Townshiphas the area of 4.7 km2 and population of 25,082 while Ahlon has the area of 3.626 km2 andthe population of 55,482.

Dagon Tsp.

Mingalartaungnyunt Tsp.

Ahlon Tsp.

Figure 1: Location of studied townships
3. MICROTREMOR SURVEY AND ANALYAIS
The studies of Nakamura (1989) have indicated that the horizontal-to-vertical (H/V) spectral
ratio of microtremors, conveniently observed at a site with only one three-component sensor,
may approximate the amplification factor of the site for vertically incident S wave.
After a number of studies on the microtremor H/V spectra, it has been widely confirmed thatthe peak frequency of the microtremor H/V spectrum at a site corresponds nearly to thenatural site frequency (Nakamura, 1989). Shear wave velocity of all layers, the variation of
thickness of the layers can be estimated through the inversion of microtremor H/V spectrum

New Technologies for Urban Safety of Mega Cities in Asia

123

assuming that it reflects the fundamental-mode of Rayleigh wave (Hiroshi Arai and Kohji
Tokimatsu, 2005).
3.1 Microtremor survey
The single station microtremor surveying was carried out at 136 sites throughout the study
townships by using SMAR-6A3P model microtremor equipment as shown in Figure 2. The
measured sites in each township are: 52 sites in Mingalartaungnyunt Township, 44 sites in
Dagaon Township and 40 sites in Ahlon Township as shown in Figure 3.

Figure 2: SMAR-6A3P model microtremor equipment

Figure 3: Location of microtremor measured sites
3.2 Data analysis
The horizontal to vertical spectral ratio, H/V ratios of NS/UD and EW/UD components were
calculated first and the ratios of both components were then averaged to determine the final
observed microtremor H/V ratio. The data analysis generally includes the separation ofrecorded acceleration time historical data for each component, division of windows for every
40.96s of recorded data, determination of Fast Fourier Transform spectrum and calculation of
microtremor H/V spectral ratio for each measured site. The observed microtremor spectra
always shows two peaks; one at lower frequency while the other at higher frequency ranges asshown in Figure 4. The low peak amplitude suggests that the impedance contrasts between the124

Determination of Site Condition based on microtremors survey in three selected townships of Yangon,
MyanmarDecember 2019, Yangon, Myanmar

underlying soil layers are small and the high peak amplitude suggests that the impedancecontrasts between the underlying layers are large (Tun Naing et al., 2013).

Figure 4: Microtremor H/V Ratios of NS/UD, EW/UD Components and Observed Spectra atsome selected sites
3.3 Shear wave velocity inversion

H/V Spectral Ratio

The inversion of shear wave or S-wave velocity structures had been focused on the H/Vratio’s peak at low frequency (generally 1.2 – 2.65 Hz) by trial and error method. The H/V are
the primary concern and all spectra for two horizontal components are average and then takethe ratio to one vertical component because it does not need to separate site effects for two
components at a site (Kawase et al., 2011). Therefore, the mean H/V of NS/UD and EW/UD
is used for S-wave velocity inversion and results at DG-19 are shown in Figure 5 and Table 1.
5.0

Obs

initial

Modi

4.0
3.0
2.0
1.0
0.0

0.1

1

10

100

Frequency (Hz)
DG-19

Figure 5: Observed microtremor H/V spectrum and calculated H/V spectra for initial and final
model at DG-19
Table 1: Parameters of initial and modified soil model of DG-19
Layer
1
2
3
4
5
6
Elastic
Half space

Thickness (m)Initial
Modi.
10
7
12
12
13
15
14
18
22
22
30
30
-

-

Vp* (m/s)
Initial Modi.
1536
1293
1633
1365
1710
1502
1741
1664
1815
1815
1957
1957

Vs** (m/s)
Initial Modi.
320
180
380
220
430
300
450
400
500
500
600
600

Unit Wt. (g/cm3)
Initial
Modi.
1.94
1.86
1.97
1.88
1.99
1.93
2.00
1.98
2.02
2.02
2.06
2.06

2219

800

2.12

*Primary Wave Velocity

2219

800

2.12

**Shear Wave Velocity

New Technologies for Urban Safety of Mega Cities in Asia

125

The modification of initial soil model by increase or decrease of soil parameters of each soil
layer gives the best fit theoretical H/V spectra (green spectrum in Figure 5).
4. RESULTS AND DISCUSSIONS
The fundamental frequency of soil, potential soil amplification, soil thickness above theweathered bedrock and average shear wave velocity of upper 30 m depth zone are main
results of this research.
4.1 Fundamental frequency of underlying soil
Generally, the fundamental frequency is related to the thickness of soil layer at the
microtremor measured sites. The frequency of the fundamental peak of observed microtremor
H/V ratio is regarded as the fundamental frequency of underlying soil layers. The
fundamental frequency of studied townships is ranging from 1.25 Hz and 2.65 Hz as shown in
Figure 6 and soil thickness is between 45 m and 125 m as shown in Figure 7.

Figure 6: Map of fundamental frequency of underlying soil in studied three townships

Figure 7: Map of soil thickness in studied three townships
In Figure 6, the red color represents the highest frequency zones while purple color is thelowest frequency zones. The thicker soil layers are observed in lower frequency zones and126

Determination of Site Condition based on microtremors survey in three selected townships of Yangon,
MyanmarDecember 2019, Yangon, Myanmar

thinner sediment layers are encountered in higher frequency zones as shown in Figure 7. It is
more dangerous for high-rise building in lower frequency zones of thick sediments than lowrise buildings while the latters are more liable to severe damage in high frequency zones ofthinner sediments.
4.2 Potential soil amplification
The peak amplitude of H/V spectral ratios can be used to estimate the potential amplificationof underlying soil. The potential soil amplification map of the studied townships is shown in
Figures 8.

Figure 8: Map of potential soil amplification in studied three townships
The red color in Figure 8 represents the highest potential soil amplification zones and it iswell observed in northern and southern parts of Dagon Township where softer soil layers will
be encountered. The purple color is the lowest amplification zones and well observed in
Ahlon Township and south-eastern part of Mingalartaungnyunt Township where denser soil
layers are dominated. The stronger ground shaking therefore can be expected in higher
amplification zones due to softer soil layers there rather than lower zones during anearthquake.
4.3 Vs30
The average shear wave velocity of upper 30 m depth zone, Vs30, of each site had been
determined by using the following equation (MNBC, 2012) based on modified soil model.
n

vs =

d
n

d
i =1

Where,

i =1

i

i

(1)

v si

di = thickness of ith soil layer

vsi = shear wave velocity in ith soil layer
New Technologies for Urban Safety of Mega Cities in Asia127n = number of soil layer
Based on the results from 136 sites in three townships, the Vs30 map was prepared as shown in
Figure 9 and it ranges from 200 m/s to 680 m/s.

Figure 9: Vs30 map of studied three townships
Figure 9 shows that most parts of Dagon Township are covered by lower Vs30 zone while
higher Vs30 covers most parts of Ahlon and Mingalartaungnyunt townships. Longer andstronger ground shaking can be expected in lower Vs30 zone than higher zone.
5. CONCLUSION
This research mainly focused on the determination of ground information in
Mingalartaungnyunt, Dagon, Ahlon townships and the microtremor survey had been applied
as the main tool. Based on results from overall research works, the following facts arehighlighted.
1. The primary outcomes of this research are fundamental frequency map, potential soil
amplification map, map of sediment thickness, Vs30 map and related soil profiles.
2. Fundamental frequency is generally ranging from 1.25 Hz to 2.65 Hz. Generally, thelower frequency zones are dangerous for high-rise buildings and higher frequency
zones are dangerous for low-rise buildings.
3. Higher ground motion and shaking can be expected in the zones with higher potential
soil amplification where the soil layers are softer than others places.
4. S-wave velocity is ranging from 200 m/s to 680 m/s in general and the higher shear
wave velocity is observed at the sites with lower peak amplitude of H/V ratios andweaker ground shaking can be expected. Meanwhile, the lower shear wave velocity isobserved at the sites with higher peak amplitude of H/V ratios and stronger groundshaking can be expected.

128

Determination of Site Condition based on microtremors survey in three selected townships of Yangon,
MyanmarDecember 2019, Yangon, Myanmar

5. The outcomes of this research are the important input parameters for better urban
planning and development of a comprehensive disaster resilience system in Yangon.

REFERENCES
Arai, H. and Tokimatsu, K., 2005. S-Wave Velocity Profiling by Joint Inversion of
Microtremor Dispersion Curve and Horizontal to Vertical (H/V) Spectrum. Bulletin of the
Seismological Society of America, Vol.95, No.5, pp. 1766-1778.
Kawase, H., San’chez-Sesma, F.J. and Matusushima, S., 2011. “Effect of Surface Geology on
Seismic Motion: Application of the H/V Spectral Ratios for Earthquake and Microtremor
Ground Motion” 4th IASEI / IAEE international Symposium, University of California Santa
Barbara, USA, page 1-13.
Ministry of Immigration and Population, 2015. The Union Report: the 2014 Myanmar
Population and Housing Census, Census Report Volume 2.
MNBC, 2012. Provisional Myanmar National Building Code, Federation of Myanmar
Engineering Societies, Myanmar.
Naing, T., Kawase, H., Matsushima, S., Thant, M., Mon, S. T., Tin, T. H. and Oo, K., K., K.,
2013. S-Wave Velocity Profiles Based on the HVRs in Bago, Myanmar for Seismic Hazard
Mapping, Proceeding, International Symposium on Earthquake Engineering, JAEE, Vol.2.
Nakamura, Y., 1989. A method for dynamic characteristics estimation of subsurface using
microtremor on the ground surface. ser.Rep. Railway Tech. Res. Inst., Jpn, vol30 (1), 25–33.

New Technologies for Urban Safety of Mega Cities in Asia

129

INVESTIGATION OF DISASTER RESPONSE ACTIVITIES OFADMINISTRATION OFFICES OF YANGON CITY
H. GOKON , T. KATO2, M.M. MON3, T. NAING4, M. NUMADA5 and K. MEGURO2
1

1

Associate Professor, School of Knowledge Science, JAIST, Ishikawa, Japan,
2
Professor, ICUS, IIS, The University of Tokyo, Tokyo, Japan
3
Master Student, Yangon Technological University, Myanmar
4
Professor, Yangon Technological University, Myanmar
5
Associate Professor, ICUS, IIS, The University of Tokyo, Japan
Correspond to H. Gokon (gokon@jaist.ac.jp)

Keywords: disaster response activities, flow chart of disaster response, Yangon city
1. INTRODUCTION
Myanmar has been threatened by natural disasters (e.g.
the 2008 Cyclone Nargis). Each administrative
organization in Yangon City has taken various measuresagainst natural disasters, but activities of who did what
and when were not clearly recorded well. There is also a
big difference between the disaster response operationsin terms of both quantity and quality of information. At
the township level in Yangon City, Kikuchi et al.(2018)
investigated three regional disaster prevention plans, but
the structure of disaster prevention-related work in
Yangon City as a whole has not yet been clarified. The
objective of this study is to analyze the actual situation of
undocumented disaster response by conducting interview
surveys with the Relief and Reconstruction Bureau in
Yangon City about disaster response operations
conducted before, after, and after the disaster.
2. METHOD
Based on interviews in Yangon City and existingdisaster prevention documents, we analyzed the overall
picture of disaster response operations. The field survey
was conducted in two parts: June 15 to July 31 andDecember 6 to 15 of 2017. For the interview, we asked
the staff who worked for 30 years to the Department of
Rehabilitation and Rehabilitation (RRD, now renamed toDDM) of the Ministry of Social Welfare andRehabilitation in Yangon City.
(1) Understanding the overall picture of disaster
response operationsFirst, we interviewed the general picture of the disaster
response work about the name of the administrative
organization related to the disaster related work and the
documents related to disaster prevention when a disasteroccurred in Yangon City.
(2) Survey of organizations in charge of disaster
response operations
Based on the survey results in (1) and the regional
disaster prevention plan in Myanmar and Japan, achecklist was prepared to investigate disaster prevention
operations including the information of before and after
the disaster, the recovery and reconstruction period, andmembers involved in the disaster prevention andrecovery. We interviewed the staff again. The survey
items before the disaster were 75 items, and the survey

130

items after the disaster were 113 items. The 25
administrative organizations including ministries and citycommittees were included in the interview sheet.
(3) Investigation of disaster response work flow
In order to clarify the flow of disaster response
operations, a workflow was created for responses after
the disaster. Based on the interview survey results, anoutline of the work flow was created, and the staff of theRelief and Reconstruction Bureau confirmed each one tocorrect and improve.
(4) Confirmation of the validity of the survey results
We conducted interviews with RRD and GAD at thetownship level, and verified the validity of the survey
results in (2) and (3).
3. RESULTS AND DISCUSSIONSAs a result of interviews, it was found that at least 12
ministries and 12 disaster prevention committees wereinvolved in disaster response work in Yangon City. As adocument related to disaster prevention, the RRD in
Yangon City has Myanmar Action Plan on Disaster Risk.
As a result of the investigation of the number ofoperations using the disaster response operation checklist,
we were able to quantitatively analyze the disaster
response operation burden of each ministry. In addition
to RRD and GAD, the Fire Department, Yangon City
Development Committee, the police, the Ministry of
Insurance, and the Red Cross have more work than otherministries.
4. SUMMARY
We conducted a survey and analysis of the actual
situation of disaster response operations in Yangon City.
As a result, the ministries and agencies that are deeply
involved in disaster response work and the overall
picture of the disaster response work flow were clarified.
REFERENCES[1] Rena Kikuchi, Muneyoshi Numada, May Myat Mon,
Tun Naing, Khin Than Yu and Kimiro Meguro: A
Comparison of Disaster Management Plans for BothJapan and Myanmar, Journal of Disaster Research (JDR),
Vol. 13, No.1, 2018

Slope modeling for future slope stability
in Hakha City, Chin State, Myanmar
May Myat MON1, Tun NAING2, Kyaw Zin LATT3, Muneyoshi NUMADA4, Khin
Than YU5, Kimiro MEGURO6
1
Master Student, Dept. of Engineering Geology, Yangon Technological University,
Myanmar, casperrosey@gmail.com
2
Professor, Dept. of Engineering Geology, Yangon Technological University,Myanmar
3
Lecturer, Dept. of Engineering Geology, Yangon Technological University, Myanmar
4
Lecturer, International Center for Urban Safety Engineering, the University ofTokyo,Japan
5
Pro-Rector, Yangon Technological University, Myanmar
6
Professor, International Center for Urban Safety Engineering,
the University of Tokyo, Japan
ABSTRACTHakha City has to face one of the major geo-hazards, landslide, during the raining
season of every year. Mudstone and siltstone are mainly observed in most of the slopes
and sometimes thin layers of sandstone are intercalated. High and deep weathering ofrocks and heavy rainfall are major controlling factors besides slope gradient. The
landslides in August, 2015 had affected large parts of Hakha, especially in Zaythit ward,
Myohaung ward and the wards along Dauchim road. The landslide inventory survey
had been conducted based on field survey and historical records to understand the
distribution and types of landslides. Soil and rock samples were collected at someselected slopes and engineering geological properties such as shear strengthparameters, moisture content, Atterberg’s Limits and so on, were determined tounderstand the behaviors of slope materials. Moreover, Twenty nine ground control
pints were constructed throughout the Hakha city for aerial survey to obtain good
accuracy of ground elevation model. The digital elevation model, DEM, is final
outcome of this survey and this DEM will be the great help for the construction of slope
profile or slope configuration of interested slopes in Hakha city. The slope modeling is
conducted in this research based on the laboratory tests results and DEM maps for
future landslide or slope instability as a result of stress exceeding the shear strength of
the slope material. The excess stress could be added with increasing pore water,
excessive overburden pressure due to external load, and so on. Moreover, poor soil
condition, weathering, slope geometry, soil stratification, discontinuities in the rock
body are some other common factors for slope instability in Hakha.
Keywords: landslide hazard, highly deformed, deeply weathered, slope modeling, future
landslide assessment
1. INTRODUCTION
The proposed research area, the new Hakha City region, is located in the Chin Hills
which forms part of Western Fold Belt. Devastating landslides occurred in this area in131

December 2019, Yangon, Myanmar

August 2015, followed by severe landside damage along the Falam-Hakha road andsome places of Hakha city. Due to this disaster, some parts of Hakha city were going to
be resettled in a new location. Most of the areas around Hakha City are hilly and containhigh topographic features with steep slope.
The characteristic of slope materials is one of the major controlling factors of landslidein this city. The stability of existing slopes is important issue for the development of thiscity and the detailed slope stability analysis is required for the critical slopes inside thecity based on geology and engineering geological properties of slope materials. For
those reasons, the soil samples were collected at some selected critical slopes andvarious laboratory tests were conducted to determine the physical and mechanicalproperties of soil. Slope modeling is important issue to understand the mechanism toassess the future landslide.
1.1 Location and Size
The study area, Hakha city is the capital of Chin State which is situated in Western
Ranges of Myanmar. The Hakha City is located at 22°40′37.94′′ N and Longitude
93°35′9.94′′ E as shown in Figure 1. The area coverage of Hakha city is 32.37 km2 andthe population is 24,926 according to the 2014 Myanmar Population and Housing
Census situation.

Hakha City

Figure 1: Location Map of Study Area
2. GEOLOGICAL CONDITION OF THE STUDY AREA
The study area is composed of the flysch types of sedimentary and metasedimentaryrocks. It can be divided into three different rock units according to lithology,
stratigraphic position and faunal content: the Falam Mudstone-Micrite Formation, theChunsung Mudstone Turbidite Formation, and the Kennedy Sandstone Formation.
2.1 Weathering Condition of Rock132

New Technologies for Urban Safety of Mega Cities in Asia

Weathering of rocks in the slope is one of the influential factors for a landslide. The
rocks in Hakha are highly and deeply weathered due to high intensity of annual rainfall
and deformation of rocks (Figure 2).

Figure 2: Weathering condition of rock in slopes of Hakha city
2.2 Deformation of RockThe rocks in Hakha area are young sedimentary rocks of Upper Cretaceous to Eocene
age. The rocks are mainly mudstone, silty mudstone, slaty mudstones and sandstones,
and they are generally regarded as soft rocks. The active subduction and collision ofIndian plate and Myanmar minor plate have caused those soft rocks highly deformed
and brecciated (Figure 3).

Figure 3: Deformation in rocks of Hakha area
3. SLOPEMODELING FOR FUTURE SLOPE STABILITY
The field survey and observation mainly consists of geological observation, engineering
geological observation at selected slopes in Hakha and aerial survey by drone.
3.1 Soil Sampling and Laboratory Testing
The disturbed soil samples were collected from 30 selected slopes of Hakha city for
identification of material types and laboratory testing. Sealed plastic bags and PVC
pipes with proper caps were used to store the collected samples. The locations ofcollected soil samples are shown in Figure 4.

Your paper title

133

December 2019, Yangon, Myanmar

Figure 4: Locations of Collected Soil Samples
The collected soil samples were tested the following physical and mechanical tests todetermine the engineering properties of soil in the slopes of Hakha city.
1.
Sieve Analysis
2.
Atterberg’s Limited Test (Casagrande)
3.
Standard Compaction Test (Proctor Test)
4.
Moisture Content Test
5.
Specific Gravity Test
6.
Direct Shear Test
The grain size distribution test was conducted according to ASTM - D422 to classify
the soil type in Hakha and the grain size distribution curves are drawn.
The soil in the slopes of Hakha can generally be regarded well graded soil because
gravel, sand, silt and clay are well observed although the majority are sand and silt andminor amount of gravel and clay.
Atterberg’s Limits tests were conducted according to ASTM – D2216. The flow curvesof liquid limit determination at some selected slopes. The liquid limit at L1 is 52.0 %and Plastic Limit is 34.95 % while the Plasticity Index (PI) is 17.05 %.
This test was conducted according to ASTM-D698 using collected disturbed samples.
The optimum moisture content and maximum dry density of soil were determinedthrough this test.

134

New Technologies for Urban Safety of Mega Cities in Asia

(a)

(b)
Figure 5: (a) Soil Testings, (b) Some Laboratory Test Results
Table 1. Summary of Laboratory Test Results
Atterberg’s Limits
SlopesDrydensity

Sieves Analysis

Moisture
Content

Strength
Parametersw

Triaxial

Soil
Types

LL

PL

PI

Gravel

Sand

Silt

Clay

%

%

%

%

%

%

%

g/cm3

%

c (kPa)

ɸ (°)

1

52

34.95

17.05

13

52

15

20

2.12

16.572

0

38.5

SC

2

38

25.01

12.99

25

26

18

31

2.05

16.133

341

30.5

CL

3

41

27.93

13.07

15

47

11

27

2.05

20.184

163

10°

SC

4

51

33.38

17.62

8

22

37

33

1.92

25.223

283

16.5

MH

5

59

37.97

21.03

5

14

41

40

1.80

31.974

59

6

MH

10

38

24.41

13.59

1

8

52

39

1.87

22.423

107

18

CL

11

39.5

24.12

15.38

10

32

25

33

1.83

19.645

34

3

CL

12

51

33.65

17.35

4

8

43

45

1.81

27.506

165

8.5

MH

13

45.5

28.31

17.19

3

31

28

38

1.83

19.548

159

6.5

CL

14

38.5

25.88

12,62

29

27

25

19

1.91

19.828

69

17

GC

15

55.50

38.73

16.77

1

8

53

38

1.66

35.749

131

19

MH

16

31.00

21.21

9.79

13

54

19

14

2.25

12.821

99

11

SC

17

56.50

40.84

15.66

19

25

30

26

1.55

30.348

93

28

MH

18

38.00

23.48

14.52

28

38

16

18

2.25

13.608

159

21.5

SW

19

32.00

17.38

14.62

24

52

13

11

2.53

10.495

138

17.5

SW

20

55.00

37.09

17.91

27

22

33

18

1.77

26.574

138

25.5

MH

21

44.50

30.92

13.58

20

33

27

20

1.95

17.044

59

14

SM

22

45.50

33.06

12.44

15

39

23

23

1.96

14.592

52

23.5

SM

Your paper title

135

December 2019, Yangon, Myanmar
23

44.50

31.78

12.72

18

23

46

13

1.64

24

41.50

27.68

13.82

22

22

32

24

1.90

25

25.00

16.55

8.45

8

27

43

22

2.18

24.06145

3ML

16.55321

12ML

15.93572

8ML

3.2 Aerial Survey by Drone
Twenty nine ground control points (Figure 6) were constructed throughout the Hakha
city (both old and new cities) for aerial survey to obtain good accuracy of groundelevation model. The ground control points were constructed based on government
bench mark which was located at the top of Mt. Rung by RTK survey instruments using
GNSS solution.

Figure 6: Location of Ground Control Points in Hakha
Phantom 4 Drone was used to take the aerial photographs from the altitude of 266 m
and total 4684 images with ground resolution of 6.76 cm/pix were taken. The drone wastaking the images along the total numbers of 66 flight paths and some aerial surveying
activities.
The digital elevation model, DEM (Figure 7) is final outcome of this survey and thisDEM will be the great help for the construction of slope profile or slope configurationof interested slopes in Hakha city.

136

New Technologies for Urban Safety of Mega Cities in Asia

Figure 7: Digital Elevation Model (DEM) of Hakha City
According to Figure (6), the lowest elevation of Hakha city is 1319 m above mean sea
level and it is around the eastern most part of old city. The highest elevation is 2106 m
and it is in the northern most part of new city. The profiles of interested slop can begenerated from obtained DEM of Hakha city. The profile along the AA′ section in
Figure (7) is shown in the following Figure (8,9,10,11,12).

Figure 8: Slope Profile along the Line L-7

Figure 9: Slope Profile along the Line L-14
Your paper title

137

December 2019, Yangon, Myanmar

Figure 10: Slope Profile along the Line L-16

Figure 11: Slope Profile along the Line L-19

Figure 12: Slope Profile along the Line L-23
4. DISCUSSION
According to sieve analysis, the soil from the selected areas is mainly composed of 26%
of clay, 30% of silt, 29% of sand and 15% of gravel in average. The dry density isrelatively low. Most of the slopes are composed of low to high plasticity silty (ML-MH)
and clayey (CL) soil.
The liquid limit is ranging from 25% to 59% and the high liquid limits can be observedin slopes 1, 4, 5, 12, 15, 17 and 20. The plastic limit is between 16.55% and 38.73% andthe plasticity index ranges from 8.45% to 21.03%. The moisture content in soil is from
10.5% to 35.7% at the time of sample collection in May and the moisture content will
be higher in the middle of raining season.
The soil from slopes 1, 2, 17 and 20 give relatively high angle of internal friction (>25˚)
while those from slopes 3, 5, 11, 12, 13, 23 and 25 give low angle of internal friction

138

New Technologies for Urban Safety of Mega Cities in Asia(≤10˚). The cohesion is ranging from 0 to 341 kPa and 114 kPa in average. The shear
strength of soil in some slope can be very low where both cohesion and angle of internal
friction are low.
The determined slope models together with unit weight of soil, shear strengthparameters; cohesion (c) and angle of internal friction (ɸ), and classified soil types andtheir thickness will be the main input parameters for future detailed slope stability
analysis in future.
5. CONCLUSION
Based on the field observation and recent research work, it is the urgent need to conduct
the systematic study and analysis of landslide potential for sustainable development of
the region.
It is obvious that Hakha city has two important influential factors for landslide; highrelief and high weathering together with extremely deformed rocks in the slopes.
Besides that, heavy rain fall and poor land use are triggering factors of landslide andslope failures in Hakha area.
The soil is composed of high percentage of clay and silt which are low permeable.
Therefore, the percolated rain water inside the slope cannot be drained completely in adesignated period. Consequently, the pore water pressure inside the slope gradually
increases and finally the high uplift pressure caused landslides and other slope failuresin Hakha. The determined physical and mechanical properties of slope materials arefundamental parameters for engineering geological modeling of critical slopes for futureslope stability analysis.
Soil types and related properties were determined for thirty selected slopes of new
Hakha city. Digital Elevation Model and contour map with five meter interval had beensuccessfully created for Hakha city (both old and new) based on results of aerial survey
by drone.
Slope profiles had been successfully modeled based on Digital Elevation Model andlaboratory test results of related soil samples.
REFERENCE
M.S. Islam, M.A. Hussain, Y.A. Khan, M.A.I. Chowdhury and M. B. Haque, “Slope
Stability Problem in the Chittagong City, Bangladesh,” Journal of GeotechnicalEngineering (JoGE) vol. 1(3), 2014, pp. 13-25.
D. B. E. Putra and T. Choanji, 2016. ‘Preliminary Analysis of Slope Stability in Kuok
and Surrounding Areas,” J. Geoscience, Engineering, Environment, and Technology,
vol. 1, 2016, pp. 4144.
R. Anbalagan, “Landslide hazard evaluation and zonation mapping in mountainous
terrain”, Eng Geol. 32, 1992, pp. 269–277.
P. Aleotti, R. Chowdhury, “Landslide hazard assessment: summary review and new
perspectives,” Bull Eng Geol Environ, 58, 1999, pp. 21–44.
H. X. Lan, C. H. Zhou, L. J. Wang, H. Y. Zhang and R. H. Li, “Landslide hazard spatial
analysis and prediction using GIS in the Xiaojiang watershed, Yunnan, China,” Eng
Geol. 76, 2004, pp. 109–128.
Chin Committee for Emergency Response and Rehabilitation (CCERR), “The Chin
State Floods & Landslides: A Community-Led Response and Assessment,” Report, Dec.
2015.

Your paper title

139

December 2019, Yangon, Myanmar

M. H. Nyo, R. S. Grant, M. T. Aye, and Y. L. Yee, “Rodent population outbreaks
associated with bamboo flowering in Chin State, Myanmar,” Researchgate, 2010.
Ministry of Immigration and Population, “The 2014 Myanmar Population and Housing
Census,” The Union Report, Census Report Volume 2, May 2015.
Department of Geological Survey and Mineral Exploration and United Nations,“Geology of the Falam – Kalemyo area northern Chin hills” 1977.

140

New Technologies for Urban Safety of Mega Cities in Asia

SOIL-STRUCTURE-INTERACTION EFFECTS ON THE DAMAGE STATEOF TYPICAL BUILDINGS IN YANGON
Khin Myat Kyaw1 and K. MEGURO2
Graduate Student, Civil Engineering Department, The University of Tokyo (UTokyo), Japan
Director/Professor, International Center for Urban Safety Engineering, Institute of Industrial Science, U Tokyo, Japan
Correspond to Khin Myat Kyaw (khinmyatkyaw2012@gmail.com)
1

2

Keywords: soil-structure-interaction, damage state, vulnerability, microtremor measurement
1. INTRODUCTION
Building damage mechanism during an earthquake
event relies on the different factors such as the intensity ofthe event, seismic resistant capacity of the building andunderlying soil condition. In case of vulnerability
assessment work, normally soil part is neglected assuming
the building is situated on firm base. However, soil
behavior during shaking plays a vital role in the collapse
mechanism of the building [1]. Because of the soil
flexibility underneath the building, the natural period getslonger resulting in enhanced effective damping ratio andincreased displacement demand [2]. Nakhaei found outthat the damage index of the short period buildings
significantly increases on softer soils and the effect ismore prominent in the structures with high aspect ratio.
[3]. The above-mentioned studies show that the soil
structure interaction (SSI) effect is important for thedamage estimation of the building in the vulnerability
assessment process.
2. COLLECTION OF BUILDING INFORAMTION
AND NUMERICAL MODELING
Yangon with its rapid urbanization and increased
population, construction industry rapidly developed
during the recent years. According to building types
information from YCDC (2016), timber, RC and bricknogging types occupied the highest percentage in theorder of approximately 51, 41, and 3 %, respectively.
Timber, brick-nogging and some low-rise RC buildings
are non-engineered constructions and the recorded
building information and material properties are notavailable. Therefore, field work on building informationcollection and material testing were conducted for theselected buildings. Samples for material property testing
were collected from the existing buildings which were

Figure 1. Material Testing Works for Masonry and Woodabout to be demolished. It was resulted using the ASTM
standard testing procedures that the mean compressive
strength of masonry block is around 680 psi and that ofInn/ Kanyin wood is 4,400 psi.

Initial analysis is started with two-storeyed brick-nogging
building situated in Shwe Pyi Thar township in Yangon.
For the SSI numerical model, substructure approach isadopted through ASCE 41-13 procedure by considering
the shallow foundation as rigid. Translational androtational stiffness were calculated taking the soil shear
wave velocity values as 200 m/s and poisson’s ratio to be
0.3.

Figure 2. Uncoupled Spring Model using ASCE 41-13
Procedure
Microtremor measurement was also conducted in themodeled building to know the natural frequency of the soil
and building. Modal analysis results were enumerated in
the Table below.
Table 1. Modal Analysis Result of Two-storeyed Bricknogging Building using Uncoupled Spring Model andMicrotremor Measurement
PeriodFixed Base
0.84 sPeriodLinearBase
0.93 sPeriodNonlinearBase0.93 sPeriodMicrotremor
Measurement
0.95 s3. CONCLUSIONS
It can be seen from the initial modal analysis of two
storeyed brick-nogging building, the natural period getslonger, and it approximately matches the microtremor
measurement result. Building responses and damage
pattern comparison for different buildings throughnonlinear dynamic analysis will be discussed later in the
USMCA 2019 presentation.
REFERENCES[1] Chopra A. and Yim S.C., ASCE Journal of StructuralEngineering, 111(4), (1985), 906-930.
[2] John P. Wolf, Dynamic Soil Structure Interaction,
Prentice-Hall, Englewood Cliffs, New Jersey, (1985)[3] Nakhaei M. and Ghannad M.A., The effect of soil
structure interaction on damage index of buildings,
Journal of Structural Engineering, 30, (2008), 149199.
[4] Gazetas, G., Journal of Geotechnical Engineering,
117(9), (1991), 1363-1381.
[5] ASCE/SEI 41-13, Seismic Evaluation and Retrofit of
Existing Buildings, Reston, Virginia, 2013.
[6] Nakamura, Y., A Method for Dynamic Characteristics
Estimation of Subsurface Using Microtremor on the
Ground Surface, Quarterly Report of Railway
Technical Research Institute 30, (1989), 25–33.

141

One-dimensional seismic response analysis byequivalent linear method in Kyauktada, Pazundaungand Botahtaung Townships,Yangon, Myanmar
Su THINZAR1and Tun NAING2
1
Assistant Lecturer (Engineering Geology), Department of Petroleum Engineering,Technological University (Mandalay), Myanmar
tharyar.stz@gmail.com
2
Professor, Department of Engineering Geology,
Yangon Technological University, Myanmar
ABSTRACT
Yangon had experienced several earthquakes in the past because it is located in the moderate
seismic prone area and the seismogenic Sagaing Fault is passing through about 40 km awayfrom Yangon in the east. The studied Kyauktada, Pazundaung and Botahtaung are major
townships of Yangon and are located mostly in soft alluvial plain of sand, silt and clay wherestrong ground motion can be expected. The microtremors survey had been conducted at 84
sites throughout the studied townships. One-dimensional seismic response analysis byequivalent linear method had been performed based on the shear wave velocity structures andsubsurface soil profiles derived from microtremor survey and boring data. The peak groundacceleration (PGA), the peak ground velocity (PGV), the response accelerations and the
predominant period are main outcomes of response analysis. The PGA values are ranging
from 0.16g to 0.28g while the PGV values are between 0.75cm/s and 1.55cm/s. The response
acceleration at 1.0s ranges from 0.07g to 0.19g and it is ranging from 0.58g to 1.10g at 0.2s.
Keywords: response analysis, microtremors survey, PGA, PGV, response accelerations
1. INTRODUCTION
Yangon is the most important city in Myanmar for the public commercially and educationally.
One of the remarkable historical events that Yangon had experienced in the past is Bago
Earthquake (7.3Mw) which was due to the Sagaing Fault on May 5 of 1930. At that time, thedeath toll in Bago was 500 and 50 in Yangon. There will be several folds in death tolls anddamages in Yangon when that earthquake recurrences due to high population density, many
substandard buildings and a large number of old buildings. High amplification of underlying
soil can cause stronger ground motion in Yangon because several large townships, including
studied townships are located in soft alluvial plain which is mainly composed of sand, silt andclay.
The shear wave velocity structures and engineering properties of underlying soil layers aremain input parameters for seismic response analysis. Therefore, the shear wave velocity
structures and engineering properties of each soil layer in studied townships were determinedby combining the microtremor survey results and secondary boring data. Another main input
parameter is the earthquake bedrock motion and however, no recorded bedrock motion is142

December 2019, Yangon, Myanmar

available for Yangon area. The computer code prepared by Ohsaki in 1979 was used togenerate synthetic bedrock motion.
2. AERIAL COVERAGE OF STUDIED AREA
The studied area; Kyauktada, Pazundaung and Botahtaung Townships are located in shoutheastern part of downtown Yangon as shown in Figure 1 and bounded by Yangon River in theSouth and Pazundaung Creek in the East. Kyauktada Township has the population of 3,700
while 3,100 in Pazundaung Township and 40,995 in Botahtaung Township according to 2014
Myanmar Population and Housing Census (Ministry of Immigration and Population, 2015).
The area coverage of Kyauktada Township is 0.6 km2, Pazundaung Township is 1.01 km2 andthat of Botahtaung Township is 2.4 km2, and 4.01 km2 in total.

Figure 1: Location map of Kyauktada, Pazundaung and Botahtaung townships(Google Earth Image, 2019)
3. SEISMICITY OF YANGON
The historical earthquakes, geologic and tectonic settings around the city highlight that
Yangon is located in a moderate seismic prone area (Su Thinzar et al., 2018). The
Seismogenic Sagaing Fault, the most active seismic source in Myanmar, is passing throughabout 40 km away in the east of city (Soe Thura Tun, 2007). The most well-known earthquake
for Yangon area is Bago earthquake of 7.3 Mw, on May 5 of 1930.
4. DETERMINATION OF INPUT PARAMETERS
The input parameters, especially the underlying soil information for seismic response analysis
had been determined by microtremor survey throughout the studied townships. The survey
results were combined with available secondary boring data.
4.1 Microtremor survey
According to Nakamura, 1988, the microtremors are low amplitude ambient seismic noises
generated by natural disturbances and microtremor survey has been used as a tool to estimate
seismic response of underlying soil layers. Based on the diffuse field theory, Kawase et al.,One-dimensional seismic response analysis by equivalent linear method in Kyauktada, Pazundaungand Botahtaung Townships, Yangon, Myanmar

143

2011, proved that the microtremor H/V spectral ratios correspond to the square root of theratio of the imaginary part of horizontal displacement for a horizontally applied unit harmonicload and the imaginary part of vertical displacement for a vertically applied unit load.
The microtremor single station measurements had been conducted at 84 sites in threetownships: 20 sites in Kyauktada Township (green colour), 20 sites Pazundaung Township(blue colour) and 44 sites in Botahtaung Township (orange colour) as shown in Figure 2. Byusing SMAR-6A3P seismometer, it was measured for 20 minutes at each site and thesampling rate is 200 Hz/s. The horizontal to vertical spectral ratio (H/V ratio) was calculated
for each site. The required input soil information for 1D seismic response analysis wereobtained by inversion of shear wave velocity structures from H/V ratio.

Figure 2: Locations of microtremor measurements in studied three townships
4.2 Input earthquake motion
As the recorded bedrock motion for Yangon is not available, the synthetic waveform of 1930
Bago earthquake was generated by Ohsaki’s (1979) computer code based on magnitude of 7.3
Mw, assumed focal depth of 20 km, and epicentral distance of 42 km for earthquake input
motion (Su Thinzar et al., 2018) as shown in Figure 3.
Synthetic Bedrock Motion of 1930, Bago EQ (7.3 Mw)

Acceleration (Gals)

150
100
50
0
-50
-100
-150

0

10

20

30

40

Time (s)Figure 3: Synthetic bedrock motion for studied townships
The maximum acceleration of synthetic earthquake bedrock motion in Figure 3 is 108 gals or
0.11 g.

144

One-dimensional seismic response analysis by equivalent linear method in Kyauktada, Pazundaungand Botahtaung Townships, Yangon, Myanmar

December 2019, Yangon, Myanmar

5. 1D SEISMIC RESPONSE ANALYSIS
1-D seismic response analysis was conducted by equivalent linear method, using DYNEQ
computer program, coded by Yoshida et al. in 2004 for each site where microtremor wasmeasured. DYNEQ is a computer code for the earthquake response analysis of the levelground in frequency domain based on the equivalent linear method and multiple reflection
theory. Since multiple reflection theory is an exact solution of the governing equation (wavepropagation equation), it has an advantage that incident and reflected waves can be separated,
input wave can be specified at any point and any types of wave (incident, composite, orreflected), and any types of wave can retrieve at any location, which is impossible in the
nonlinear analysis, and some of them are important in the engineering practice (Yoshida et al.,2004).
The shear wave velocity of 800 m/s was used for elastic half space or weathered bedrock
below all soil layers (Hirokawa, 2016). The shear wave velocity, thickness and unit weight ofeach soil layer, the number of soil layers, and earthquake bedrock motion are the main inputs
parameters of response analysis. Theoretical amplification characteristics from layer of elastic
half space or weathered bedrock to surface had been determined for consideration of thestrong ground motion due to lose alluvium sediments.
6. RESULTS AND DICUSSION
The major results of this research are spectral response spectrum (response accelerations for1s and 0.2s), peak ground acceleration (PGA) and peak ground velocity (PGV).
6.1 Response spectrum
The response spectrum is used extensively in earthquake engineering practice. The response
spectrum describes the maximum response of a single degree-of-freedom (SDOF) system to aparticular input motion as a function of the natural frequency (or natural period) and damping
ratio of the SDOF system (Kramer, 1996). Some response spectra under 3 materials (soil)
damping conditions; 2% damping, 5% damping and 10% damping are shown in Figure 4. It is
obvious that the greater soil damping will reduce the response acceleration more. The
response acceleration at 5% soil or material damping is generally used for earthquake resistantdesign consideration.

Figure 4: Spectral response spectra at some selected sites in studied townships
The maps of response accelerations for 1s and short period 0.2s were prepared based on the
response spectra at 5 % damping and are shown in Figure 5 and Figure 6.
One-dimensional seismic response analysis by equivalent linear method in Kyauktada, Pazundaungand Botahtaung Townships, Yangon, Myanmar

145

Figure 5: Map of response acceleration at 1s for Kyauktada, Pazudaung and Botahtaung
Townships
The response acceleration at 1s is ranging from 0.07g to 0.19g as shown in Figure 5 and it canbe regarded the acceleration is low at 1s. Relatively, higher acceleration (green to red) zones
are around the city hall in western part and the highest one (yellow to red zone) in southeastern part of the area. The purple colour zones represent the lower response acceleration at
1s.

Figure 6: Map of response acceleration at 0.2s for Kyauktada, Pazundaung and Botahtaung
Townships
The response acceleration at 0.2s ranges from 0.58g to 1.10g as shown in Figure 6 and mostof the areas are covered by higher acceleration. The various structures may response at higher
response acceleration in the areas (green, yellow and red zones) along Thein Phyu Road,
between Sule Pagoda Road and Lower Pazundaung Road and along the Merchant Road.

146

One-dimensional seismic response analysis by equivalent linear method in Kyauktada, Pazundaungand Botahtaung Townships, Yangon, Myanmar

December 2019, Yangon, Myanmar

6.2 Peak ground acceleration, PGA
Ground motions with high peak ground accelerations are usually, but not always, more
destructive than motions with lower peak accelerations. Very high peak accelerations that lastfor only a very short period of time may cause little damage to many types of structures(Kramer, 1996). The most commonly used measure of amplitude of a particular groundmotion is peak ground acceleration, PGA and it is the absolute value of horizontal
acceleration (Kramer, 1996). The PGA is always used to describe the ground motion becauseof its natural relationship to inertial force induced in certain types of structures (Kramer,
1996). The acceleration time histories of some selected sites are shown in Figure 7 and the
PGA map is shown in Figure 8.

Figure 7: Acceleration time histories at some selected sites in studied townships

Figure 8: PGA map of Kyauktada, Pazundaung and Botahtaung townships
As shown in Figure 8, the PGA values are ranging from 0.16g to 0.28g in the studied
townships. The red colour represents the highest PGA zones and the lowest PGA zones are in
purple colour. The highest PGA zones can be observed around city hall, along the sections ofMerchant Road, Mahavandula Road between Bo Aung Kyaw Road and Botahtaung Pagoda
Road. The stronger ground shaking can be expected in those higher PGA zones then lower
PGA zones.

One-dimensional seismic response analysis by equivalent linear method in Kyauktada, Pazundaungand Botahtaung Townships, Yangon, Myanmar

147

6.3 Peak ground velocity, PGV
The peak ground velocity (PGV) is another useful parameter for characterization of groundmotion amplitude. Since the velocity is less sensitive to the higher-frequency components ofthe ground motion, the PGV is more likely than the PGA to characterize ground motion
amplitude accurately at intermediate frequencies (Kramer, 1996). For structures or facilities
that are sensitive to loading in this intermediate-frequency range (tall or flexible buildings,
bridges, etc.), the PGV may provide a much more accurate indication of the potential fordamage than the PGA (Kramer, 1996). The following Figure 9 shows surface velocity time
histories of some selected sites in studied townships.

Figure 9: Velocity time histories at some selected sites in studied townships
The map of peak ground velocity (PGV) was prepared for studied townships based on thevelocity time histories of 84 sites as shown in Figure 10.

Figure 10: PGV map of Kyauktada, Pazundaung and Botahtaung townships
The PGV values are between 0.75 cm/s and 1.55 cm/s as shown in Figure 10 and the
distribution PGV values is similar to that of PGA values; the highest PGV zones are aroundcity hall, along the sections of Merchant Road, Mahavandula Road between Bo Aung Kyaw
Road and Botahtaung Pagoda Road. The relatively larger damage can be expected in higher
velocity zones than the other parts of the townships.

148

One-dimensional seismic response analysis by equivalent linear method in Kyauktada, Pazundaungand Botahtaung Townships, Yangon, Myanmar

December 2019, Yangon, Myanmar

7. CONCLUSION
Kyauktada, Pazundaung and Botahtaung are important townships of Yangon due to existenceof buildings with high historical and cultural values such as ministers’ Office and City Hall.
Although Yangon is located in moderate seismic prone region, the seismic risk can be quite
high because of its high population and substandard buildings. Therefore, 1D seismic
response analysis by equivalent linear method was carried out at 84 sites, using DYNEQ
computer code to support detailed hazard information for future seismic risk analysis.
The PGA, values are between 0.16g and 0.28g while the PGV values range from 0.75 cm/s to
1.55 cm/s. The PGA and PGV distribute similarly; the highest zones were observed aroundcity hall, along the sections of Merchant Road, Mahavandula Road between Bo Aung Kyaw
Road and Botahtaung Pagoda Road.
Most parts of three townships are covered by high spectral response acceleration at 0.2s andthe acceleration is relatively low at 1s. It can be regarded that the seismic risk of buildings in
the areas with high PGA, PGV and response acceleration will be relatively higher than thebuildings in other places.
REFERENCES
Google Earth Image, 2019. [Online]. Available: http://www.google.com/
Hirokawa, Y., Matsushima, S., Kawase, H., Naing, T., and Thant, M., 2016. Estimation of undergroundstructures in Yangon City, Myanmar using single-station and array microtremors, Proceedingof International Symposium on Earthquake Engineering, JAEE, Vol.1.
Kawase, H., Sánchez-Sesma, F. J. and Matsushima, S., 2011. Effects of Surface Geology on
Seismic Motion: The Optimal Use of Horizontal-To-Vertical Spectral Ratios of Earthquake
Motions for Velocity Inversions Based on Diffuse Field Theory for Plane Waves, Bulletin of
Seismological Society of America, Vol 101, pp 201-214.
Kramer, S. L., 1996. Geotechnical Earthquake Engineering, Prentice Hall, New Jersey.
Ministry of Immigration and Population, 2015. The Union Report: the 2014 Myanmar
Population and Housing Census, Census Report Volume 2.
Nakamura, Y., 1988. A method for dynamic characteristics estimation of surface layers using
microtremor on the surface, RTRI Report 4, 18-27.
Ohsaki, Y., 1979. Guideline for evaluation of basic design earthquake ground motions,
Appendix to Regulatory Guide for seismic Design of Nuclear Power Facilities, Japan.
Thinzar, S., Naing, T. and Latt, K. Z., 2018. Determination of Ground Motion Parameters by
1D Equivalent Linear Method in Botahtaung Township, Yangon, Myanmar, Proceedings of
9th International Conference on Science and Engineering, Yangon Technological University,
Yangon, Myanmar.
Tun, S. T., 2007. Tectonic Map of Myanmar and Surrounding Region, Myanmar Geosciences
Society, MGS.
Yoshida, N. and Suetomi, I., 2004. DYNEQ: A computer program for dynamic response
analysis of level ground by equivalent linear method,” version 3.25.

One-dimensional seismic response analysis by equivalent linear method in Kyauktada, Pazundaungand Botahtaung Townships, Yangon, Myanmar

149

OVERVIEW OF URBAN GROWTH AND YANKIN REDEVELOPMENTTOWARDS SUSTAINABLE LAND USE PLANNING IN YANGON

S.S.MOE1, T.G.SHWE2
1

Associate Professor, Department of Architecture, Yangon Technological University, Yangon, Myanmar,
2
Professor, Department of Architecture, Yangon Technological University, Yangon, Myanmar,

Keywords: Urban Growth, Urban Congestion, Sustainable Land Use Planning, Environmental Impact, Yankin
Redevelopment, Yangon.
1.
INTRODUCTION
Yankin is one of the most populated townships of inner
urban ring area in Yangon. Nowadays, it is rapidlychange to modern city by building with multistoried
high-rise buildings and it has been transforming to be acommercial hub of Yangon. Within its parameter some
important buildings are existed. These are Central BankFig (2.2) Number of household in townshipof Myanmar, Yangon Head Quarters (existed on
Fig, (2.3) Density Map
Industrial Road), CB Bank HQ (existed on Sayarsan
3.
CAUSE AND CONSEQUENCES
Road), Yoma Bank HQ, Ooredoo Telecom HQ in
Currently,
in Yangon development trends is going to
Myanmar Plaza (existed on Kabar Aye Pagoda Road),build
in
mixed-use
projects neglecting the inhabitants
Telenor HQ (existed on No 1. Industrial Road0,
behavior,
comfortandtraffic congestions are causing
Myanmar International School (existed on Maw Ya
lackof
properzoningplan
for long turn development.
Waddy Street), Yankin Children Hospital (existed on
Accordingtositelayoutandsynergy, using urban center
Kanbae Road). Urban facilities like international school,
withgroundfloor
retailfacingthe street residential
vocational training centers in the field of Health, IT and
and/orofficeonupperlevels.
These
may include one or
Finance among other education and training are grouping
multiple
blocks.
Eachdeveloper
must
normally stand oneach other. So, Yankin Land use is tremendously
its
own
experiences
based
on
area
market demand.
changed to second CBD of Yangon (central business
Traffic
impactisthemajor
factorof
YangonCity. Future
distrait). This condition is that all the elements need to
mixed
use
development
projects
shouldbestudy anddevelop the next generation of Entrepreneurs and leader
accesstrip
generation
and
by
using
sharedparking,of Myanmar. These urban facilities are offices which
consideringinternaltrip
capture,site
layoutandwalking
include Grade A office buildings for the multinationals
distances.
and SOHO (Small Office Home Office) for4.
CONCLUSION
entrepreneurs and Shared office for the startups and IT
Thereisa clear conclusion arising from this study thatmall among other malls to be invited for entrepreneurs
point
towards
the development of idea for land use
who are starting business using information technology.
potentialinYangon.
Yangon is one of the mostBeside that hotels, condominium, exhibition andimportantcommercial
centers
and city has also grownconference center to be included.
rapidly in recent years. Unplanned and rapid
2.
POPULATION, POPULATION GROWTH
urbanization increase population as well as number of
AND HOUSEHOLD
vehicles, poor traffic management and poor road
According to the census record in 2014, there are 14,637
condition. Shopping malls or shopping centers arehouseholds in Yankin township and population is about
nowadays arising to build in Junction area and near
70,946 persons, including in promotion of male 32,724
junction area. In this study some land use changed
persons and female 38,222 persons. Male to female ratio
development projects are made a case studies and detailis approximately 1:1.2. In figure 2.1 shows the increasing
analysis are going upon them. However, it is clear fromof population from 2015 to 2017. Fig 2.2 shows thethe information in this conclusion that the primary uses
population and Number of households in each ward. Fig
today and foreseeable mixed use developments are retail,2.3 shows the population per square mile in each ward.
restaurant, residential and office. Available resource
should be concentrated on those uses, but any procedures
developed should be adaptable to all common land uses.
According to this some area should be controlled. Someshould be promoted and some should be freeze.
REFERENCES

Fig (2.1) Growth rate of population in township
Fig (2.2) Number of population in township150[1]San San Moe, “The Current Trends of Urban Development inYangon City and Its Implication on the Environment” GMSARN
International Online Journal Vol-3/ No.4, March, 2010 pg. 40-49(www.gmsarn.org)[2]Yangon City Development Committee. 2016. Yangon City
Comprehensive Land Use, Zoning and Urban Design Review Working
Committee.

ESTIMATION OF SITE AMPLIFICATION FACTOR IN YANGON CITY
Takumi MATSUMOTO1, Takaaki IKEDA2, Hideomi GOKON3, Atsuya MINAGAWA4TUN NAING5, and Osamu MURAO6
Graduate student , Civil and Environmental Engineering, Nagaoka University of Technology, Niigata, Japan,
2
Professor, Civil and Environmental Engineering, Nagaoka University of Technology, Niigata, Japan,
3
Associate professor, Knowledge Management, Japan Advanced Institute of Science and Technology, Ishikawa, Japan,
4
Graduate student , Civil and Environmental Engineering, Nagaoka University of Technology, Niigata, Japan,
5
Professor, Engineering Geology, Yangon Technological University, Yangon, Myanmar,
6
Professor, International Research Institute of Disaster Science, Tohoku University, Miyagi, Japan,
Correspond to Matsumoto (s163310@stn.nagaokaut.ac.jp)
1

Keywords: site amplification factor, vulnerability evaluation, microtremor, H/V spectral ratio,soil classification
1. BACK GROUND
Our research focuses on seismic risk assessment inYangon, Myanmar. There is plate boundary around
Myanmar, and the Sagaing fault runs in the central part,so the earthquake risk is very high. The ground motion due
to an earthquake may cause greatly damage. In this study,
for the purpose of seismic vulnerability evaluation of
surface ground, we estimated the site amplification factor(ARV) based on average shear wave velocity in Yangon.
2. ESTIMATION MEATHOD OF ARV
The target area was 568 wards of Yangon, and the ARV
was estimated from three methods. Fig.1 shows the site
amplification factor of each ward determined from theestimated values of three methods. Each estimation
method is explained below. The accuracy of ARV was
improved by estimating it in order of 1), 2) and 3).
1) Simplified Method
In Tokyo, 12 types of soil classification are definedfrom geomorphologic and geologic characteristics, and
the ARV of peak ground velocity is determined for eachsoil classification[1]. In this study, the soil classification of
Yangon was determined based on it of Tokyo, and the
ARV was simply estimated. Yangon was classified into 4categories from geoinformation. Tab.1 shows the soil
classification and characteristics of Yangon.
Table 1. The soil classification and characteristics of
Yangon based on it of Tokyo
Classification
ARV
Characteristic
Plateau 1
1.6
Diluvium, Gravel
Plateau 2
1.7
Diluvium, Clay
Valle-plain 2
1.8
Sediment, Soft layer 3-8m
Alluvial plain 2 2.3
Alluvium, Soft layer 0-10m2) Microtremor measurement
The ARV shows strong correlation with the shear wave
velocity[3]. Therefore, this study estimated the ARV using
the formula with the average shear wave velocity as theparameter (Eq. (1)) proposed by Matsuoka andMidorikawa (1994).
log 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = 1.83 − 0.66 log 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴(1)

The average shear wave velocity was calculated from thepredominant frequency of surface ground estimated by the
H/V spectral ratio of microtremor. Microtremor
measurement was conducted at 140 sites at intervals of
about 2 km.
3) Boring data
The average shear wave velocity was calculated fromboring data in Yangon, and the ARV was estimated by
Eq.(1). The ground with N-Value less than 50 was
regarded as surface ground, the predominant frequency of
surface ground was calculated based on N-Value.
Figure 1. Site amplification factor of Yangon

3. CONCLUSION
The accuracy of the estimation was improved bycomparing the results of each method. By using
microtremor measurement and boring data, the ARV
reflecting the predominant frequency and ground structure
at each site was indicated.
REFERENCES[1] Maruyama, Y., Fushioka, S., Yamazaki, F., Evaluationof Site Amplification in the Survey of District-based
Vulnerability to Earthquake Disaster Performed by Tokyo
Metropolitan Government, Institute of Social Safety
Science, No.16, 2012[2] Nakamura, Y., Basic Sturacture of the H/V Spectral
Ratio, The Society of Exploration geophysicists of Japan,
2008[3] Midorikawa, S., Matsuoka, M., Sakugawa, K., SITE
EFFECTS ON
STRONG-MOTION RECORDSOBSERVED DURING THE 1987 CHIBA-KEN-TOHOOKI, JAPAN EARTHQUAKE, japan Association for
Earthquake Engineering, No.9, 1994

151

STUDY ON AMPLIFICATION FACTOR OF MAXIMUM ACCELERATIONFOR SEISMIC HAZARD ASSESSMENT
Atsuya MINAGAWA1, Takaaki IKEDA2, Hideomi GOKON3, Takumi MATSUMOTO4, and Tun NAING5
Graduate student, Nagaoka University of Technology, Japan,
2
Professor, Nagaoka University of Technology, Japan,
3
Associate Professor, Japan Advanced Institute of Science and Technology, Japan,
4
Graduate student, Nagaoka University of Technology, Japan,
5
Professor, Yangon Technological University, Myanmar,
1

Keywords: Vulnerability assessment, Maximum acceleration, Maximum velocity, Hazard map

2. METHODS
2.1 Methodology
First, the acceleration and velocity amplification factors
are obtained using the vertical array observation records
where seismometers are installed on the base and theground surface. However, since there is no vertical array
seismic observation in Yangon City, we use the records ofvertical array observations in Japan.
Since the amplification factor is affected by the groundmotion level, multiple seismic records with different
ground motion levels are used. The velocity time history
waveform is calculated by integrating the acceleration
time history waveform1).
2.2 Calculation of amplification factor and relational
expression
It was found that the geological condition is mainly sandand clay by the geologic columnar section of Yangon, andthe surface layer is a very soft ground with a surface N
value of 50 to 25m and 45m. Figure-1 shows a geologic
columnar section of Yangon. Therefore, the measurement
points similar to the geological condition of Yangon was
selected from the geological condition and S-wave
velocity of the geologic columnar section using the strong
motion data of the strong motion observation network(KiK-net2)) in Japan.
KiK-net has about 700 observation facilities nationwide,and each observation facility has an observation well.

152

Figure-1 The geologic columnar section of Yangon
12

The amplification factor of the
maximum velocity

1. INSTRCUTION
Our research focuses on the evaluation of amplification
characteristics for earthquake risk assessment in Yangon
city, Myanmar. The earthquake risk is very high because
there is the Sagaing fault longitudinally cutting in central
Myanmar, and a plate boundary in the vicinity of thiscountry. The amplification characteristics of the groundare evaluated using topography classification, soil profile,
microtremor and so on. It is possible that the groundsurface shake greatly affects the damage caused by theearthquake. The amplification characteristic of the groundin our research has been mainly the evaluation of the
maximum velocity in the surface ground. In this study, it
is aimed to evaluate the amplification characteristics ofmaximum acceleration and to investigate the effectivenessof earthquake risk control in Yangon.

108

y = 0.5321x + 2.9704

6
4
2
0

0

2

4

6

8

10

The amplification factor of the maximum acceleration

Figure-2 the relationship of amplification factor
Strong-motion seismometers are installed on both thesurface and underground. The selected locations were
AICH06 which observed maximum accelerations of 5.2,
5.3, and 5.6 gal, and AICH09 which observed 5.0, 5.2, and5.2 gal, and AKYH17 which observed 5.0 gal three times.
3. RESULTS
Figure 2 shows the amplification factor of maximum
acceleration on the horizontal axis and the amplification
factor of maximum velocity on the vertical axis, andshows the relationship linearly. At the present stage, there
are only 18 measurements, but it can be inferred that there
are correlations between them.
4. CONCLUSIONS
Although the calculation of amplification factor in thisresearch is not a method to carry out in detail, it isnecessary to investigate as a new evaluation object of theamplification characteristic of the future ground using therelationship between both of them. The plan is to expand
the usefulness of research on amplification characteristics
in Yangon.
REFERENCES[1] Kazuyuki IZUNO, Ritsumeikan University,"Integral.xlsm" program for integrating the acceleration
waveform in the frequency domain (2015)[2] National Research Institute for Earth Science andDisaster Resilience (2019), KiK-net, National ResearchInstitute for Earth Science and Disaster ResilienceDeveloping Evacuation Areas in Yangon for
Emergency Response with GIS system
Ms. Eiei TUN1, Ms. Tintin AYE2
DR. Takaki KATO3 and Ms. Tomoko MATSUSHITA4
1

Student, Satreps Group of Urban Planning,

Department of Architecture, Yangon Technological University, Yangoneiei.cocci@gmail.com
ABSTRACT
Yangon is facing fire disaster as highest risk and evacuation areas will become major issues
to provide in new planning. Currently, there is no usage of green spaces as evacuation areasin Yangon. The objective of having an evacuation area includes quickly and safely moving
population away from the danger zone into shelters to reach in time by the shortest way, toallocate disaster prevention evacuation areas depending on population density. The minimum
standard of evacuation areas for each ward will be produced as a hypothesis of the study. The
evacuation service areas analysis will reveal the lack of green spaces in each ward and also
define suitable locations with a focus on emergency safe and accessibility as one of thedisaster facilities of green spaces. Network analysis through GIS, evacuation service areas,
recommended evacuation routes, and risk level can be determined based on risk level andhuman's walking speed. The questionnaire surveys of government offices which performmainly in reducing disaster risks will enhance for accurate outcomes. The output indicates thevulnerable areas of Yangon, introduction of green areas as emergency shelters andenhancement of emergency modified evacuation methods to increase resilience in city
planning.
Keywords: Risk assessment, Emergency response, Evacuation Service Areas, Geographic
Information System, Evacuation Routes.
Introduction
Myanmar, also known as Burma, is one of the developing countries in Southeast Asiawith the population density of 56 million. The rapid growth of urbanization has been
occurred in Yangon when reviewing last 10 years to until now. Yangon has been experienced
changes of land utilization over 60 years after colonial period. The growth in population andphysical assets in hazard-prone areas, lack of basic infrastructure and access to affordable
land, extreme poverty and substandard structures of buildings increases the vulnerabilities of
the urban population. Moreover, there is important need to include emergency evacuation
areas in new town planning. Currently, the green area per person of Yangon is 0.37 square
meter per person according to JICA study and it is noticeable minimum when compared toother developing countries. The important factor is the rule and regulation on urban planning.
Most of the urban planners predicted that Yangon may become mega city in 2040. The

153

integrated guideline and recommendations will be new evaluation and changing of integrated
town planning.
The first step towards the urban resilience planning is to ensure that affected people
are evacuated in a short time to safe assembly points and shelters during the disasters. To
ensure an efficient disaster management, the shelter locations should be strategicallyallocated within minimum evacuation distance and time. The increased recognition of green
and open spaces is one of the strategies to the urban expansion characteristics. The open space
network makes contribution to urban resilience.
Literature Review and Study Framework
Planning emergency shelters in advance is an effective approach to mitigate the damage
caused by natural disasters.
Pre-identification of suitable shelter to be used in evacuations
This section should plan for the pre-identification of suitable accommodation forevacuees within the safety zone. Shelter provides for the temporary accommodation ofevacuees. It provides the basic personal needs which arise at an individual level during an
emergency. Identification of appropriate shelter areas should be based on safety, availabilityof facilities, accessibility, capacity, and numbers of persons. Location will depend on the typeand severity of the hazard, as well as potential secondary hazards. According to particularsituations and contexts, new levels and types of risk may quickly emerge requiring
evacuation to new areas due to secondary hazards such as fire following earthquakes. Sites
should be identified in the planning stages. Issues in the use of public facilities, such as
schools, must be considered when identifying potential evacuation centers. This will include
analyses of the potential negative impacts of the use of public facilities on host communities.
Emergency Response Preparedness System of Myanmar
The Humanitarian Country Team (HCT) of Myanmar drafted and regularly updated
an Inter-Agency Contingency Plan (IACP). The IACP was designed to support theGovernment of the Union of Myanmar in preparing for, and responding to, any of the hazards
that may affect Myanmar. In 2014, the HCT decided to apply the new guidance for InterAgency Response Preparedness (ERP) as an action-oriented approach to enhance readinessfor humanitarian response. This methodology replaces the previous IACP. The ERP approachseeks to improve effectiveness by reducing both time and effort, enhancing predictability
through establishing predefined roles, responsibilities and coordination mechanisms. The
Emergency Response Preparedness Plan (ERPP) has four components which have similarities
with the previous IACP: i) Risk Assessment and Monitoring, ii) Minimum Preparedness
Actions, iii) Contingency Response Planning, and iv) Standard Operating Procedures for theInitial emergency response.
The overall goal is to mitigate the impact of disasters and save as many lives as
possible from preventable causes. [8]Current Conditions of emergency evacuation system of Yangon
The survey is extracted through the discussions with the government officers whoplay mainly in the disaster management cycle. The Government offices include urban
planning group of Yangon City Development Committee, Ministry of Social Welfare, Relief

154

and Resettlement, and Myanmar Red Cross Society. The major aim is to improve theemergency evacuation system as a response for disaster management. The survey iscomposed with main 11 questions to reveal the current emergency response system of
Yangon.
Firstly, the action plan is effected and losses time, livelihood and infrastructuredevelopment for post disaster emergency responses. YCDC has to coordinate with otherrelevant ministry and public official for rehabilitation services. The contingency Plan of
Myanmar aim for multi hazards such as earthquakes, storms, flooding and etc. Types ofdisasters are classified from small to large scale. The Disaster risk management system
includes responses for basic facilities such as food, wastes and relief goods. The evacuation
teams need support with equipment for rescue and research. The major contribution of foodsupply and basic utility will serve for the evacuees. Non- food items such as sanitary (washkit) for 10,000 people store for disaster preparedness. Total warehouses of both governmentand of NGOs are totally around 30 numbers in Yangon. Starting from 2015, priority needs for
emergency evacuees target for 22,000 residents per year in MRCS. Each warehouse of therelief and resettlement has emergency food for minimum 150 to 300 people normally. For
non-food items, each warehouse contains 10,000 people. In each evacuation team, theequipment include Telephone, Based VHF Machine, Radio with battery, camera, carry box,
advanced first aid kits, T-shirt, cap, back pack, touch, calculator, notebook and pen, VHF
Icon, Life Jacket, Rain coat and sleeping bag. During 2011-2014, MRCS have already trained
712 volunteer by 25 team trainings in different states and region in Myanmar. YCDC takes
emergency preparedness by serving duties and responsibilities of drainages, collecting
garbage, checking the building resistance, etc.
Secondly, project areas include non-structural, structural, small-scale disaster risks
reduction, health care and early warning system under MRCS. A national disaster response
team has been set up by the Myanmar Red Cross society in the country that will be able togive immediate attention and assistance to emergencies and disasters in the country. Major
response preparedness is to understand disaster management and awareness, simulation anddrill.. It also includes Disaster risk reduction, preparedness for safe public facilities andshelter. Contingency plan as major response preparedness should include temporary shelter
such as schools, monasteries and open spaces such as football field for each township. The
minimum requirements of each temporary shelter need to analyze and provide for theinternational standard of shelter requirements in future. Depending upon the townshipdisaster management committee, MRCS, YCDC and community leaders including theresidents, the most vulnerable areas are evolved. The suitable locations for temporary
emergency evacuation are based on the township population and township risks level.
Mostly, the evacuees keep at the religion building, temporary shelters, schools and stadiums
and their relationship resident. Besides, undergraduate schools serve as evacuation areas and
MRCS can support basic facilities of children mainly and the aids to be use as evacuation
shelter. The affected people usually get Diarrhea, dengue, respiratory tract infection are
diseases after disasters. The participants were trained on how to manage disasters andemergency situations and also to equip them with the right skills on how to deal with diseases
like Malaria, Cholera, Ebola, Yellow Fever and other epidermal related diseases.
Thridly, the missing of the affected people is usually facing when making evacuation
during disasters. Besides, transportation such as the direction of exit way, how to go and run
to shelter to reach safely, how to stay and which places can be saved for their live, etc., andFinancial difficulties are the difficulties for the evacuation team. Besides, home ownership155

becomes major problem when providing the shelters and also the basic facility during
disaster. After disaster, the difficulties become the camp management, contributed relief
goods to disaster affected people, health and nutrition of refugee, resettlement after disaster.
Between the government offices and NGO, the cooperation and coordination, define duties
and responsibilities, time-frame, budget become major tasks for resettlement. When they
make evacuation for relocation the affected people, the organization usually face the scarceland for relocation the evacuees. There is no special evacuation place in Yangon.
Thirdly, the renovation of infrastructure, resettlement, employment opportunity,
mental secure, etc., become the important tasks to carry after the disasters. Emergency
facilities such as medicals, evacuation places, hospitals, and search and rescue equipment
become essentially need to reduce the disaster risks. The above results reflect the current
emergency evacuation process of Yangon. Nearly all of the organizations express the wholeprocess of disaster management cycle from their current position. According to the survey,
the lack of planning leads to scattered processes. Therefore, the integrated emergency
evacuation management plan should be developed. Additionally, the ongoing process should
be taken from the determination from several coordination workshops.
MethodThe author would like to study the township level as a typical one by using thecapacity constraints and accessibility constraints to reduce the disaster risks level. The spatial
analysis using database link with Geological Information System (GIS) will utilize tohighlight vulnerable areas of township. The study was based on township report and 2014
Housing Census. The next section provides our results and discussion. The paper concludes
with a summary of the results showing that vulnerability townships areas for emergency
evacuation.
The framework and processes of analysis in the present research are as shown below.
1) Calculation the coverage areas within 1km from centroids of each ward. A map
produces the area in square-meter per person to know the coverage amount ofevacuees in shelters.
2) Calculation of the linear distance between each ward and each emergency shelter
The linear distance between the center of each ward and each emergency shelter will
be calculated by using the normal people walking rate at 4km.
Basic Data Sets Used
Background Data
The South Dagon Township is located with the Dagon Seikkan Township on the East
side, Hle-gu on the north, Tharkata and Thingangyun Townships on the south and North andEast Dagon Myottit Townships on the west. The study area is located along the No (2) Main
Road. The major roads of Pyi Htaung Su and Kyan Sit Thar Road are connectedneighborhood townships. The railroad is passed through 26 ward and 22 ward within thetownship.
Green and Open Spaces Locations
The data of existing green areas including parks, playgrounds and green area aresupported by Yangon City Development Committee (YCDC) and places of worships are
extracted from JICA Study of 2012. The facility and the attributes of the existing data set are156the major keys for analysis. The total 68 number of parks and playgrounds are undercontrolled by Yangon City Development Committee (YCDC) as public ownership. The
existing places of worships will also be used as potential shelters for evacuation according to
the questionnaire survey. The total 93 numbers of places of worships exist inside the South
Dagon Myotthit Township. The locations will be analyzed to find out the shelter coveragearea per person. In the immediate aftermath of a disaster, particularly in extreme climaticconditions where shelter materials are not readily available, coverage area less than 3.5
square meter per person become appropriate to save life and to provide adequate short-term
shelter to the greatest number of people in need. In such instances, the shelter response
should be designed to reach 3.5sq.meter per person as possible, as longer durations may
begin to affect the health and well-being of the people accommodated. [2] [6]Response Capacity Evaluation
The distribution of emergency shelters will be displayed on the digital map by using
GIS tool. In the present research, the places of worships as emergency shelters are newly
added to emergency shelters. The places of worships were utilized as emergency shelters in
the past disasters. For a shelter to meet the basic facility, the number of people in a shelter
should not exceed the shelter's maximum capacity. There are two kinds of analysis for theevacuation coverage area.
For the first one, a proximity feature (emergency shelters) that is within 1km from
centroid of each ward is selected and 'n' value (the total number of evacuation shelter within
1km) is obtained. For each ward, the n value will be the average of the number of emergency
shelters within 1km.The 1km is a standard of the human walking distance. Following thesame series, the population within 1 km from centroids of each ward will be produced. The
results of total emergency shelters will be divided by the total population. The result willshow the vulnerable wards which lack evacuation areas.
For the second, the 1km rings from the centroids of green areas including parks,
playgrounds and places of worships will be produced. These intend to know the capacity ofeach emergency shelters which can hold during disasters. According to the above twoanalysis, the minimum capacity of evacuation areas will be produced as responses of
emergency disaster risks management.
Response Coverage Evaluation
In the present research, the linear distance between each district and each emergency
shelter will be calculated by using a tool of GIS. The residential data is extracted from the2012 JICA study. The data identify a total of 6097 residential communities.
There are two types of road generally: major and minor. The counted roads are
2 lanes and above. The origin destinations (OD Cost Matrix) analysis of parks, playgrounds
and green areas has done using the velocity equation. The standard human walking rate of 30
mile per hour is using to produce the minimum time taken for the evacuation. The OD cost
matrix analysis, using the tool of GIS; a proximity feature of emergency shelter as destination
analyzed with centroids of each household as origins and show the shelter demand.
Results and Discussions
For the analysis of evacuation areas for South Dagon Myotthit Township, the existing ofgreen areas and places of worships in each ward are taking into account as first. The results157

show that about 50 percent of the total wards of green areas lack in evacuation areas for theevacuees. And, there are two wards which lack the place of places of worships. This study
will show in the fig a and b as below.
The response capacity analysis shows that the green area and places of worships area
per person in each ward. According to the figures of c and d, the results show the emergency
evacuation area per person. The maximum evacuation area per person of green spaces is10.814 sqm for No.25 ward and the minimum is 6.431sqm for No.26 ward. For the places ofworships, the maximum is 34.77 sqm in Ywar Thar Gyi ward and minimum one is 10.22 in
Nol.66 ward. The total coverage wards for green and places of worships are ward No.26(6.431sqm), No.25 (21.144sqm), No.66 (10.22sqm), No.63 (13.67sqm), No.57 (17.71sqm)
and Ywar Thar Gyi Ward (48.43sqm). The red circle shows the wards where coverage area isbetween 0 to 5sqm. About 50 percent of the total wards lack in evacuation areas for theevacuees. But , there are only two wards which lack the place of places of worships.

Fig.a and b show the existing green areas and places of worships in South Dagon Myotthit Township.

Fig.c and d show the coverage area density of green area and places of worship per person in South Dagon Myotthit Township

158

The Accessibility Analysis for the Emergency Evacuation Response
The accessibility analysis states that people cannot arrive to evacuation areas within
10 minutes and only 30 minutes may be coverage to be safety. The first 10 minute show thatfew residents can arrive to evacuation areas. In order to avoid the chaos situations at theevacuation stage, the route capacity should have the sufficient wide for the refugees to pass.
Smaller capacity than the required ones becomes a high risk of evacuation route, because it
will delay the evacuation clearing time and it may produce greater chaotic conditions.
Currently, the roads of South Dagon have not standard width for fire fighters. Most
residential houses located at the lower level of ground and do not have platform to walk.

Fig.a show coverage area of green areas in South Dagon Myotthit Township.

Fig.b show coverage area of places of worships in South Dagon Myotthit Township.

Discussion and Conclusion
On the basis of the present analysis, the authors would like to recommend that eachward within the townships should have coverage within 7 to 15 minutes. Result indicated thatmost residents in South Dagon Myotthit Township have not been covered by evacuation
places yet. Blocking main roads was resulting in the deduting of covered evacuation coverage
area.

159

However, the suitable evacuation should be allocated within the limited time as further
research. The promotion of facilities of green evacuation areas will be promoted from thedangerous diseases. The research for the time varying shelter demand analysis to a locationallocation model for emergency management will be proceed with further research.
REFERENCES[1] Open Space Suitability Analysis for Emergency Shelter after an earthquake By J. Anhorn and B. Khazai[2] Yangon Region, Eastern District Dagon Myothit (South) Township Report[3] Sendai Framework for Disaster Risks Reduction 2015 – 2030
[4] Study on Green and open spaces as emergency shelters by Dr. Yasmin Bachattara, Tokyo University[5] 2014 Myanmar Population and Housing Census[6] Yangon Master Plan JICA 2012[7]Planning Emergency Shelter for Urban Disaster Resilience: An Integrated Location-allocation ModelingApproach, Laijun Zhao, Huiyoung Li, Yan Sun, Rongbing Huang, Qingmi Hu, Jiajia Wang and Fei Gao[8] Emergency Response Preparedness Plan, Myanmar (version 1.0, updated in June 2014)[9] Determining Evacuation Service Areas and Evacuation Route Risk Level as Disaster Mitigation Plan using
GIS – based Software in Hyuga, Japan[10] Mulit Hazard Contigency Plan , Myanmar Red Cross Society

160

A STUDY OF EVACUATION RISK IN THE CENTRAL BUSINESS DISTRICT OF YANGON CITY
AND DISCUSSION ON THE ROLE OF BACK DRAINAGE SPACE
T. MATSUSHITA1, A. KUBOTA2, and K. MEGURO3
Project Researcher, International Center for Urban Safety Engineering, Institute of Industrial Science, the University ofTokyo, Japan, matsu-t@iis-u-tokyo.ac.jp (corresponding author)
2
Project Professor, Department of Urban Planning, the University of Tokyo, Japan, ak@td.t.u-tokyo.ac.jp
3
Professor & Director, International Center for Urban safety Engineering, Institute of Industrial Science, the Universityof Tokyo, Japan, meguro@iis.u-tokyo.ac.jp
1

Keywords: Back Drainage Space, Yangon, evacuation risk
1. BACKGROUND AND OBJECTIVE
This study focuses on the role of a unique urban spacecalled Back Drainage Space (BDS), a 15-foot wide backalley with surface drainage and underground sewage
facilities which was built behind buildings to provide
sufficient light and air to keep the city sanitary and protect
it from flood and fire. It was implemented by the British
during the colonial period and in the early days, the space
was not only used as drainage space but it served as asocial space for the residents. However, starting in the
1980s, BDS became cluttered with garbage. Today there
are 182 BDSs in the Central Business District (CBD) of
Yangon, but they have been underutilized for nearly three
decades. From 2011-2015, Myanmar went through aseries of political reforms towards democratic government
and as a part of the transformation, Yangon City
Development Committee (YCDC) decided to improve the
BDS environment. A large scale cleaning and repairing of
the BDS started in 2015 (Figure 1). In 2017, a social
enterprise called Doh Eain initiated a project called Alley
Garden Project (AGP) to improve BDS and promote its
use as a space for the community. As a result, eight BDSs
have been transformed via collaboration between thecommunity and the government by 2019. Impact study
was carried out by the authors and the result has indicatedthat the use of the BDS has increased and people’s
perception of it has been improved [1].
2. PROBLEM STATEMENT
Despite the positive effects and prospects of BDS
brought by the project, a majority of BDSs remain
underutilized. Based on the previous studies conducted by
the authors, three reasons why BDSs have not beenutilized are that 1) the spaces have been filled withgarbage and/or privatized and difficult to manage among
the residents; 2) physical access from a building or street
to BDS is limited due to a lack of staircase and locked
gates prescribed by law; and 3) the use of BDS is
prohibited by YCDC law [2]. However, the city accepts
the use of some BDSs transformed by AGP because it isfor a “public good” and its usefulness is recognized. The
authors consider BDSs as significant assets as they have apotential to become shared urban space in the CBD wherevery little open space for the people exists. But in orderfor the BDS to be used as shared urban space, abovementioned issues need to be resolved and a sustainable

management system needs to be developed. This study
focuses on a physical aspect of accessibility as it can posea serious risk in the case of disaster if no appropriate
evacuation scheme is in place, especially since the CBD
is the oldest and most densely populated commercial
center in Yangon. The authors conducted surveys to grasp
the actual condition to identify issues and discuss possible
resolutions in relation to the role of BDS.
3. SURVEY METHOD
A field survey was conducted to check structural andnon-structural conditions related to accessibility, bothfrom a building to BDS and BDS to a street in February
2019. Total of 115 BDSs in 4 townships (TS) in CBD,
namely Lanmadaw TS (LMTS), Latha TS (LTTS),
Pabedan TS (PBTS) and Kyauktada TS (KTTS) where
BDSs are concentrated were surveyed. 88 out of 115
BDSs are “full-length BDSs” described in item no.5 inTable 1 meaning they have a full block length of 820 ft.
The results from these 88 BDSs were used to calculate
values represented in item no.6 to 10. It should be notedthat the survey was conducted using methods available tothe authors thus the values were obtained from different
sources and assembled for this analysis. The number ofaccess points (staircases and ladders) were obtained
through visual surveys conducted by the authors, whichwere difficult at times due to inaccessibility of some of the
BDS, while the building data including the number ofbuildings, usage and floor numbers were acquired fromdataset created by JICA project [3].
4. FINDINGSFor an access from building to BDS, three typicalconfigurations are observed; 1) steel staircase built in an
alcove, 3) steel ladder attached on a wall surface andFigure 1: Transformation of BDS (from left: BDS as asocial space (photo by Yangon Heritage Trust), BDS as T
rash Alley, BDS clean-up effort by the city, BDS transfor
med through Alley Garden Project (photo by Doh Eain)

161

Table 1: Existing condition of BDS in 4 Townships
1.Township (TS)2.No. of conventional HH / TS*1
3.Total no. of surveyed wards*2
4.Total no. of BDS surveyed / TS
5.No. of “full-length” BDSs / TS
6.Average no. of buildings / BDS
7.Average no. of staircase / BDS
8.Average no. of ladders / BDS
9.Average no. of access / BDS
10.% of accessibility to BDS / TS11.% of residential use building*3
12.% of building 1-4F
13.% of building 5F+
14. Average no. of exit to street
15. % of BDS w/ N-S exit

LMTS

LTTS

PBTS

KTTS

6978
7
33
18
50
12
6
18
36%
88%
51%
48%
4.4
90%

4292
9
23
21
42
10
3
13
31%
87%
58%
41%
2.6
0%

6563
11
29
24
34
7
0
7
21%
81%
63%
36%
2.4
0%

6120
9
30
25
28
9
2
11
37%
74%
69%
30%
2.4
5%

“Conventional household (HH) includes “one or more
persons who are either related or unrelated and share living
quarters and meals” according to 2014 Census [4];*2 Authors surveyed wards with BDS only;*3 This includes four categories of residential buildings that are
residential-detached house, residential-apartment, residentialmixed apartment, and residential–mixed detached house.
*1

Figure 2: Typical conditions of access points (from left:
deteriorated staircase in alcove; ladder attached to the wall
surface; concrete staircase locked with steel fence)staircase made of concrete (Figure 2). The survey findings
are summarized in Table 1 which shows that on average,
9.5 staircases and 2.8 ladders were observed as accesspoints per BDS, where the average number of buildings
facing BDS turned out to be 38.5. In all, on average, 12
points of access from 39 buildings to the BDS wereobserved, which means 31.3% of buildings facing the
BDS have a second means of egress. However, thecondition of most of these access points are neither in use
nor in a state of being used safely due to severe
deterioration and a lack of proper maintenance. Some of
the residents are privatizing the alcove as their storage
which disturbs the path. Steel staircase and ladder areoften rusted and broken while new staircase made ofconcrete seems sturdier but often enclosed and lockedwith steel fences on the ground floor for a security reason.
For an access from BDS to a street, there are 6 exit
points at maximum, 2 at longitudinal, N-S direction and 4
at cross sectional, E-W direction. 90% of BDS in LMTS
had N-S exits while only 0-5% for other 3 TSs. On average,
LMTS had nearly double the number of exit points (4.4)
compared to other 3 TSs (2.4~2.6).
With respect to the differences observed between TSs,
PBTS had lowest accessibility rate (AR) of 21% among
4 TSs. On the contrary, LMTS had a high AR (36%) anda largest number of buildings per BDS (50 buildings),
while KTTS also had high ARC (37%), but with asmallest number of buildings (28) per BDS. Likewise,

162

LMTS had a higher ratio of the residential use (88%) andlarger number of buildings with 5-stories and more (48%),
while KTTS had a lower ratio of residential use (74%)
and smaller number of buildings with 5-stories and more(30%). Thus it can be said that two TSs - LMTS which ismore residential, dense, taller neighborhood and KTTS
which has lower buildings with wider frontage –had highAR despite of their contrasting characteristics. Thesefindings are insufficient to conclude whether or not there
is a correlation between AR and other characteristics ofthe built environment and further investigation is needed.
4. ANALYSIS & DISCUSSION
According to the authors’ previous studies [1], threechallenges concerning the improvement of theaccessibility are 1) physical difficulty to create space for
installing new staircase, 2) financial difficulty and 3)
managerial difficulty in consensus building among multiunit owners of a building. This study attempted to verify
the actual condition by finding facts about staircase andexit points of evacuation and comparing between TSs.
And it was found that although 31.3% of buildings havea second means of egress, the majority of them are
unusable because of neglect and privatization by theresidents. This may be due to a lack of incentive for the
residents to commit to the BDS environment because thelaw does not allow its use and in reality, they can survive
without using it. Nonetheless, as stated earlier, BDS canbecome shared urban space to benefit the city and theresidents’ safety also depends on its usability in the caseof disaster. In order to create an incentive, it is importantthat the BDS becomes a legally usable space which has
been demonstrated by AGP. If the BDS can be used as anamenity space, it will increase a utility value and may
incentivize the residents to use the space and eventually
improve the environment including the accessibility.
Therefore it can be concluded that the usability of the
BDS is a critical factor in creating a safe urban
environment and the improvement of the BDS
environment and its accessibility need to be studied inparallel.
ACKNOWLEDGEMENT
We would like to thank the residents, local authorities
and volunteers for their cooperation in this study. The fieldstudy was made possible by the opportunity provided by
SATREPS program supported by JICA and JST.
REFERENCES[1] Matsushita, T. et al., “Impact Evaluation of Alley
Revitalization Project in Yangon and Investigation of
Potential as Urban Commons,” Great Asian Streets,
National University of Singapore, December 14-16, 2018.
[2] YCDC “YCDC Law” Chapter 29, No. 315, 2018[3] Yangon Regional Government, YCDC, “Yangon
Mapping Project,” 2019.
[4] Department of Population, Ministry of Immigration
and Population, “The 2014 Myanmar Population andHousing Census,” May 2015.

SESSION EURBAN SAFETY & DISASTER MITIGATION: RISK ASSESSMENTLONG TERM MEASURES FOR EARTHQUAKE DISASTER SAFETY IN
DEVELOPING COUNTRIES OF ASIA
PRADEEP KUMAR RAMANCHARLA1
1

Professor, EERC, IIIT Hyderabad, India
ramancharla@iiit.ac.in

Keywords: Earthquake safety, Risk Index, Vulnerability, Mitigation
1. ABSTRACT
Due to rapid urbanization in many cities in the world,in last few decades, there is a tremendous pressure on
housing industry to cater to the needs. This fast pace ofconstruction activity with no planning has led to unevengrowth of low-to-medium rise buildings in tier II cities
and medium-to-highrise buildings in tier I cities, causing
serious threat to life and property during disasters. The
same is clearly evident from the losses during earthquakes
in the recent past including twin major earthquakes in
Nepal. Therefore, it is necessary to carry out Long term
mitigation measures for Earthquake Disaster safety.
Earthquake Disaster Management has 6 stages, namely,
prediction,
mitigation,
preparedness,recovery,rehabilitation and reconstruction. Out of these six, three
are pre-event and the other three are post-event. For longterm disaster risk mitigation, there is a need to emphasize
on mitigation and preparedness measures. In this paper a
newly developed method for the assessment of earthquake
safety index is proposed. This method consists of the
combination of three major components viz., Hazard,
Exposure and Vulnerability. In addition to these, it also
includes physical, social, economic and othervulnerability parameters. Each of these parameters is subdivided and depending on the city, usage and built
environment, a weightage factor is assigned to each of thecomponents which constitute Safety Index. Similar
concept has been worked out in various cities by UNDP,
FEMA, etc., worldwide in last decade. As a first attempt
in India, it is proposed to evaluate risk in the form of index,
by developing an appropriate model for Disaster
Mitigation Indexing for Bhuj. This kind of indexing will
be helpful for the administrative bodies in comparing theoverall risk across number of cities or region and also inprioritization of cities to implement appropriate disastermitigation and preparedness measures.
2. INTRODUCTION
Earthquake disaster risk assessment is urgently required
to mitigate possible losses in future disasters. Quantitative
assessment of earthquake risk is necessary to confirm
qualitative intuition of the severity of the problem. And,
this quantitatively method of assessing earthquake risk ofcities/towns located in Seismic Zones III, IV and V will
help understand relative earthquake risk across not only
the cities but also the districts. Therefore, a simple
measure, called the Earthquake Disaster Risk Index(EDRI), is proposed to estimate broadly the earthquake164risk of a city and a district; this is not meant to be used for
estimating the earthquake risk of individual houses. The
objectives of the proposed work are;
• Provide a systematic method to compare broadly theearthquake disaster risk across many cities or
districts;• Create awareness in cities with low seismicity thateven a small earthquake event can cause a majordisaster owing to characteristics of the built
environment in the cities;• Sensitize governments and decision makers to takeappropriate actions towards reducing earthquake risk,
and judiciously use the available limited resources(manpower and money);• Identify effectiveness of the specific measures
adopted in the construction of buildings, by reevaluating the EDRI periodically over the years; and• Prioritize cities and districts for launching
earthquake risk mitigation program.

Figure 1. Street view of market of Bhuj city
3. METHODOLOGY
Risk index has been computed using the combinationof hazard, vulnerability and exposure parameters of the
Bhuj city. The main purpose of the visit was to conduct
the rapid visual survey (RVS) of buildings to help
understand the distribution of risk at city level. But,
considering the time required for survey and field data
conversion in a computer for further analysis, the decision
was taken to capture the visual inspections in the form ofphotographs. These photographs of buildings wereanalysed later for calculating the risk of individual
building. As a result, the team could do the risk
calculations and results analysis in a systematic format in
a computer. Various parts of new and old settlements of

the city was surveyed and photos of building stock inthose area were captured.
Risk = Hazard x Exposure x Vulnerability(1)

4. CASE STUDY OF BHUJ CITY
Bhuj is the one of the largest cities in Gujarat in termsof population as well as in area especially in Kachchh
region. As per Census of India 2011, Bhuj city has about
32,681 buildings which include the residential,commercial and office buildings. Based on the basic load
resisting system or framing system and construction
technology, 28% buildings are of stone masonry, 27% ofbrick masonry, 52% reinforced concrete (RC) and rest 7.5%of other category buildings are standing till the date.
26 January 2001 Bhuj earthquake has completelychanged the mindset of private and government
construction work in and around the city. In order tocompute the risk index of the city, a field survey was
conducted by IIIT Hyderabad. After collection of building
information of bhuj city, next step was the calculation ofrisk of individual building, and risk of city. IIIT
Hyderabad team had prepared an approximate procedure
to calculate the risk of city based upon the risk of
individual buildings in the city.
Table 1. Risk Index of all Surveyed Buildings and Risk
Index of Bhuj City

Bhuj city has low mean EDRI score for Brick Masonry
Building with RC Roof compared to RC Buildings; thesame trend is reflected in the standard deviation of EDRI
score. The reason for large standard deviation in RC
Buildings is its poor earthquake resistance as seen in the2001 Bhuj Earthquake. On the other hand, most Brick
Masonry Buildings performed poorly during 2001 Bhuj
Earthquake and were re-constructed with earthquake
resistant features, leading to decrease in mean EDRI value
and lesser deviation.

Figure 4. Loss of life scenario: (a) Present, (b) After
Exposure Issues rectified, (c) After Exposure + Life
Threatening Factors rectified, (d) After Exposure, LTF
and Architectural Features rectified, (e) After
Exposure, LTF and Structural Aspects Rectified, and (f)After all Aspects are rectified
5. CONCLUSIONS & RECOMMENDATIONSThis paper aims to arrive at long term mitigation
measures. For that purpose, a methodology was developed
and the same was tested on Bhuj city as a case study. The
following recommendations were given to local bodies toreduce risk of the city:• Locate staircase properly while planning andseparate it structurally to reduce significantly
possible damage in building.
• Orient structural members properly to contribute tolateral stiffness and uniform stiffness along bothprincipal plan directions to avoid twisting ofbuilding during horizontal shaking.
• Modify local building byelaws to provide sufficient
gap between buildings to reduce damage in buildings
due to pounding effects.
• Prevent any new construction or extension ofexisting buildings of gamtal areas. Propose newpolicy to encourage owners to move out of unsafe
buildings. Encourage new housing schemes or loan
for new building construction in other locations.
• Retrofit important buildings (including multi-storey
buildings) urgently.
• Train private and government engineers in designand detailing, and artisans in construction ofearthquake resistant buildings.
• Generate awareness in public to accelerate disastermitigation and preparedness programs.
6. REFERENCES••

Figure 3. Distribution of EDRI score•

Ramancharla Pradeep Kumar and C. V. R. Murty:
Earthquake Safety of Houses in India: Understanding the
Bottlenecks in Implementation, ICJ, Vol. 88, No. 9, Sept
2014.
Srikanth T., Kumar R. P., Singh, A. P., Rastogi, B. andKumar, S. (2010) “Earthquake Vulnerability Assessmentof Existing Buildings in Gandhidham and Adipur Cities
Kachchh, Gujarat (India)”, European Journal of Scientific
Research , Vol.41 No.3, pp.336-353, ISSN 1450216X, http://www.eurojournals.com/ejsr.htm
Jain, S.K. (2010), Seismic Assessment & Retrofitting of
RC Frame Buildings, Rebuild, Vol. 4, 1, pp. 6-8.

165

A STUDY ON DEFINITION TO NATURAL DISASTER-DANGEROUS POINTS ON ROAD THATAIM TO UPGRADE THE EVALUATION OF DISASTER RESISTANCE ON ROAD-NETWORKS. OSAWA1, J. TAKAYAMA2, M. FUJIU3, and Y. SHIOZAKI4Doctor Course Student, Kanazawa University, Kanazawa, Japan,
2
Professor, Kanazawa University, Kanazawa, Japan,
3
Associate Professor, Kanazawa University, Kanazawa, Japan,
4
Assistant Professor, Kanazawa University, Kanazawa, Japan,
Correspond to Assoc. Prof. M. FUJIU (fujiu@se.kanazawa-u.ac.jp)
1

Keywords: road disaster prevention plan, disaster resistance, road-network evaluation, dangerous point on road
1. INTRODUCTION
Japan is prone to various natural disasters. Even
recently, large-scale earthquakes and heavy rains haveoccurred, and they cause great damage. It is necessary toquickly deal various disaster responses to mitigate thedisaster damage. It is also an important challenge thatdefine response details and its procedures clearly andensure that stakeholders have informed them. On the other
hand, to be implemented these responses, it is essential totransport physical resources and personal resources todisaster-response bases. It is recognized that keeping theconnection between disaster-response bases under natural
disaster is more important in various disaster responses inJapan from these facts and past disaster experiences. Fromthese social backgrounds, many methods to assess thedisaster resistance of road-network that aiming to keep
connectivity on road-network under natural disaster havebeen proposed. The perfection as evaluation method ofdisaster resistance on road-network is often argued whileargumentation about "what kind of road-conditions haveinfluenced the possibility of road-damage in natural
disaster" of conditions for the appropriate application ofthese methods is not enough. The purpose of this study is
proposing the definition method for dangerous points onroad that possible to be damaged in natural disaster.
2. METHODOLOGY
It has been often discussed that the damage state and/or
cause of damage by natural-disasters. On the other hand,little work has been done on application these knowledges
of previous studies in the research field of road structures
to assessment the disaster resilience of road-network. The
problem seems to lie in the fact that the application policy
is not established.
To propose such an application policy for road-network
assessment, investigation reports of natural-disasters that
occurred in the past in Japan are referenced as researchsources in this study. The advantage that using thesereports is completeness of past damage cases. To achieve
the purpose of this study, what types of road-structure andwhat its elements are vulnerable to natural-disaster issummarized in first step. In next step, text mining
techniques are used for analyzing the factors that related
to vulnerability.

166

Figure 1. An example of road collapse.

Figure 2. An example of tsunami damage
3. CONCLUSIONS AND FUTURE WORKSIn the future, we will collect and organize quantitativeand qualitative data such as individual specifications andsurroundings of each structure and the scale of the external
forces that acted on each of these organized damage forms
and factors, and statistically analyze them. The aim is to
extract elements that have a relationship with damage. In
addition, it is a future task to show the requirements of thehazard points for disasters that should be considered in theevaluation of the functionality of the road network against
natural disasters based on the extracted elements from thedamage form, damage factor, and disaster scale.

Seismic Vulnerability Assessment ofLifeline System in Myanmar
AYE AYE MAR1, KYAW KYAW2, TAKESHI KOIKE3
PhD candidate, Department of Civil Engineering, Yangon Technological University,
Myanmarayeayemar.civil@gmail.com
2
Professor, Department of Civil Engineering, Yangon Technological University, Myanmar
3
Academic Advisor, JICA EEHE Project, Yangon, Myanmar
1

ABSTRACT
Lifeline earthquake disaster brings not only property loss but also functional damage tourban activities and socioeconomic loss. In this research, one of the water supply network
system of Gyobyu in Yangon region is proposed for the seismic vulnerability assessment
based on the three limit states: immediate occupancy (IO), life safety (LS), and collapse
prevention (CP) corresponding to the three earthquake levels: maximum operated earthquake(MOE), design basis earthquake (DBE), and maximum considered earthquake (MCE),
respectively. This research aims to assess the condition of the supply of water distribution
system of downtown area after the earthquake and to evaluate and assess the probability of
failure of structural components for each failure mode. To find out the failure mode of eachstructural component, the seismic performance of the pipes are assessed by the pipe damage
mode such as leakage, pull-out and buckling failures at the joint based on the seismic design
guideline from American Lifelines Alliance (ALA). It can be said that the proposed seismic
risk procedure is quite useful and applicable to all large cities, located in earthquake-prone
areas of the world and it can help decision-makers who work with disaster prevention andreduction of urban lifeline system for the better plan in the future.
Keywords: water supply system, vulnerability assessment, three earthquake levels, probabilityof failure, seismic design guideline
1. INTRODUCTION
Lifeline systems are often grouped into six principal types of systems: electric power, gas andliquid fuels, telecommunications, transportation, wastewater facilities, and water supply.
According to earthquake survey in recent decades, the correlation and coexistence of thelifeline system are the important factors to result in their big losses.
Myanmar is one of the earthquake-prone regions as it is located in the eastern part of Alpide
Earthquake Belt, between the eastern end of Himalaya Arc, the collision zone of Indian andAsia Plates, and the northern segments, highly active portions of Sunda Arc. The mostsignificant and active fault in Myanmar is the Sagaing fault shown in Figure 1, a 1500km longtectonic fault that passes through the cities of Nay Pyi Taw, Bago, Sagaing, Mandalay, andclose to Yangon, as in [1].
Yangon, the second city of Myanmar, is situated in the southern part of the Central lowland
and it is tectonically bounded by the Indian-Burma plates subduction in the west, Sagaing
fault which is located about 40km in the east of Shwedagon pagoda, West Bago Yoma fault in
the north, Kyaykkyan fault in the north-east, and the Andaman rift zone in the south, as in [2].

167October 2010, Kobe, Japan

Figure 1: Fault Hazard Map in Myanmar
In this paper, one of the water supply network system of a hospital in Yangon region is
proposed for the seismic vulnerability assessment based on the three limit states: immediate
occupancy (IO), life safety (LS), and collapse prevention (CP) corresponding to the threeearthquake levels: maximum operated earthquake (MOE), design basis earthquake (DBE),
and maximum considered earthquake (MCE), respectively.
2. DECRIPTION AND SELECTION OF STUDY AREA
The present water supply system of Yangon which has been operated over 100 years, allpumping stations in reservoirs and main transmission pipes have already aged and beyond its
lifespan, because of the long economic sanction to Myanmar. Gyobyu pipeline wasconstructed in 1940 and has been operating for over 70 years. After that, this pipeline suffered
Taikkyi earthquake effect on March 2017. According to the report of Yangon City
Development Committee (YCDC), over 200 numbers of pipe supports damaged between
Gyobyu reservoir and near Phugyi reservoir (10.5miles). Water supply is vital to the functionof an industrialized society and important to emergency response and recovery after
earthquakes.

Figure 2: Schematic Configuration of Existing Water System of Yangon (JICA, 2012)168

New Technologies for Urban Safety of Mega Cities in Asia

There are mainly four reservoirs shown in Figure 2: Gyobyu reservoir, Ngamoeyeik reservoir,
Phugi reservoir, and Hlawgha reservoir, which supply the water by the various types oftransmission main pipes and distribution pipelines to the citizens in Yangon area, as in [3].
Among them, Gyobyu reservoir is proposed as a source point and Kokkine reservoir in Bahan
Township is selected because it is one only one above-ground pipeline in Yangon. The watertransmission pipeline, however, in Yangon, is installed on the ground supported by theconcrete foundation from the reservoir to the downtown terminal point by segmented steel
pipe having concrete lining with dresser coupling joint.
3. METHODOLOGY
The basic information to assess the seismic vulnerability of the lifeline system is moredetailed classified into two types of data: earthquake hazard data and lifeline systems
vulnerability data. These parameters are used in the safety and vulnerability assessment of thewater supply system. Generally, it includes seismic hazard analysis for Sagaing fault based on
the probabilistic way, the basic concept of the seismic design method of the water supply
system, and vulnerability assessment of the system at the three different seismic performancelevels.
Based on Probabilistic Seismic Hazard Analysis (PSHA), the following earthquake motions
are defined: MOE – 50% in 50 years, DBE – 10% in 50 years, and MCE – 2% in 50 years
corresponding to the three limit states: immediate occupancy (IO), life safety (LS), andcollapse prevention (CP), respectively [4] and their corresponding pipe joint criterion for theirperformances is formulated based on the Japan Water Work Association (JWWA) guideline[5] as shown in Table 1. By analyzing microtremor data value from the microtremor
measurements along the pipeline, the soil profile types existing along the study area arechosen based on the code, ATC-40. The probabilities of damage mode in each segment are
estimated from the fragility curves for structural components at the three different limits ineach area.
Table 1. Design Formula of Pipe Joints for Wave Effect due to Design Earthquake
DesignEarthquake

Limit
state

MOE

IO

Mechanical Joint
Straight
Geometrical
pipe
pipe

Continuous Joint
Straight
Geometrical
pipe
pipe

None
DBE

LS
None

MCE

CP
None

Seismic Vulnerability Assessment of Lifeline System in Myanmar

169

October 2010, Kobe, Japan

4. STRUCTURAL SAFETY ASSESSMENT
In this study, the earthquake magnitude of 6.51M, 7.34M, and 7.87M for the return period of73, 475, and 2475 years are estimated by using Figure 1. The PGA at bed rock of 0.087g,
0.178g, and 0.281g for the MOE, DBE, and MCE are estimated with the assumption of
R=54km for Taikkyi and Hmawbi area. The PGA at bed rock of 0.319g, 0.284g, and 0.448g
for the MOE, DBE, and MCE are estimated with the assumption of R=36km for Mingalardon
area. Then the PGA at bed rock of 0.096g, 0.196g, and 0.308g for the MOE, DBE, and MCE
are estimated with the assumption of R=50km for Mayangone, Bahan and Yankin area.
Moreover, a simple procedure to evaluate the soil amplification factor of surface strata isdeveloped based on the response spectrum method by INOUE et al. Finally, the PGA atground surface of 0.208g, 0.427g, and 0.674g for the MOE, DBE, and MCE are taken bymultiplying the PGA at bed rock with the soil amplification factor of 2.4 and 2.2 for Taikkyi
and Hmawbi respectively. The PGA at ground surface of 0.16g, 0.33g, and 0.53g for the
MOE, DBE, and MCE are taken by multiplying the PGA at bed rock with the soil
amplification factor of 1.37, 1.71, 1.83 and 1.76 for Mingalardon, Mayangone, Bahan andYankin respectively. Based on the response acceleration spectrum , the response velocity
spectrum , can be theoretically formulated as shown in Table 2.
A simplified methodology for the seismic vulnerability assessment of water distribution
networks are determined. The results of axial and bending damage mode of pipes in eachtownship are compared with the critical seismic performance at the three limit states. From
which, the pipe damage mode such as leakage, pull-out and buckling failures at the joint will
be revealed.
Table 2. Analysis of Response Velocity Spectrum,
Response Velocity Spectrum(m/s)
Earthquake Taikkyi Hmawbi Mingalardon Mayangone Bahan
MOE
DBE
MCE

0.259
0.383
0.661

0.219
0.336
0.548

0.172
0.187
0.44

0.24
0.281
0.593

0.25
0.281
0.597

Yankin
0.258
0.289
0.617

Figure 3: Axial Damage Mode of Mechanical Joint Pipes (MS) in Six Townships at MOE,
DBE, and MCE

170

New Technologies for Urban Safety of Mega Cities in Asia

Figure 4: Bending Damage Mode of Mechanical Joint Pipes (MS) in Six Townships at MOE,
DBE, and MCE
Figure 3 and 4 show the axial and bending damage mode of pipe at the three seismic
performance levels in six townships. Based on the results of damage mode of pipes, the axial
displacement of mechanical joint pipes are more than the critical limits whereas the bendingstrain of mechanical joint pipes are controlled within the critical limits.
In estimation of probability of failure mode from fragility curves, the probability of failureof continuous and mechanical joint pipes at the three seismic performance levels in six
townships, as shown in Figure 5 to 10, show that most of the mechanical joint pipes have
100% probabilities of failure in three seismic levels.

Figure 5: Probability of Failure of Continuous Joint Pipes (MS) in Taikkyi at MOE, DBE, andMCE

Figure 6: Probability of Failure of Continuous Joint Pipes (MS) in Hmawbi at MOE, DBE,
and MCE

Seismic Vulnerability Assessment of Lifeline System in Myanmar

171

October 2010, Kobe, Japan

Figure 7: Probability of Failure of Continuous Joint Pipes (MS) in Mingalardon at MOE,
DBE, and MCE

Figure 8: Probability of Failure of Continuous Joint Pipes (MS) in Mayangone at MOE, DBE,
and MCE

Figure 9: Probability of Failure of Continuous Joint Pipes (MS) in Bahan at MOE, DBE, andMCE

Figure 10: Probability of Failure of Continuous Joint Pipes (MS) in Yankin at MOE, DBE,
and MCE172

New Technologies for Urban Safety of Mega Cities in Asia

5. CONCLUSIONS
The analysis results for each failure mode of the system are mainly depending upon the shear
wave velocities, response velocity spectrum, and network data of the system. From theevaluation of the axial damage mode of pipe joints for each township, it can be examined thatthe more the displacement in mechanical joint. Moreover, all mechanical joint pipes have
100% probabilities of failure in three seismic levels. It shows the alert for aging pipes,
especially mechanical joint pipes, should be replaced with newly developed pipes based on
the seismic design guideline and seismically resilient water pipes together with non-leakage
joint mechanism are needed when the current water supply system is upgraded to a new
system.
REFERENCESThe Sagaing Fault, Myanmar (Burma) [Online]. Available: http://www.sagaingfault.info/
Myo Thant, “Probabilistic Seismic Hazard Assessment for Yangon region, Myanmar,” Reportof Department of Geology, University of Yangon, Myanmar, December 21, 2012.
Situation of Water Supply System of Yangon City and its Future Demand, Yangon City
Development Committee [Online]. Available: http://www.ycdc.gov.mm /Maung Tint Lwin, A Simplified Seismic Performance based Method for Steel Moment
Resisting Frames using Building Design Data Bank, Ph.D Thesis, Yangon technological
University, Yangon, September, 2015.
Khin Aye Mon, T.Koike, G.Nishikawa, L.E.Garciano, and J.Kiyono, A Simplified
Seismic Design Method of Water Lifelines in Developing Countries, AUN/SEED-Net
Project, 2015-2017Yi, H. L.2012.

Seismic Vulnerability Assessment of Lifeline System in Myanmar

173

A funfamental study on dynamic wave propagationin the soil around a cavity
Yusuke Nakata1, Reiko Kuwano2, Masahide Otsubo2, Umair Ali1
Graduate Student, Graduate school, The University of Tokyo, Japan
2
Professor, Institute of Industrial Science, The University of Tokyo, Japan
3
Research Associate, Institute of Industrial Science, The University of Tokyo, Japany-nakata@iis.u-tokyo.ac.jp
1

ABSTRACT
Recently, an increasing number of sinkhole problems in developed cities have been reported.
To prevent a sinkhole, it is necessary to detect a subsurface cavity in its earlier stage. Although
dynamic wave survey is often used to investigate the stiffness or structure of the ground, it is
not always valid for detection of subsurface cavities. If ground motion sensors are installed inburied pipes, detecting a subsurface cavity based on vibration characteristics of surrounding
ground would be feasible. In this study, with the aim of improvement in cavity detection method,laboratory model tests were conducted to investigate wave propagation through the model
ground during the process of cavity growth. In the model tests, nano-order compression waves
were excited and received with piezoelectric transducers and the time and frequency domain
analyses of the received signals were performed. As a result, a decrease in both wave velocity
and lowpass frequency (flp) was observed as a cavity grew due to the expansion of the loosened
area around the initial cavity. Discrete element method simulations were also conducted withthe presence of a subsurface cavity and a decrease in flp was observed due to the diffraction of
propagation path.
Keywords: subsurface cavity, dynamic measurement, disk transducer, discrete element
method
1. INTRODUCTION
Recently, an increasing number of sinkhole problems in developed cities have been reported.
Sinkholes occur as the final phase of subsurface cavity growth; thus, improvement of cavity
detection method is required. Dynamic wave survey is widely used to investigate the stiffness
or structure of the ground, whereas characteristics of dynamic wave propagation around a cavity
are not well understood. Kominami et al. (2018) reported that this method is not always valid
for the detection of a subsurface cavity. According to Fujii et al. (2019), the ground-penetratingradar method, which is currently used for finding cavities beneath the road surface in Japan, ispractically conducted only for cavities that are located shallower than 1.5 m from the groundsurface. However, no efficient method to find a cavity at a deeper elevation has been established.
As the cavities are often formed due to the failure of deeper underground structures, if groundmotion property can convey information about the nearby subsurface cavity, detecting cavities
in deeper ground is maybe possible by installing motion sensors on underground structure. In
this research, with the aim of improving the cavity detection method using a dynamic wave

174

December 2019, Yangon, Myanmar
propagation method, laboratory model tests, and discrete element method (DEM) simulations
were conducted with the presence of a subsurface cavity.
2. MODEL TEST
2.1 Model preparation
A cylindrical transparent chamber was used to reduce the effect of reflected waves due tosidewalls. The chamber was 30 cm in diameter with a capacity of water supply through theholes on the bottom plate (Figure 1). Uniformly graded silica sand No. 5 having a medianparticle size of 0.5 mm, was used in the model test. The sand was pluviated from a specificelevation to achieve a specimen height of 20 cm with a relative density of 50%. Two pairs of
disk transducers (DT) were placed on the bottom plate and the top surface of the sandy ground(Figure 1). The DTs including both P- and S-type piezoelectric elements were developed basedon Suwal & Kuwano (2013). The dimension of each piezoelectric element was 30 mm × 30
mm × 2 mm (thickness). A thin coating of epoxy resin was applied to the surface of the elements
to prevent damage due to water and abrasion caused by angular sand grains. The elements wereplaced inside acrylic frames and supported using silicone and epoxy resin. Uniform load of
about 2.7 kPa was applied on the surface of the sandy ground to ensure firm contacts between
the sand grains and the surface of DT.

Figure 1: Schematic of soil chamber and disk transducer
A single period of sinusoidal pulse having input frequencies of 2~30 kHz was given from the
DT at the ground surface (transmitter) and received at the DT on the bottom plate (receiver).
An input voltage of 140 V was sent to the P-type element to generate compression (P-) waves
and the excited P-mode displacement on the surface of the disk transducer was about 8~12 nm.
The chamber design and experimental procedure broadly followed Kominami (2018). On thebottom plate, there are three holes; two larger holes are for supply and drainage of water andthe other hole located at the center is for drainage of soil with pore water (Figure 2). The
saturation condition of the sand was controlled by raising and lowering a water tank connectedto the chamber through the bottom plate. By opening the initially closed hole at the center where
the water level was initially adjusted to be 10 cm or 15 cm from the bottom, the soil was drainedwith water and cavity was formed in the ground. Dynamic wave measurements were performed
at five stages of the ground condition as below (Figure 3):
1. Dry: after the surface load was applied to the dry ground
2. Saturated: after increasing the water level to the surface

New Technologies for Urban Safety of Mega Cities in Asia

175

3. No cavity (unsaturated): after lowering the water level to the bottom
4. Cavity S (unsaturated): after the first cycle of drainage of both water and soil
5. Cavity L (unsaturated): after the second cycle of drainage of both water and soil
For each condition of the five stages, wave velocity and frequency distribution of inserted andreceived waves were analysed.

Figure 2: Bottom plate

Figure 3: Flow of experimental procedure
After performing the wave measurement for ‘Cavity L’, the ground was cut vertically into half
to observe the cross-section of the cavity (Figure 4). The volumes of cavities were estimatedfrom the drained sand and the volume of ‘Cavity L’ was observed five times as large as that of‘Cavity S’ (Figure 4). The shape of ‘Cavity S’ was inferred from the volume of the drained sandwith an assumption that both ‘cavity S’ and ‘Cavity L’ had a similar shape. The wave
measurements were conducted along the vertical line connecting the transmitter DT and thereceiver DT, located 2 cm off from the side of ‘Cavity L’ (Figure 4).

Figure 4: The cross-section of the cavities

176

A fundamental study on dynamic wave propagation in soil around a cavity

December 2019, Yangon, Myanmar
2.2 Results and discussion
The data of compression (P-) waves measured along the vertical line (dotted line in Figure 4)
were analyzed. The time domain responses are shown in Figure5(a) where the amplitude ofreceiver responses was normalized by the maximum amplitude for ’No Cavity’ case. It is foundthat attenuation was considerable for ‘Saturated’ and ‘Cavity L’ cases. P-wave velocity (VP)
was calculated from the rising points of the input and output signals and VP data are listed in
Figure 5(b) for the five stages of the ground condition. As the condition changed from ‘Dry’ to‘Saturated’ VP decreased, while VP increased from ‘Saturated’ to ‘No Cavity’. This variation
can be attributed to the variation in the effective stress that varies with the change in pore waterpressure. As the cavity expanded, VP decreased continuously although the wave path was 2cm
off from the cavity in “Cavity L”. VP for ‘Cavity L’ was lower than that of ‘No Cavity’ by 27%.
This reduction is probably explained by the expansion of the loosened area in the soil aroundcavity as VP is lower for looser soil (Otsubo et al., 2017). It was found from this result thatgrowth of a cavity can be correlated with the change in VP around the cavity.

Figure 5: (a) Time-domain responses of P-waves (amplitude of receiver responses was
normalized by the maximum amplitude for ’No Cavity’ case) (b) VP for each condition
The amplitude of frequency spectra (fast Fourier transforms of received signal / transmitted
signal, FFTout/FFTin) with frequency for the four conditions excluding ‘Saturation’ are shownin Figure 6(a). The input wave frequency was 30 kHz for the frequency domain analysis toexcite a broad range of frequencies. The lowpass frequency, the maximum frequency that canpass through the ground (flp) is quantified by considering a threshold amplitude of 8 × 10-4 forthe experiment. The flp values of each condition are illustrated in Figure 6(b). As Otsubo et al.
(2017) described, flp has a consistent relationship with stress or density. The present experiment
revealed that flp decreases when the model ground becomes fully saturated; in contrast, flp
increases when the model ground becomes unsaturated, exhibiting a similar variation with VP.
However, the increase in flp due to shift from ‘Saturated’ to ‘No Cavity (unsaturated)’ wasrelatively larger than that for VP; this is probably caused by the capillary force generated
between contacting particles during the unsaturation process. In the process of cavity expansion,
flp decreased as the size of cavity increased similar to the variation in VP. The flp value for‘Cavity L’ was smaller than that for ‘No Cavity’ by 60% and the decreasing rate of flp was
significant compared to that of VP. Thus it is inferred that growth of a cavity can be assessedfrom flp around the cavity more sensitively than measurement of wave velocity.

New Technologies for Urban Safety of Mega Cities in Asia

177

Figure 6: (a) Frequency spectra of received waves and (b) lowpass frequency
3. DEM SIMULATION
To understand the mechanism of the decrease in VP and flp around a subsurface cavity, DEM
simulation was conducted considering the situation of the model test. Particle-scale analyses
using DEM enable observation of phenomena that cannot be measured in the laboratory
experiment including wave reflection and diffraction.
3.1 Model preparation
Ali et al. (2019) revealed that the inter-particle cohesion due to unsaturated pore water isnecessary to simulate a subsurface cavity. In this research, a simplified unsaturated model
implemented by Ali et al. in the open-source LAMMPS code (Plimpton, 1995) was used. The
contact theory follows the Hertz-Mindlin model but an inter-particle suction of 5 kPa wasconsidered to stabilize the model with a cavity. Note that the value of suction adopted is muchlarger than the realistic value. The size of spherical particles was 1.2 – 2.2 mm in diameter,
Young’s modulus, Poisson’s ratio, and the specific gravity were 71.6 GPa, 0.23, and 2.5,
respectively.
The dimensions of the model ground were 200 mm in width (X), 20 mm in depth (Y) and 180
mm in height (Z) and it was prepared using an air-pluviation method under gravity. Periodic
boundary was applied for the Y-axis direction and rigid boundary conditions for the X- and Zaxis directions. Firstly, the inter-particle friction was set to 0 so that a dense condition wasachieved (void ratio of 0.572). Secondly, the inter-particle suction was applied to mimic theunsaturated condition in the laboratory model test. Lastly, the inter-particle friction wasincreased to 0.5 and particles located in the area of 40 mm × 100 mm (Cavity S) or 60 mm ×
150 mm (Cavity L) crossing the periodic boundary were removed from the simulations to
produce a cavity.
After the ground had become stabilized, P- wave was generated either right above the cavity orright above the receiver region (Figure 7). Particles located inside a square of 50 mm (width) ×
10 mm (thickness) were considered as a transmitter and a receiver (Figure 7). The particles
inside the transmitter region were excited downward following single period of cosine pulse
having a frequency of 20 kHz and a double amplitude of 200 nm (see Figure 9 for particles
displacement). No viscous damping was considered during the wave propagation simulation.

178

A fundamental study on dynamic wave propagation in soil around a cavity

December 2019, Yangon, Myanmar

Figure 7: Outline of the model
3.2 Results and discussion
When P-wave was transmitted from right above the receiver, no distinct difference in received
waves was observed irrespective of the difference in cavity size. This is probably due to thesuction force that is beyond realistic value, and therefore the influence of a cavity on thesurrounding soil, i.e. loosening effect, was not measurable. Therefore, the consequences when
the transmitter right above the cavity was excited are described below.
For ‘No Cavity’ case, the radial propagation of P-waves was observed as illustrated in Figure
7. As the effective confining pressure increases with depth, a gradual increase in wave velocity
was observed at a deeper elevation. Reflection was observed at the walls and at the boundary
between soil and cavity. Diffraction phenomenon was also observed around the cavity (Figure8). The time domain and frequency domain responses of the transmitted and received waves
are shown in Figure 9. The time domain displacements are calculated as the mean displacementof the particles inside the region. In the frequency analysis, time domain response until 1.5 ms
was processed. flp was estimated by considering a threshold amplitude of 1 × 10-2 for DEM data.
The rising point of the received waves is slightly delayed for ‘Cavity L’, where the shortest
travel path is diffracted and extended (Figure 9(a)). As for flp, a slight decrease for ‘Cavity L’
was observed (Figure 9(b)). The overall distribution of frequency at large amplitudes was also
lowered for ‘Cavity L’ compared with the other conditions.

Cavity S
Cavity L
Figure 8: Reflected wave and diffraction wave
New Technologies for Urban Safety of Mega Cities in Asia

179

Figure 9: (a) Time – displacement and (b) frequency spectra of waves
This study also analyzed the arrival time of P-waves which were reflected vertically at theceiling of the cavity. The arrival time was measured at the transmitter and it was 0.495 ms for‘Cavity S’ and 0.225ms for ‘Cavity L’. These are almost proportional to the distance between
the transmitter and the ceiling of the cavity, which is 80 mm for ‘Cavity S’ and 30 mm for‘Cavity L’. This indicates that the reflection waves from the ceiling of a cavity can be effective
to estimate the depth of the subsurface cavity.
4. CONCLUSIONSThis study investigated characteristics of compression wave propagation in the soil around acavity using laboratory model tests and DEM simulations. Based on the model tests, thefollowing conclusions can be drawn:
 Characteristics of P-wave propagation are affected due to a subsurface cavity nearby.
 Both VP and flp decrease as a cavity grows.
 Decrease in flp is more sensitive compared to VP when the cavity size increases.
Based on the DEM simulations, the following conclusions can be drawn.
 flp decreases due to diffraction of the propagation path around a cavity.
 Reflection of P-waves at the ceiling of a cavity is evident.
 An improved DEM model considering loosening and arching effects is required.
REFERENCES
1.
2.

3.
4.
5.

180

Kominami, N., 2018. The relationship between sinkholes and waterpaths and theeffectiveness of underground water sound, Master thesis, University of Tokyo, Tokyo,
Japan.
Fujii, K., Kitamura, K., Kojima, Y., Kuwano, R., Yonemoto, Y., Achievements ofCollaborative Study on Effective Measures for Prevention of Road Cave-in in FUJISAWA
city, Proceedings of 54th Japan National Conference on Geotechnical Engineering. 14431444.
Hardin, B.O. & Richart, F.E., 1963. Elastic wave velocities in granular soils. J. Soil Mech.
Found. Div. 89, No. 1, 33-65.
Otsubo, M., O’Sullivan, C., Hanley, K. J. & Sim, 2017. Influence of packing density andstress on the dynamic response of granular materials, Granular Matter 19:50.
Ali, U., Otsubo, M., Kuwano, R., 2019. Implementation of suction-tension model for cavity
simulations using DEM. Proceedings of 54th Japan National Conference on GeotechnicalEngineering, 809-810.

A fundamental study on dynamic wave propagation in soil around a cavity

December 2019, Yangon, Myanmar
Plimpton, S., 1995. Fast parallel algorithms for short-range molecular dynamics. Journalof Computational Physics. 117, No. 1, 1-19.
7. Suwal, L. P. & Kuwano, R., 2013. Disk shaped piezo-ceramic transducer for P and S wave
measurement in a laboratory soil specimen. Soils Found. 53, No. 4, 510-524.
8. Dutta, T. T., Otsubo, M., Kuwano, R. & O’Sullivan, C., 2019. Estimating stress wave
velocity in granular materials: Apparent particle-size dependency and appropriate
excitation frequency range, Géotechnique Letters. 9 (3), 1-26.

6.

New Technologies for Urban Safety of Mega Cities in Asia

181

UNSATURATED SHEAR CHARACTERISTICS OF EXTREMELY LOOSE VOLCANIC SOIL
CAUSING SLOPE DISASTER
Itsuki Sato1and Reiko Kuwano2
1

Doctoral Student, The University of Tokyo, Institute of Industrial Science, Tokyo, Japan, i-sato@iis.u-tokyo.ac.jp
2
Professor, The University of Tokyo, Institute of Industrial Science, Tokyo, Japan, kuwano@iis.u-tokyo.ac.jp

Keywords: Volcanic soil, Cementation, Particle crushing, Landslide, Slope disaster
1. INTRODUCTION
Slope Disasters that flow a long distance with destructiveenergy at very gentle slopes are sometimes observed. Insuch cases, the trigger layer is often volcanic soils withextremely high void ratios, induced by earthquake or
heavy rainfall. The loose structure of such volcanic soils
are retained by weak cementation or composed ofcrushable particles having intra voids. Although the causeof destructive long-distance flow has been explained byliquefaction, trigger layer was not always fully saturated,
i.e. liquefaction is not a major cause. Thus, this study
considers deformation and strength characteristics of
unsaturated soils. Focusing on the fact that slope disasters
such as long-distance flow or gentle slope flow are
triggered by loose volcanic soil layers, artificial loose soil
samples consisting of silt and cement were prepared [1].
Triaxial tests with unsaturated condition were performed
to discuss how air trapped in voids affects the shear
strength properties.

which the shear strength converges to a residual state,called steady state.

2. TEST RESULTS
Artificial pumice specimens ( Φ =5cm, H=10cm) withcementation and crushable particles were prepared.
Unsaturated CU tests were conducted at different
confining pressure and initial water content by using
double cell method (Table1).
Table 1. Experimental cases
Test
Sr(%) before
consolidation
Consolidationpressure(kPa)Preconsildationpressure(kPa)ρs（g/cm3)
Void ratio, e

Ad-100 Ad-300

A60- A60- A70- A70CU100 CU300 CU100 CU300

0

0

60

60

70

70

100

300

100

300

100

300

20

20

20

20

20

20

2.69
2.06 ~2.02

Volumetric strain atconsolidation εvol (%)

3.2

6.1

3.2

15.2

4.7

18.1

Sr(%) after
consolidation

0

0

63

76

75

93

3. CONCLUSIONS
Figures 1 and 2 show experimental results. Artificial
pumice exhibits a high shear strength and a low
compressibility when cementation is maintained.
However, once cementation is lost, a high compressibility
is observed. Although the specimen is not fully saturated,
after the shear strength reached its peak and thecementation was lost, a brittle behaviour was observed in

182

Figure 1. Unsaturated CU test results.

Figure 2. Stress path
REFERENCES[1] I. Sato, R. Kuwano (2019) Vulnerability of volcanic loose
soils having cementation and crushable particles, International
Symposium on Deformation Characteristics of Geomaterials(IS-Glasgow 2019), E3S Web of Conferences, 92, 09001.

Relationship between inequality, education, anddisaster experience at the household levelin Yangon City, Myanmar
1

Kota HORIUCHI1 and Michael HENRY2Master student, Graduate School of Engineering,
Hokkaido University, Japan
kt_horiuchi@eis.hokudai.ac.jp
2
Associate Professor, Faculty of Engineering,
Hokkaido University, Japan

ABSTRACTThe Government of Myanmar issued The Myanmar Sustainable Development Plan
(MSDP) in August 2018. The MSDP is designed to achieve ensuring balance between
development in the economic, social and environment spheres. In this research, as the
economic, social and environmental aspects, income inequalities, education
attainment levels, and disaster experience, are focused on. This is because Myanmar
is a nation having the possibility of various natural disasters, and the income
inequality and the education attainment levels can be considerable in households
units. The objective of this research was to clarify the relationship between income
inequality and the damage of water-related disaster while examining the relevance of
the income inequality and the education attainment levels, and to consider the
relationship the education attainment levels and experience of disaster. From analysisof these relationships, it was revealed that there are relationships between the HIS
Zone and experience of disaster, between education and the HIS Zone, and between
income and the education. Therefore, it is concluded that the education has arelationship with the experience of disaster, and the income influences the experienceof disaster through the education and the HIS Zone.
Keywords: sustainability, education, income, disaster
1. INTRODUCTION
Myanmar is proceeding the development system in the government, and has
experienced rapid economy and political growth in recently years. According to theWorld Economic Outlook Database (International Monetary Fund, 2019), the economic
growth rate of Myanmar keeps advancing from 5% to 8% in recently 7 years. However,it has been appearing the imbalances growth in Myanmar so much as to concentrate on
the economic and political growth. To address the imbalances, the Government of
Myanmar designed “The Myanmar Sustainable Development Plan (MSDP) (TheGovernment of the Republic of the Union of Myanmar , 2008) in order to ensure theright balance between economic, social development, and environmental protection.

183

December 2019, Yangon, Myanmar

Myanmar also have a possibility to suffer from various natural disasters. According to
the hazard profile of Myanmar (Government of the Union of Myanmar, 2009), it isclassified the disasters in Myanmar to the cyclone, droughts, earthquakes, fires,
landslides, high tide, and tsunami. Furthermore, these disasters frequency are not low,
and a lot of local people suffer from these disasters every year. Especially for the waterrelated disasters, such as cyclone and flood, the damage of them are more severe thanother disasters. For example, in cyclone Nargis, which occurred in 2008, the number ofdead and missing exceeded 140,000 people, according to the Learning from Cyclone
Nargis (Nizar Mohamed, 2009). Therefore, it is quite important problem to be solved,
and safety from disaster is an important social and environmental aspect forsustainability.
With these conditions of Myanmar in mind, this research focused on the social andenvironmental aspects for attaining sustainability. In social and environmental sphere,
income inequalities, education achievement levels, and disaster experience and damage
were focused. The objective of this research was to clarify the relationship between
income inequality and the experience and damage of water-related disaster, while also
examining the effects of the education attainment levels on the experience and damageof water-related disaster. It will be able to contribute to suggest some strategies toaccomplish sustainable development in Myanmar.
2. SURVEY METHOD AND SAMPLE CLASSIFICATION
2.1 Investigation method
In order to clarify the relationship between water-related disaster and income inequality,and education attainment levels, it was used the data of Household Interview survey(HIS) in Yangon city, conducted by Japan International Cooperation Agency (JICA) in“Strategic Urban Development Plan of Greater Yangon” in 2012. The detail of HIS issummarized in Table 1. In this survey, 10,069 households answered, which is equal to1.0~1.2% of population of Yangon City in 2012. As for survey items, this researchutilized the data of household socioeconomic conditions, such as income inequality andeducational achievement levels, and experiences of water-related disaster and propertyof damage. The data which was used in this research was summarized in the Table 2.
Table 1: Summary of questionnaire ( Japan International Cooperation Agency, 2013)
MethodInterview Survey
Term
22 Sep 2012 – 16 Nov 2012
TargetHousehold in Yangon City
Number of Sample
10,069 Household
Table 2: Survey items

184

Classification
Income inequality

Questionnaire contents
Household income per month

Educational levels

Education attainment level

Experience of waterrelated disaster andproperty of damage

Experience of disaster
Property damage by cyclone
Property damage by flood

Response categories
Below 25,000 to Above 1,000,000
University degree or higher, Highschool, Middle school, Primaryschool or lower
Experience, No experience
Very serious, Serious, Slight, None
Very serious, Serious, Slight, None

New Technologies for Urban Safety of Mega Cities in Asia

2.2 Investigation area
HIS was conducted in 18 townships groups (HIS Zone), which compose Yangon city,and the number of sample households and proportion to the actual households in eachHIS Zone are summarized and shown in Table 3. The distribution of sample was
decided by the population in 2011.
Table 3: Characteristics of townships in Yangon in 2011
HIS
Zone
A
B
C
D
E
F

No. of the sample
households
495 (1.22 %)
546 (1.08 %)
556 (1.14 %)
411 (1.13 %)
397 (1.00)
492 (1.00 %)

HIS
Zone
G
H
I
J
K
L

No. of the sample
households
675 (1.00 %)533 (1.00 %)489 (1.00 %)
571 (1.00 %)431 (1.00 %)380 (1.00 %)

HIS
Zone
M
N
O
P
Q
R

No. of the sample
households
1,123 (1.00 %)
596 (1.00 %)805 (1.00 %)
700 (1.39 %)
500 (1.70 %)
300 (2.08 %)2.3 Definition and classification of sustainability indicators
To consider the sustainability in Yangon City, the data of household income, educationlevel and the experience and damage of disaster were selected as indicators of threesustainability pillars: Economy, Society, and Environment. In addition, HIS Zone wasalso considered as an indicator to reveal the actual Myanmar’s sustainability condition
depending on the residence areas.
As for the income and education levels, it was classified into the four groups as shownin Table 4. In this research, it was defined that the highest education level in thehousehold member as the household education level, because it is expected that theperson who has the highest education level will support the other household members.
Among 10,069 households of data, 9,518 data were valid and 551 data was notconsiderable because of the lack of the income and education responses. The
distributions of income and education levels in household data are summarized in Table
4. Regarding with the relationship between the income and education levels, a
correlation coefficient was 0.378609, and it can be said that there is a weak relevance.
Thus, it was available to analyze both of indicators.
As for the experience of water-related disaster, it was classified as shown below inTable 5. Among 10,069 households of data, 9,518 data was also available to analyze therelevance of the experience of water-related disaster to the income levels and theeducation levels. Meanwhile, as for the responses for cyclone or flood damage, the total
number of household data was restricted because they only include the people who haveexperienced each disaster. The available household number of who have everexperienced cyclone was 6,228. Among them, 5,072 households have ever experienced
cyclone damage. On the other hand, 237 households have ever experienced flood and 94
households have ever experienced flood damage. The number of households that haveever experienced flood together with flood damage was closed to 1.0~2.0% of total
households, so it was omitted in the below discussion. The classification of theexperience of cyclone or flood damage and the property of damage of them weresummarized in Table 6.
Relationship between inequality, education, and disaster experience at the household levelin Yangon City, Myanmar

185

December 2019, Yangon, Myanmar

Table 4: Classification of household income and education level
IncomeClassification
Number( kyat/month)
Low income
1,712(0 ~ 100,000)
Middle income
3,829(100,001 ~ 200,000)
High income
3,144(200,001 ~ 500,000)
Extremely high income
833(500,001 ~)
Total
9,518

Ratio
17.99%

Education
Classification Number

Ratio

1,155

12.13%

40.23%

Upper primaryschoolMiddle school

2,516

26.43%

33.03%High school

1,608

16.89%

8.75%

Above
university
Total

4,239

44.54%

9,518

100.00%100.00%

Table 5: Classification of experience of water-related disaster
Experience of water-related disasterClassification
Number
Ratio
Yes
6,617
69.52%
No
2,901
30.48%
Total
9,518
100.00%
Table 6: Classification of experience and property damage due to cyclone and flood
Experience of cyclone damage
Classification Number
Ratio
Yes
5,072
81.44%
No
Total

1,156
6,228

18.56%
100.00%Experience of flood damage
Classification Number
Ratio
Yes
94
39.66%
No
Total

186

143
237

60.34%
100.00%CycloneProperty damage
Classification
NumberVery serious
751
Serious2,044
Slight
2,277
Total
5,072

Ratio
14.81%
40.30%
44.89%
100.00%Flood

Property damage
Classification
NumberVery serious
26
Serious20
Slight
48
Total
94

Ratio
27.66%
21.28%
51.06%
100.00%

New Technologies for Urban Safety of Mega Cities in Asia

3. ANALYSIS RESULTIn this research, it was analyzed the relationship between the experience of waterrelated disaster, the income level, the education levels and the HIS Zone at the
beginning. Then, the households that have experienced disaster were divided to thegroup of cyclone, flood and others, and analyzed the relationship between theexperience of cyclone damage, the income levels, the education levels, and the HIS
Zone in the group. Next, the experience of cyclone damage were distributed as propertyof damage, such as very serious, serious, and slight. The relevance of the property ofdamage of cyclone to the income levels, the education levels and the HIS Zone wascalculated in the group.
In each analysis, Cramer’s V was calculated in order to evaluate the degree of influence
between each indicators. The degree of relationship with Cramer’s V is shown in Table
7, and the equation of Cramer’s V is shown below. The evaluation criteria in Cramer’s
V is objective, so it was modified to this analysis to reveal the relationships of them.
Table 7: Degree of the relationship of Cramer’s V
Cramer’s V
0.31 ~
0.21 ~ 0.30
0.11 ~ 0.20
0.01 ~0.10
0The degree of relationship
Relative strong relation
General relation
Weak relation
Very weak relation
No relation

The equation of Cramer’s V&UDPHU’V9χ2 = Chi-square valuen = Sample size
k = Number of category

3.1 Relation between experience of water-related disaster and socioeconomic
condition
The relevance of the experience of water-related disaster to socioeconomic condition,such as the income levels, the education levels and the HIS Zone, was analyzed by
Cramer’s V. This analysis was conducted with targeting the group that was composedwith 9,518 households of Table 5, and cross-tabulation data which shows the
distribution of households is summarized in Figure 1. The Cramer’s V are summarized
in the Table 8.
The proportion who have ever experienced water-related disaster became lower as theincome levels and the education levels rise. From the analysis of Cramer’s V, therelationship with the HIS Zone and the experience of disaster, with the income andeducation levels, and with the HIS Zone and the education levels were considered as
general relation.
Table 8: Results of Cramer’s V in the group that have experienced water-related
disaster (N=9,518)
IncomeEducation
HIS Zone
Experience of disaster

IncomeEducation

HIS Zone

0.225998
0.189938
0.104956

0.216482
0.125452

0.261187

Experience of disaster

Relationship between inequality, education, and disaster experience at the household levelin Yangon City, Myanmar

187

December 2019, Yangon, Myanmar

Extremely high57.50%

High

42.50%

66.48%

Above university

63.91%

36.09%High School

69.22%

30.78%

33.52%

Yes

Middle72.53%

27.47%

Middle School

74.44%

25.56%

Low

74.24%

25.76%

Upper Primary

79.83%

20.17%

0%

25%

50%

75%

(a) Divided by income levels
R
Q
P
O
N
M
L
K
J
I
H
G
F
E
D
C
B
A

0%

100%

25%

25%

75%

100%

(b) Divided by education levels

83.72%
77.78%
82.41%
70.88%
77.23%
85.20%
85.23%
70.30%
67.93%
74.73%
74.95%
59.02%
63.60%
53.98%
64.83%
48.91%
55.45%
46.99%
0%50%

No16.28%
22.22%
17.59%
29.12%
22.77%
14.80%
14.77%
29.70%
32.07%
25.27%
25.05%
40.98%
36.40%
46.02%
35.17%
51.09%
44.55%
53.01%
50%

75%

100%

(c) Divided by HIS Zone
Figure 1: Experience of water-related disaster (N=9,518)

3.2 Relation between experience of cyclone damage and socioeconomic condition
Table 9: Results of Cramer’s V in the group who have experienced cyclone (N=6,228)
Experience of cyclone damage
Extremely high42.86%

High

32.05%

Above university

32.26%

67.74%High School

30.30%

69.70%

67.95%

44.68%

55.32%

Middle SchoolLow

41.18%

58.82%

Upper Primary

25%

50%

75%

(a) Divided by income levels
50.00%
16.67%
12.50%
7.32%
6.52%

33.33%

75.00%

100.00%91.67%

50.00%
100.00%85.71%
25%

50%

No

25%

39.47%
50%

75%

100%

(b) Divided by education levels
50.00%

90.91%
95.24%
100.00%92.68%
93.48%

Yes

57.53%

60.53%0%100%

HIS Zone
0.307632

42.47%

83.33%
87.50%

38.89%

26.09%
0%188

Education
0.104734

Middle

0%

Q
P
O
N
M
L
K
J
I
H
G
F
E
D
C
B
A

57.14%

Income0.104827

25.00%

0.00%
8.33%

9.09%
4.76%
0.00%

61.11%
66.67%

73.91%

50.00%
14.29%
75%(c) Divided by HIS Zone
Figure 2: Experience of cyclone disaster damage (N=6,228)

0.00%
100%

New Technologies for Urban Safety of Mega Cities in Asia

The relevance of the experience of cyclone to socioeconomic condition, such as theincome levels, the education levels and the HIS Zone, was analyzed. This analysis was
conducted with targeting the group that was composed with 6,228 households of Table
6 of cyclone, and cross-tabulation data which shows the distribution of households issummarized in Figure 2. Cramer’s V are summarized in the Table 9. The relationshipwith the income levels and the education levels, with the income levels and the HIS
Zone, with the Education levels and the HIS Zone were omitted above table.
There are no distribution of who have experienced disaster damage in all income levels.
However, the proportion became lower as the education levels rise. From the analysis of
Cramer’s V, the relationship with the HIS Zone and the experience of cyclone damage
was recognized as relative strong relation in Cramer’s V. On the other hand, it was notappeared the relationship of the experience of cyclone damage and the income levels
and the education levels.
3.3 Relation between property cyclone damage and socioeconomic condition
The relevance of the property of damage of cyclone to the income levels, the educationlevels, and the HIS Zone was analyzed, and summarized in the Table 10. This analysis
was conducted with targeting the group that was composed with 5,072 households ofTable 6 of cyclone, and cross-tabulation data is summarized in Figure 3.
Table 10: Results of Cramer’s V in the group who have experienced cyclone damage(N=5,072)
Property damage of cyclone
Extremely high 10.88% 26.87%
High 12.75%
Middle 14.92%

37.74%
42.08%

Low 18.67%
0%62.24%

44.10%
25%

50%

Income0.089718

Above university 11.38% 34.82%
High School 14.95%

42.70%

42.35%

42.99%

Middle School 15.16%

43.61%

41.23%

37.24%

Upper Primary

75%

100%

R
48.54%
Q 5.80%18.45%
35.51%
P
15.13%
47.24%
O
36.94%
N
15.98%
47.49%
M
10.16%
40.51%
L
18.79%
50.35%
K
13.38%
41.40%
J
13.21%
36.94%
I
14.56%
40.45%
H 8.23%38.41%
G
11.27%
42.61%
F
11.11%
41.41%
E
11.66%
37.42%
D
11.89%
34.05%
C
10.40%
39.20%
B
13.90%
36.32%
A
10.53%
33.92%
25%

22.42%
0%25%

HIS Zone0.221662

53.80%

49.51%(a) Divided by income levels

0%

Education
0.084117

44.84%

Very serious
Serious
Slight32.74%

50%

75%

100%

(b) Divided by education levels

33.01%
37.63%
28.68%
36.53%
49.33%
30.85%
45.22%
49.85%
44.98%
53.35%
46.13%
47.47%
50.92%
54.05%
50.40%
49.78%
55.56%

58.70%
34.38%

50%(c) Divided by HIS Zone
Figure 3: Property of cyclone damage

75%

100%

Relationship between inequality, education, and disaster experience at the household levelin Yangon City, Myanmar

189

December 2019, Yangon, Myanmar

The proportion of who experienced slight damage was higher as the income andeducation levels rise. However, it was recognized that just only the HIS Zone haverelationship with the property of cyclone damage in Cramer’s V.
4. CONCLUSION
From the results, it is revealed that the HIS Zone has the strongest factor for the disaster
experience, especially cyclone, among almost the income levels or the education levels.
Then, it is obvious that the HIS Zone and the education levels have relationship.
Furthermore in the property damage due to cyclone, it is clear that the HIS Zone has
relationships with property of cyclone damage and the education levels. Therefore, it
can be said that the education levels influence on the HIS Zone and the HIS Zone
decides the disaster experiences and the damage of cyclone. It can be assumed thathouseholds who have higher education levels prefer to stay in the areas that have lesspossibility to be exposed to the dangerous and damage of disaster, such as cyclone.
In addition, the income levels influence on the property damage of cyclone through the
HIS Zone. It was not found the directly relationship with the income levels and thedisaster experiences, however, it can be concluded that the income levels have also
influences for the disaster experience if other aspects of disaster were analyzed with theincome levels because the influential role of the HIS Zone for the property of damage.
ACKNOWLEDGEMENT
This research was supported by the Science and Technology Research Partnership for
Sustainable Development (SATREPS) program, which is sponsored by the Japan
Science and Technology Agency (JST) and Japan International Cooperation Agency(JICA). The copyright of this Household Interview Survey data belongs to Japan
International Cooperation Agency (JICA). The authors would like to express their
gratitude to Dr. Akiyuki Kasasaki of The University of Tokyo and Mr. Naoki
Yamashita of Nippon Koei Co, for permission to use this data.
REFERENCES
International Monetary Fund, 2019. Myanmar: Gross domestic product, constant prices(Percent change), World Economic Outlook Database, The United Stated of America.
The Government of the Republic of the Union of Myanmar, 2018. Myanmar
Sustainable Development Plan (2018-2030), Myanmar
Government of the Union of Myanmar, 2009. Hazard profile of Myanmar, Myanmar.
Nizar Mohamed, 2009. Learning from Cyclone Nargis, United Nations Environment
Programme Kenya.
Japan International Cooperation Agency, Nippon Koei Co., Ltd., NJS consultants, Ltd.,YACHIYO Engineering Co, Ltd., International Development Center of Japan Inc., Asia
Air Survey Co., Ltd., ALMEC Corp. 2013. A Strategic Urban Development Plan ofGreater Yangon : Final report 1, Appendix, Appendix 2, Japan.

190

New Technologies for Urban Safety of Mega Cities in Asia

Development of Subsurface Cavity Potential Map for Effective Road Cave-in Countermeasures
Ryoko SERA 1, Reiko KUWANO 2,
1

Manager, Operational Headquarter, GEOSEARCH Co.,LTD., Tokyo, JAPAN, r-sera@geosearch.co.jp (corresponding
author)2
Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, JAPAN, kuwano@ iis.u-tokyo.ac.jp
Keywords: subsurface cavity; road cave-in; regional characteristics; factor analysis; evaluation of potential
1. BACKGROUND
Preventing road cave-in is key to keeping road traffic
functions. Since the 1990s, several Japanese public
administrations began subsurface cavity surveys utilizing
ground-penetrating radar technology. The trigger ofstarting surveys was a social issue known as the “cave-in
syndrome” that a fact of multiple road cave-ins in Tokyoin 1988. From then on, the surveys have been conducted
regularly all over Japan that focuses on cavities due todamage of aged buried infrastructures, influenced byhigh-density underground development, and fluctuationof groundwater level. In recent years, emergency surveys
were carried out after large earthquakes to ensure disasterrecovery activities. Such unique and state-of-the-art
technologies for the prevention of cave-in have been
innovated through various experiences over 30 years.
Especially, it is important that the survey technology ofsubsurface cavities be improved in accuracy and speed,
and the early detection will lead to a reduction in roadmaintenance costs. Besides, survey data analysis andcave-in mechanisms have been discussing and thedevelopment of repair material for cavities has
progressed based on field investigations. Regarding theevaluation of cavity/cave-in, each data of the subsurface
cavity was used for prediction of risk to cave-in itself,
but this is the first attempt to evaluate the regional area
using the cavity survey data and the environmental
factors of cavities.

Figure 1: Photo of a self-propelled cavity exploration car
named “SKELE-Car”
2. PURPOSE OF DEVELOPMENT OF THE
POTENTIAL MAP
Cave-in potential map is an information-sharing tool.
The purpose of the development of that map is tounderstand the regional condition. It shows the potentialof cavities in regional using the cavity survey data andthe environmental factors of cavities. For keeping roadfunctions against cave-ins, it is necessary to consider theroad network around the cavities. The regional

assessment of the potential of the cavity/cave-in and themap showing it gives some benefits. It takes appropriate
measures not only for regular situations but also for
emergency situations such as large-scale natural disasters.
In addition, these approaches will support discussion atother local governments that starting new measures forcave-in as experienced cases.
3. CONTENTS FOR DEVELOPMENT THE MAP
The beginning of cave-in is a small groundphenomenon. One of the factors forming cavities can beconsidered as a washout of soil particles through a
broken sewer pipe or joint. Fig. 2 shows photos as actual
examples of the factor of cavities in Fujisawa city. In
addition, another main factor is the consolidation
settlement of soil particles in the subgrade; loosen thesoil around the underground structure and fluctuation ofgroundwater level. In many cases, some contributing
factors influence each other forming cavities.

Figure 2: Photos at detail investigations of the cavity
and a broken sewer pipe by aging [2]The development of the potential map prototype wasconducted in collaboration with Fukuoka City[1] andFujisawa City[2] [3]. Each city has different localities, withdifferent city development scales, underground usage,
the history of the survey of the subsurface cavity, and thefactors of cavity. The content used to develop the
potential map prototype is as follows:
1. Databases of cavity survey / including informationof repair and factors of cavity
2. Governmental manage data / GIS; roads, sewage
3. GIS data; landform, geology
4. The databases of the cave-in
5. Monitoring survey data of cavities
6. Detail investigation data of causes of cavity
7. Governmental manage data; groundwater level
The contents of 1-3 were used for development inFukuoka City, and 1-7 were used for development inFujisawa City. Using these contents, the main regional
environmental factor and appearance rate of the cavities
in each area were analyzed, and the method forevaluating the potential of cave-in was studied.

191

4. PROTOTYPE CAVE-IN POTENTIAL MAP OF
FUJISAWA CITY
The cave-in potential of Fujisawa city was set by using
four factors belonging to each divided grids; type andage of sewer pipe, the number of sewers attaching pipe,
groundwater level, and surface geology. The thresholdvalues are as follows:-Sewer: Confluence type laid in 1950-80s-Number of sewer attaching pipes: more than 300 /m2-Groundwater level/reference value: shallower than
GL-3m
-Surface geology: Sandy
After making sure for appropriateness by sensitivity
analysis of four potential factors in each, the regional
occurrence tendency of cave-ins was analyzed byoverlaying each four-factor maps with the cave-in andcavity location map. A knowledge that cavities often
occur under overlapped multiple factors was reflected inthis evaluation as a new attempt. Fig. 3 shows the
combination of cave-in factors and grade ofpotential/probability of occurrence of Fujisawa City.

Figure 3: Combination of cave-in factors and grade ofpotential/probability of occurrence of Fujisawa City [4]Fig. 4 shows the cave-in potential map as a prototype
of and occurrence tendency of cavity/average number ina unit length of road.

Figure 4: Cave-in potential map as a prototype of andoccurrence tendency of the cavity of Fujisawa City [4]192

Furthermore, assuming the potential value as Y andthe occurrence frequency of cave-ins/ cavities as X, thefollowing approximate expression and correlation
coefficient were obtained was obtained:
Cave-in: Y = 0.460x - 0.085, R2 = 0.9180
Cavity: Y = 1.508x - 0.352, R2 = 0.8977
This highly accurate formula suggests “if one cave-in
occurs, there will be 3 to 4 cavities”.
5. CONCLUSION
This is the first attempt to evaluate the area by thecavity information. And it was able to get the realistic
result with the output named cave-in Potential Map.
Subsurface Cavity Potential Map is achieved byreliable cavity survey data over several years. The
evaluation got possibility by analysis and quantificationof regional factors from field investigations andgovernmental manage data. It is necessary to understandthat the quality of an evaluation depends on "theaccuracy of cavity survey" and "determining the cause ofcavity“. Preventing road cave-in is key to keeping roadtraffic functions and it also will be a disaster-resistantsystem. This MAP can be used by any city around theworld, for all road administrators; National roads,
prefectural roads, for all administrative departments;
roads, sewage, disaster prevention, and not limited to one
region, can be expanded into zones.
REFERENCES[1] Ryoko SERA., R. KUWANO, and M. HOTTA,(2019). Development of subsurface cavity potential map
for prevention of road cave-in, The 16th Asian Regional
Conference on Soil Mechanics and GeotechnicalEngineering (16ARC), Taipei.
[2] Hiromitsu NISHIYAMA., H. YOKOTE, M.
HARIGAYA, R. KUWANO, and H. MIKI, (2019).
Achievements of Collaborative Study of Effective
Countermeasures for Prevention of Road Cave-in in
Fujisawa City, Japan Society of Civil Engineers 2019
Annual Meeting, TAKAMATSU, VI-292.
[3] Kunio FUJII., K. KITAMURA, Y. KOJIMA, R.
KUWANO, M. ABE, and M.OKAMURA, (2019). A
Discussion about Effective Countermeasures against
Road Cave-in in Fujisawa City based on Monitoring
Survey of Subsurface Cavity by Public-Academia-Private
Collaborative Study, Japan Society of Civil Engineers
2019 Annual Meeting, TAKAMATSU, VI-293.
[4] Ryoko SERA., R. HIRATA, Y. YAMAMOTO, R.
KUWANO, S. YONEMOTO, and N. KUROSAWA,(2019). Development of Cave-in Potential Map of
FUJISAWA
City
by
Public-Academia-Private
Collaborative Study, Japan Society of Civil Engineers
2019 Annual Meeting, TAKAMATSU, VI-294.

Issues on Crisis Management ~especially counterterrorism~ at the Tokyo Olympic GamesITO Tetsuro
Visiting Professor, ICUS, IIS, the University of Tokyo, Japan
Keywords: Olympic Games, Terrorism, Risk management, Crisis management
1. Introduction
In 2020, Tokyo Olympic Games will be held in Japan. In
the big sporting events such as the Olympic Games, somany issues on crisis management emerges comparedwith other normal sporting events.
This paper describes empirical analysis about why someparticular big sporting events such as Olympic Games
cause crisis management issues, and what kind of threats
are there, and what the features of threat are, and terrorismis the biggest issue among these threats.
The Analysis are about the methods of risk management
such as preparations for threats, prevention of crisis andmitigation of damage, and methods of crisis management
for minimization of damage, prevention of expansion ofdamage and chain expansion of crisis.
This paper describes about 2020 Tokyo Olympic Gamesand analyses cause of threats, issues on crisis management
and resolution of crisis in the Games.
2. The Issues and Countermeasures in the Big Sports
Event
1
2

IssuesSecurity3

Traffic
Management
Crowd Control

4

Abnormal Events

Countermeasures
Counterterrorism
Cyberterrorism Measures
Public Law and Order
Transportation Measures
Traffic Jam Measures
Crowd Control in the Stadium
Crowd Control outside of theStadium
Safety Measures in the
Emergencies and the Natural
Disasters
Heat Stroke Measures

3. The biggest issue on crisis management at Tokyo
Olympic Games is the terrorism.
The reason why the terrorism becomes biggest issue is
Olympic Games is big sport event which attracts
international focus. Therefore terrorist can appeal theiropinion and thoughts and existence to the whole world infront of numerous media coming from the world.
There have been many terrorism incidents at the O
lympic Games in the past. In late years a terrorist
incidents by the influence of the Islam extremism
occur worldwide, and not only the things affectedby the Islam extremism but also the terrorism
with the group which the name has not been yet
known may be expected in future.
And it is necessary to assume the terrorism by

every means of tools such as using drones andcyber terrorism. And the targets of terrorism havespread to soft targets from conventional targets.
4. What are important to counter the crisis?
~Risk Management and Crisis Management~[1] Risk Management as the Prior Measures to Crisis
To take prior countermeasures to crisis is very importantto prevent crisis and to mitigate the damage. The
important things to build countermeasures are 1. The
assumption of various type of crises. 2. Examination ofvarious countermeasures to crises. 3. The decision of acountermeasure and to start the preparations and executecountermeasures to crisis.
[2] Crisis Management in the period of before the timeof Olympic Games and at the time in the mid of Olympic
Games.
It is very important to investigate the countermeasures tovarious hazards which will happen in the period of thetime before Olympic Games and at the time in the mid of
Olympic Games. The important things are 1. Who will
prepare and execute the countermeasures to crises? 2.
Who will play the role of countermeasures when
emergency situation outbreaks? 3. What kind of crisis
management will be executed? 4. Who will be thedecision maker of the countermeasures to the crisis? 5. Is
enough training accomplished for a state of emergency?
4. Who is the main player to prepare and execute thecountermeasures to the each crisis?
In the big sporting event there are many interested partyof the event not only the persons concerned with sports
itself but also the central and local government, media,
sponsor, the public etc. It is very important to establish asystem to prepare, examine, execute the countermeasures
to crises in advance. The important things are to decide
earlier who is the main player of risk management for eachcrisis? It is also very important to build the close
cooperation system for risk management and crisis
management.
5. Conclusion
Big sport event such as Olympic Games become a hugesociety phenomenon beyond contents in itself of thecompetition. The crisis to surround the big sporting event
became huge too. Risk management and crisis
management are very important to prevent or avoid crisisand to mitigate the damage. Early establishment of thesystem to prepare, examine, execute countermeasures tocrisis is crucial for close cooperation between concernedorganizations of big sporting event.

193

SESSION F
SPECIAL SESSION: SATREPS/ TRANSPORTATION,INFRASTRUCTURE MANAGEMENTAnalysis of transit behaviors using
mobile call detail records
Kyaing1, Ko Ko Lwin2, Yoshihide Sekimoto2
1
Civil Engineering Department,
Yangon Technological University,
Myanmar1
kyaingkyaing63@gmail.com
2,3
Institute of Industrial Science (IIS), University of Tokyo, Tokyo,Japan2kokolwin@iis.u-tokyo.ac.jp
3sekimoto@iis.u-tokyo.ac.jp
ABSTRACT

Rapid urbanization and modernization are increasing around the world including Myanmar.
Mobile call detail records (CDRs) provide new opportunities to measure the transport demands
and problems in transportation planning. This research aims to analyze the transit behaviors
of mobile phone user based on their call activities. O-D pairs were computed for the whole cityand extracted O-D pairs, which fall inside the buffer region, based on their Cell ID locations
for rail users. Logical assumptions are specified to extract all users. This results indicated thatthe four categories of transit usage such as rail users, non-rail users, other modes to rail andrail to other modes. Among the four categories, non-rail users are the highest proportion andrail users are the lowest proportion. This study is very useful in future travel demands to support
a better new transport system in Yangon City.
Keywords: call detail records, origin-destination, rail users, non-rail users, transit behaviors
1. INTRODUCTION
In order to satisfy the needs for rapid urbanization and motorization, the city should be wellplanned with a variety of facilities. Among the needs, transportation infrastructure plays a vitalrole in economic growth of country. The current urbanization and motorization are becoming
worse and worse day by day on the existing transport infrastructure in Yangon city. The
deteriorating of urban transport situation has become a serious concern socially, politically andenvironmentally. In order to provide a well transportation planning, it is necessary to understandtransit behaviors.
To analyze the transit behaviors, many data sources and information are required. Today,
especially in developing countries, the process of obtaining relevant real-world indicators is a
hard task that needs a lot of expertise and resources. Household travel interviews and census
survey data or traffic counts represent traditional tools to analysis travel demand. Interview andsurveys, however, are costly and rare especially in Myanmar.
The roadside and household surveys involve expensive data collection, limiting sample sizes
and lower update frequencies. Moreover, they are prone to sampling biases in reporting. The

196

December 2019, Yangon, Myanmar

census data is also hard to obtain to analysis travel demand. Due to the expensive roadsidesurveys and infrequent data collection of census data, CDRs data have become a powerful tool
to analyze travel behavior patterns that are useful for transportation planning. Therefore, thisstudy concentrates to analyze transit behavior using mobile call detail records in Yangon urban
area.
The structure of this paper is organized as follows: related relevant study backgrounds arepresented in Section 2. Section 3 states why the study area is selected as a case study. Section
4 briefly describes data to be used in this study and how to extract origin-destination pairs andtransit behavior of travelers. Transit behaviors of the study area are discussed in Section 5.
Finally, conclusions and future works are presented in Section 6.
2. PREVIOUS STUDIESThe number of researchers studied the various topics using mobile call detail records. Samplingbiases and reporting errors occur in traditional approaches (Hajek, 1977: Kuwahara and
Sullivan, 1987; Groves, 2006). Automated registration plate scanners (Castillo et al. 2008) andmobile traffic sensors such as portable GPS devices (Parry and Hazelton, 2012: Morimura andKato, 2012: Herrera et al. 2010) can be used for origin-destination estimation in more recent
approaches. The mobility patterns of phone users are linked to human mobility behavior. Lwin
et al. (2018) analyzed the hourly link population and flow directions of Yangon city frommobile CDRs data. This dataset was intended to optimize bus routes, solve traffic congestion
problems, and enhance disaster and emergency preparedness. Kyaing et al. (2017) analyzed
human mobility patterns for different regions in Myanmar based on CDRs data. In this study,
average distance travelled, preferred days of long distance users and human mobility patterns
at different times of same place and same time at different places were analyzed for two major
cities. The results indicated the similarities and differences in mobility patterns for both cities.
Zin et al. (2018) also estimated the origin-destination trips in Yangon by using CDRs data. This
study described the originating and destination trips from each township in weekday andweekend. And then, the estimated values are compared with the JICA O-D trips at 2013 forvalidation purpose. Kyaing et al. (2017) forecasted the trip generation by using CDRs data. In
this study, regression models were described for forecasting of trip generation.
Rose (2006) and Caceres et al. (2008) described other issues to be considered that may affectthe accuracy of transport mode prediction. These factors are market penetration, customer
profile and network infrastructure of the mobile network operator supplying the billinginformation, citizens who do not carry or have their mobile devices turned off during travelling.
Traffic data estimations were analyzed using a variety of metrics extracted from mobile phone
networks by Caceres et al. (2008). The development of origin-destination matrices for traffic
flow estimates, travel speed, travel time calculations, and traffic volumes were also presented.
Transportation mode inference was examined from mobile billing records based on travel timeby Wang et al. (2013). Mode share of driving and public transportation for a given origin anddestination are determined and walking trips are not taking into account in this study. H.
Ishizuka et al. (2015) proposed an automated method to generate an alignment of cell towers
for a specific transportation route using unsupervised machine learning techniques. They
focused on distinguishing different types of motorized transport such as train, bus, and subway.
Their proposed system can estimate a specific name of transport line which a user rode on by
sequence matching between cell tower sequences of a user and pre-learned cell tower sequences
for each route.
In this study, transit behaviors of travelers were analyzed using mobile call detail record forurban area of Yangon City.

New Technologies for Urban Safety of Mega Cities in Asia

197

3. STUDY AREA
Yangon has an area of 598.750 km2 with a population of 5.211 million in 33 Townships of theurban area. The current urbanization and motorization are becoming worse day by day on theexisting transport infrastructure in Yangon city. Traffic congestions, long travel time, low travel
speed and traffic accidents are subjected in most parts of the days. Average travel speed being
even below 10 kph in central business district. In order to provide good transportation planning,
it is necessary to measure transit behavior of Yangon City. Therefore, the urban area of Yangon
was selected as a case study. The location of the study area and its road network is shown in
Figure 1.

Figure 1: Location of the study area

4. METHODOLOGY
4.1 Data
Call Detail Records (CDRs) data are used to estimate of origin-destination trips and toinvestigate the travel behavior of the phone uses. The CDR data containing all mobile phone
voice calls and data means such as short message service (SMS) and internet service werecollected from base transceiver stations (BTS) towers which are located in the study area from
1st December 2015 to 7th December 2015. It was provided by Myanma Posts andTelecommunications (MPT), which is one of the biggest mobile operators in Myanmar. There
are 657 BTS towers of MPT services and 132 traffic analysis zones in 33 townships of study
area.
Distribution of traffic analysis zones and township boundary and BTS towers in traffic analysis
zones are shown in Figure 2(a) and Figure 2(b) respectively. Individual phone numbers wereanonymized by the operator before leaving their storage facilities and were identified with asecurity ID (hash code) to safeguard personal privacy. CDRs data contain Timestamp (date and198

Analysis of Transit behaviors using mobile call detail records

December 2019, Yangon, Myanmartime), Caller’s ID, Call duration in second and Caller’s connected cell tower ID. The locationof a user can be determined from the Cell ID that provides the ID of BTS station that iscommunicating with the user.
In addition, secondary data such as road network map of Yangon City was also used to analyze
travel distance for each O-D pair trip.

Figure 2(a). Distribution of traffic analysis zones, (b) Distributions of BTS
4.2 Method
In this paper, various transportation modes were identified and transit behavior were analyzed
using mobile call detail records in Yangon.
4.2.1

Identification of trip

Cell phone usage of each region can be used to generate trip numbers of this region withincertain time frame and time windows. For each mobile user, it is assumed that a trip is madebetween two consecutive calls occurring within a limited time window with different BTS. The
number of trips (flows) can be analyzed as the movement of people who travel from starting
point in the origin region and ending in the destination region. In this study, origin anddestination zones the cells defined by the base stations and convert the O-D trip to be between
Traffic Analysis Zones (TAZs) instead of between cells.
Therefore, time window is necessary to be defined for the determination of O-D trip. Generally,time window interval is defined according to travel behavior of study area. The time window isrepresented by the travel time to make a O-D trip. Time window is identified as 3 hours in thisanalysis.
4.2.2

Pre-processing of CDRs data

Pre-processing of CDRs data was done to extract O-D pairs based on BTS stations. Firstly, allmissing data were removed and error in BTS file, missing BTS name, wrong coordinates andtownships names were corrected in this analysis. And, Cell ID numbers were formatted tostring. Geographic locations (Longitude, Latitude) were added to each cell IDs after formatting.
New Technologies for Urban Safety of Mega Cities in Asia

199

CDRs data alone could not know the location of a person because it is only CELLID with themobile subscriber. Therefore, the geolocation of CELLID needs to join with latitude andlatitude to trace the location. Both formatted voice and data usage were merged by individual
subscribers. From these CDRs data, PID, DTIME, and CELLID data were only used in thisanalysis.
4.2.3

Processing of CDRs dataO-D pairs were extracted for three hours’ interval such as 06:00-09:00, 09:00-12:00, 12:0015:00, 15:00-18:00, 18:00-21:00 for only Tuesday for typical weekdays and Sunday for the
weekend. 3-hour interval was identified based on hourly variation of human mobility pattern
for the study area. As a time window determination, travel time between origin and destination
were extracted for all trips travelled by each user for the whole day. It is found that travel time
between origin and destination trip is maximum 3 hours. Therefore, 3 hours is identified as time
window in this study.
And, travel distance, duration and travel speed were calculated for each O-D pair with the road
network of Yangon City. In this study, BigGIS RTX Research Toolbox (Lwin et al. 2018) wasused to process CDR data cleaning, formatting, Cell ID geolocation, OD pair generation,
network distance measurement, and speed calculation.
4.2.4

Identification circular railway user from CDRs data

Circular railway line has predefined 200 m or 400 m buffer for service area to determine modeshare of rail users as shown in Fig.4.

Figure 4. Rail (buffer 200 m or 400 m) and road network of study area
According to questionaries’ survey, 200 m buffer is predefined as rail user service area in thisstudy. O-D pairs were computed for the whole city and extracted O-D pairs, which fall inside
the buffer region, based on their Cell ID locations for rail users. True and false status are
specified as logical assumptions to extract rail users. True is specified as if calling fall inside

200

Analysis of Transit behaviors using mobile call detail records

December 2019, Yangon, Myanmar

the buffer region and false is identified as if calling fall outside the buffer region. Therefore, it
can be identified as circular railway user if both origin and destination of traveler’s status are“True” (both calling fall inside of the buffer area). The numbers of O-D pairs for rail users wereextracted using SQL queries. After that, mode share was computed for rail users.
4.2.5

Identification of transit mode from CDRs data

Users were divided into four categories such as circular railway to other mode, other mode tocircular railway, circular railway users, and non-circular railway users.
If origin of traveler’s status is “True” (calling fall within buffer area) and destination of
traveler’s status is “False” (calling fall outside of buffer area), transit behavior is defined as
circular railway to other mode. If origin of traveler’s status is “False” (calling fall outside ofbuffer area) and destination of traveler’s status is “True” (calling fall within buffer area), transit
behavior is defined as other mode to circular railway. If both origin and destination of traveler’s
status is “False” (both calling fall outside of the buffer area), transit behavior is defined as noncircular railway users. Finally, analyzed data are discussed for future transportation planning ofstudy area.
5. RESULTS AND DISCUSSIONS
Transit behavior of travelers were determined using CDRs data in study area. Table 2 shows
the transit behavior of travelers on weekday and weekend.
Table 2. Transit behavior of travelers
Day

Mode

Other Mode to Circular
Railway (%)
Circular Railway users (%)
Weekday Circular Railway to Other
Mode (%)
Non Circular Railway Users(%)
Other Mode to Circular
Railway (%)
Circular Railway users (%)
Weekend Circular Railway to Other
Mode (%)
Non Circular Railway Users(%)

Time interval
06:00- 09:00- 12:0015:0009:00 12:00 15:00
18:00

18:0021:00

6.68
1.75

7.07
2.10

7.22
2.18

7.34
2.24

6.55
1.87

6.49

7.07

7.22

7.39

6.81

85.08

83.77

83.37

83.03

84.78

5.90

6.38

6.63

6.69

6.16

1.55

1.74

1.76

1.76

1.69

5.92

6.42

6.58

6.75

6.35

86.63

85.46

85.03

84.80

85.80

From this Table, it is found that railway users are around 2 %, other mode to railway users isabout 7 %, circular railway to other mode is also 7 % and non-circular rail users is about over
80 % on weekday. On weekend, railway users are around 2 %, other mode to railway users isabout 6 %, circular railway to other mode is also 6 % and non-circular rail users is about over
80 %. Non-circular railway users are the highest between 06:00-09:00 and 18:00-21:00 interval
New Technologies for Urban Safety of Mega Cities in Asia201

of the day. It can be inferred that public bus and private car/taxis are the primary responsible
for their work trip. But, other remaining transit behavior of users are totally different in thesetime intervals. Weekday and weekend transit behavior are very similar although actual values
are may not be the same.
There are some limitations of CDRs data used in this study. While CDRs data were used in thisresearch, it in tracing location, O-D (Origin-Destination) trips are based on call activities.
Therefore, although people are moving from one place to another place, this trip cannot accountfor a trip if he/she does not use the mobile phone in this analysis. Positions may also changeslightly due to load balancing. And, routes were estimated based on the shortest-path analysis.
Travel distances were measured based on this analysis, and also speeds were calculated using
these distances. This study can be analysed with CDRs data from only MPT is available
although there are three telecommunications in Myanmar such as Ooredoo, Telenor and MPT
services due to difficulties in data acquisition of privacy issues.

6. CONCLUSIONSIn this study, it is found that non-circular railway users are the highest and followed by othermode to circular railway and circular railway to other mode. Other mode to circular railway andcircular railway to other mode users are similar proportions and rail users is the least proportion
among all of transit because of its inconvenience and uncomfortable. In addition, most of thepeople can choose only private car, taxi and public bus to arrive their destination according toroad network as shown in Fig.1. Rail network is provided only circular pattern of urban area
and is not provided north-south and east-west directions across Yangon City. Therefore, newtransit system should be provided to balance the demand and existing transit systems should be
improved to reduce private car usage. If public transport services such as bus and rail can be
improved, many challenges and issues can be solved in urban area of Yangon.
This method can be easily applied for the large population of the large-scale area such ascountry/state/division/township levels. Therefore, it is a cost-effective solution to complement
traditional survey without time consuming. These data are very helpful in the prediction ofpassenger demand for transport services. We hope that this study will help to improve newtransport services of Yangon City traffic planning and public facility management.
As for further studies, the results were validated by Person Trip Survey for Comprehensive
Urban Transport Plan of the Greater Yangon and route trips through road network based on
their mode choice and traffic assignment will also be analyzed to measure traffic congestion ona roadway system.
REFERENCES
Castillo, Enrique del et al. 2008. Trip matrix and path flow reconstruction and estimation basedon plate scanning and link observations, Transportation Research Part B. Vol 42, Issue 5, pp455-481.
G. Rose, 2006. Mobile phones as traffic probes: practices, prospects and issues, Transport
Reviews, vol. 26, no. 3, pp. 275–291.
H. Ishizuka, N. Kobayashi, S. Muramatsu and C. Ono, 2015. Classifying the mode oftransportation using cell tower alignments, Vol. 2015-MBL-74, No. 57, Vol. 2015-UBI-45, No.
57.
Hajek. J. J. 1977. Optimal Sample size of Road-side-interview Origin-Destination surveys (No.
RR 208).

202

Analysis of Transit behaviors using mobile call detail records

December 2019, Yangon, Myanmar

Kyaing, D.; Lwin, K.; Sekimoto, Y. 2017. Human Mobility Patterns for Different Regions in
Myanmar Based on CDRs Data, IPTEK J. Proc. Ser. 2017.
Kyaing, D.; Lwin, K.; Sekimoto, Y. 2017. Estimation of Trip Generation by Using CDRs Data,
Proc. Sep. 2017, volume 11.
Lwin, K., Sekimoto, Y., & Takeuchi, W., 2018. Development of GIS Integrated Big Data
Research Toolbox (BigGIS-RTX) for Mobile CDR Data Processing in Disasters Management,
Journal of Disaster Research, 13(2), 380-386. doi:10.20965/jdr. 2018.p0380.
Lwin, K.K., Sekimoto, Y., Takeuchi, W. 2018. Estimation of Hourly Link Population and Flow
Directions from Mobile CDR, ISPRS-International Journal of Geo-information, 7, 449.
https://doi.org/10.3390/ijgi7110449
Morimura, T., Kato, S., 2012. Statical origin-destination generation with multiple sources, In:
21st International conference on in pattern recognition (ICPR), November 11-15, Tsukuba,
Japan.
Wang, M.H, Schrock, S., Vander Broek, N. and Mulinazzi, T., 2013, Estimating Dynamic
Origin-Destination Data and Travel Demand Using Cell Phone Network Data, International
Journal of Intelligent Transportation Systems Research, Vol 11, N°2, 2013, pp. 76-86
Zin, T.; Kyaing, D.; Lwin, K.; Sekimoto, Y. 2018. Estimation of Originating-Destination Trips
in Yangon by Using Big Data Source, J. Disaster Res. 2018, 13, 6–13.

New Technologies for Urban Safety of Mega Cities in Asia

203

Economic and operational analysis of public
transportation in Pathein township
Emmanuel1 and Kyaing2
1
M.S candidate( Transportation Engineering), Civil Engineering Department,
Yangon Technological University, Yangon, Myanmar
immanuelfalam1995@gmail.com
2
Associate Professor, Yangon Technological University, Yangon, Myanmar,kyaingkyaing63@gmail.com
ABSTRACT

It is essential to have economical public transport mode due to undeniable issue for the current
and future populations. Pathein include one of the most populous cities in Myanmar without
the good quality services of public transportation. The problem of the study area is irregular
headway cause the less reliability on transit system, poor mobility, poor performance quality
in transit operation system. The travel characteristics and willingness-to-pay data werecollected using questionnaires survey at the check points with road side interview in which
random and purposive sampling utilized. Using the data collected from an experimental survey,
analysed with logit model, benefit-cost and net benefit analysis. This study will drive to themore convenience and safety public transportation mode by specific consideration on
economical factors and improvement of operation system. According to willingness to pay ofpeople and peak passenger demand, estimate the suitable headway within 15-20 minutes
operate with fourteen vehicles per day. The route distance will be 28.86 km between Patheinand Kangyidaunk. This study can assist the decision maker to supply the better public
transportation mode for Pathein township and especially helpful for the operators to achieve
the higher benefit by improving the service quality of public transportation.
Keywords: transit, mobility, logit model, benefit-cost analysis, willingness to pay.
1. INTRODUCTION
Transportation plays the important role in the livability of a community the factors that
influence a community's quality of life. Rural residents are more reliant on personally-owned,
single driver automobiles for transportation than their urban counterparts. However, it is
impossible many rural residents are only relying on this mode of transportation. Personalvehicles may be expensive to purchase and maintain, and some residents cannot have drivers'
licenses. Efficient and affordable transportation is the main feature in economic growth in rural
areas and helps ensure that people can obtain services and participate in public life. Public
transportation provides people with mobility and access to employment, community resources,
medical care, and recreational opportunities in their communities. Attracting people to use thepublic bus has never been easy. Private vehicles have typically offered better alternatives thanthe public bus at the cost of environmental problems. The challenge is even greater in rural
areas and small cities where factors such as diverse activity locations, abundant parking lots,

204

December 2019, Yangon, Myanmar

and nonexistence of traffic jams have justified the use of private car as a commuting mode. In
general, factors affecting ridership will be determined by the demand for services, the level ofservice provided, and the cost of service. Demand for services can be estimated based on
population and demographic characteristics. It is expected that demand will be greater in areas
with a higher population and that concentrations of transportation-disadvantaged populations
will create greater demand. In Myanmar, Ayarwady region include one of the high number ofregistered vehicles above five lakh in the year of 2019 meanwhile increasing population. To
protect the negative impact of increase vehicles, public transportation sector include in the vital
portion. The public transportation system in Pathein township operates with the old vehicles
and without any improvement on the performance quality. Therefore, this research will focus
on the improvement of public transit system of the study area.
2. PROBLEM STATEMENT AND OBJECTIVES
2.1 Problem statement
Transit service exists in a dynamic environment, in which changes in passenger demand occur
regularly. Nowadays, the transportation system in Myanmar has been well developed due to therapid urbanization and growing economic prosperity. People can travel smoothly not only local
but also international. Different modes of transport in Myanmar are air transport, rail transport,
road transport and water transport. Currently, road transportation is the main transportation
system such as car, bus, taxi, bike and railway are the main transport alternatives in Patheintownship in which private bicycle and bike is common mode for almost every household. Thiskinds of mix transport system cause congestion on the road especially the area where without
separate bicycle or bike lanes. The public transportation system in Pathein township, operates
with the old age vehicles without any improvement on the performance quality. The impact ofusing old age vehicles affect on travel speed, safety, convenience, more fuel consumption, bodystiffness.
Among the various problem, this study will focus to improve the existing public transportationon the following factors:
1. Unfrequently headway
2. Less regular public transit users
3. Long waiting time during off peak period
4. Overtaking problem during the busiest time
2.2 Objectives
The general objective of this study contain to improve the transit operation system bydetermined regular headway based on peak passengers demand meanwhile reduce the longwaiting time during the off peak period, to investigate the convenience and comfortable transit
mode for the connection of urban and rural area by making economic analysis.
The specific objectives to fulfill the purpose of the study are as follow:
1. To calculate the proper headway for improving transit performance depends on passenger
demand and define the bus fare.
2. To displace the new vehicle to the existing modes
3. To estimate net present value (NPV), for the propose transit mode.
4. To estimate internal rate of return (IRR)
5. To estimate cost-benefit ratio (B/C)

New Technologies for Urban Safety of Mega Cities in Asia

205

3. STAGES OF THE STUDY
In order to achieve the aim and objectives of this research the work is divided according to thefollowing chart can be seen in Figure.
Determine Study Area

Data collection for existing transit operational and performance

Compare transit performance of Dyna and TukTuk

Study three different types of vehicle
specification for transit improvement

Questionnaires to thepassengers’ perceptions

Study Economic characteristics

Data Analysis

Conclusion andrecommendation

Figure: Methodology Flow Chart
3.1 Implementation of the study method
Firstly, determined the study area then made the literature review on transit system and its
operational, economical characteristics. The literature review seek for case studies applied incities of developing countries especially in the cities that have similar conditions. The second
phase related to collect the operational data and the socioeconomic characteristics on theexisting transit modes users around the study scope includes the passengers, drivers, operators
point of views. Chosed the most suitable mode for the study area. The third phase involves
analysed the collected data by logit model to describe the most association variables which
concern with the behavior of the transit users. Compare the performance of existing transit
system. In the fourth phase contain the detailed study for the propose vehicle specification andanalysed according to the operation system. Using the fundamental transportation calculations
and other economical calculation method. Finally, summarized the main findings andconclusion from the study.
3.1.1 Effective Parameters in calculation sample size and benefit-cost analysis
The questionnaire design was developed to collect the data from the following portions;
1. Socioeconomic characteristic of the transit users
2. The existing transit operational performancesn = 𝑁𝑁𝑁𝑁/(1 + 𝑁𝑁𝑁𝑁 𝑒𝑒𝑒𝑒^2 )(1)Where; N is the total populationn is the number of sample size
e is the standard confidence level 95%

206

Economic and operational analysis of public transportation in Pathein townshipDecember 2019, Yangon, Myanmar

Net Present Value (NPV)
Net present value is present value of all future cost and benefits. In this method the stream ofcosts / benefits associated with the project over an extended period of time is calculated and is
discounted at a selected discount rate to give the present value. Benefit are treated as positiveand cost as negative and the summation gives the net present value (NPV). Any project withpositive NPV is treated as acceptable.

Cost benefit Ratio (CBR)

NPV = ∑𝑡𝑡𝑡𝑡

𝐵𝐵𝐵𝐵(𝑡𝑡𝑡𝑡)−𝐶𝐶𝐶𝐶(𝑡𝑡𝑡𝑡)(1+𝑖𝑖𝑖𝑖)^𝑡𝑡𝑡𝑡(2)

Cost benefit ratio is the ratio of total present benefit and the total present cost.
CBR = PB/PC(3)

Discount rate
Discount rate represents the time value of money. Selecting a discount rate is key assumption
for benefit – cost analysis. Higher the rate the tougher it is for a project to be economicallyjustified since costs typically are incurred in early years (and less heavily discounted while
benefits occur over longer timeframe). In discount rate the following risk factors include:(i) the risk free interest rate(ii) tare of inflation. It is measured by either by consumer price index or GDP deflator(iii) market risk, industry risk, firm specific risk, project risk, social risk, political risk, exchange
rate risk.
Internal Rate of Return
To calculate IRR, which allows the discount rate to be varied until it results in a net present
value of 0, such that NPV =0
3.1.2 Effective Parameters in calculation of operational system
Headway is a measurement of the distance or time between vehicles in a transit system. The
minimum headway is the shortest such distance or time achievable by a system without areduction in the speed of vehicles. Headway is a key input in calculating the overall routecapacity of any transit system.
Headway =𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑐𝑐𝑐𝑐𝑆𝑆𝑆𝑆𝑐𝑐𝑐𝑐𝑆𝑆𝑆𝑆𝑐𝑐𝑐𝑐𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑐𝑐𝑐𝑐∗𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑆𝑆𝑆𝑆𝑙𝑙𝑙𝑙 𝑓𝑓𝑓𝑓𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑓𝑓𝑓𝑓∗60(4)𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑝𝑝𝑝𝑝 ℎ𝑙𝑙𝑙𝑙𝑜𝑜𝑜𝑜𝑓𝑓𝑓𝑓 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆

Cycle time is the number of minutes needed to make a round trip on the route, including
layover/recovery time. Cycle time is important for several reasons, including playing a part in
the formula used for determining the number of vehicles needed to provide a given level ofservice on a route.
Cycle Time = 2* Length *60/ Speed(5)

New Technologies for Urban Safety of Mega Cities in Asia

207

4. CASE STUDY
According to collected field data, there were more than fifteen bus stops along the study route
but only the busiest bus stops were used to collect data. Two types of vehicles run on the study
route which are Tuk Tuk and Dyna. Total length of this transit line is about 28 km from theorigin to destination. Female respondents’ interesting is about thirty percent more than malebecause female mostly rely on public transit according to different types of trip purpose.
Generally, the ages between eighteen and thirty years, under eighteen years, above sixty years
are the daily users of public transportation for education trips, work trips, social trips etc. In theweekend, about fourty percent of destination is at the city center of Pathein to go shopping trips.
From about 400 questionnaire data, 92% of respondents agree to change the transit mode to get
the more safety, high speed, low operating costs.
Variables
Occupation
X1
Trip origin from KGD
X2
Trip origin from KK
X3
Waiting time at bus stops
X4
Travel Frequency
X5
Willingness of waiting time reduce X6
Let L= mode change system with Hijet, Bi (i=0, 1, 2, 3, 4, 5,6) are coefficients of the Binary
Logistic Regression model to be estimated from the data. Then according to standard theory oflogistic regression, the value of Logit is given by:
L= ln (odds) = ln (p/1-p) = B0 + B1X1 + B2X2 + B3X3 + B4X4 + B5X5 + B6X6
(6)
Table 1. Variables in the logit equation.
B

S.E.

Wald

df

Sig.

Exp(B)

X1-1.6990.428

15.751

1

0.000

0.183

X2

-1.5

0.497

9.095

1

0.003

0.223

X3

-1.8330.452

16.489

1

0.000

0.160

X4

-0.962

0.497

3.744

1

0.053

0.382

X5

0.97

0.367

6.996

1

0.008

2.638

X6

-1.644

0.584

7.914

1

0.005

0.193

Constant

2.224

1.044

4.537

1

0.033

9.248

The equation of the logistic regression line is given by:
L = 2.224 – 1.699 X1 - 1.5 X2 - 1.833 X3 - 0.962 X4 - 0.97 X5 –1.644 X6(7)

The main findings of this mode change (Hijet) analysis are; strongly association of transit modechange for students’ occupation and passengers from Kankone and Kangyidaunk residents,
significant association on the travel frequency and waiting time at bus stops of the current transit
system and people who willingness to reduce waiting time at bus stop.

208

Economic and operational analysis of public transportation in Pathein townshipDecember 2019, Yangon, Myanmar

5. DETAIL CACULATION OF NPV AND BENEFIT-COST RATIO
According to the described equations, net present value, cost-benefit ratio, internal rate of return
will calculate for the transit improvement of the study. The cost will be considered with
Myanmar kyats.
Description of project characteristic and cost for one vehicle per year;
Assumptions;
Discount rate = 17%
Fixed cost per vehicle include: purchase cost = 9,500,000 MMK
License registration fees = 200,000 MMK
Annual variable costs for one vehicle;
Commercial license = 96,000 MMK /year
Maintenance cost = 360,000 MMK /year
Engine oil cost = 379,218 MMK /year
Fuel consumption rate per year = 3717 liters= 870 MMK/ liter= 3,233,790 MMK
Driver wages = 200000 MMK/month = 2,400,000 MMK /year
Gate fees = 1000 MMK/day = 36,500 MMK/year
Milliage depreciation cost (life time for pickup truck 5 years) = 1,900,000MMK
Insurance rate = 1.7% *purchase = 161,500MMK
Assume revenue only from bus fare ;Hijet car capacity= 11 persons
Bus fare= 300 kyats/trip
Number of round trips= 6 trip/day
Number of operating vehicles =14veh/day
Capacity factor= 0.8
Total revenue=11 x 14 x 300 x 6 x 0.8 x 365 = 80,942,400 MMK/year
Concept of fuel,17 km = 1 litre
Travel distances= 173.16 km/day= 63203 km/year
Concept of engine oil cost calculations,
Assume, the engine oil must be refill after every five thousand kilometer used.
5000 km = 30,000 kyats
So, 1 km = 6 MMK,For 63203km, engine oil cost =379,218 kyats/year
Assume: capital cost include all fixed cost.
Annual variable cost include:(1) Commercial license,(2) Maintenance cost,(3) Engine oil cost,(4) Fuel cost,(5) Driver wages,(6) Gate fees,(7) Milliage depreciation cost,(8) Insurance rate.
The ridership for origin to destination is 1.5 times the capacity depends on the following
reasons: (1) many villages along the study route, (2) boarding and alighting at the villages.

New Technologies for Urban Safety of Mega Cities in Asia

209

Table 2. The investment cost and benefit estimation
Year

Investment or Cost(C)

Profit or Benefit(B)

Net Benefit( B-C )

PV factor
1/(1+i)^t

PV

MMK (164,900,000)

1.0000MMK (164,900,000)

0MMK164,900,000 MMK

-

1

MMK

124,537,140 MMK

165,564,000 MMK

41,026,860

0.8547

MMK

35,065,692

2

MMK

124,537,140 MMK

165,564,000 MMK

41,026,860

0.7305

MMK

29,970,677

3

MMK

124,537,140 MMK

165,564,000 MMK

41,026,860

0.6244

MMK

25,615,963

4

MMK

124,537,140 MMK

165,564,000 MMK

41,026,860

0.5337

MMK

21,893,986

5

MMK

124,537,140 MMK

165,564,000 MMK

41,026,860

0.4561

MMK

18,712,808

6

MMK

124,537,140 MMK

165,564,000 MMK

41,026,860

0.3898MMK

15,993,853

7

MMK

124,537,140 MMK

165,564,000 MMK

41,026,860

0.3332

MMK

13,669,960

8MMK124,537,140 MMK

165,564,000 MMK

41,026,860

0.2848

MMK

11,683,727

MMK

1,161,197,120 MMK 1,324,512,000 MMK 163,314,880

MMK

7,706,667

TOTAL

NPV =
B/C =
IRR =

Discount rate
20%
17%
IRR

7,706,667 MMK
1.14
18.5%
Table 3. Internal rate of return estimation
NPV(28,325,219.68) MMK
7,706,667 MMK
18.50%

6 DISCUSSION AND CONCLUSION
6.1 Discussion
According to the economic analysis, the result net present value is positive with discount rate
17%. It means the project is acceptable. The benefit-cost ratio is greater than 1 with 17%
discount rate. So that this investment for mode change with Hijet should accept to get healthy
and good public transportation system in Pathein township especially around the study area.
6.2 Conclusion
Based on the survey result, females are more interesting on questions. The most users’
occupation is student because the study route location pass through more than five basic schools
and universities in Pathein township. The data shows the trip purpose of other transit users
include, recreational trip, work trip, shopping trip, social visit, education trip etc. Among these,
education trip is the most significant trip depends on the data collection.
In the collected data the most of respondent do not need to wait the long period during
peak hour but the long waiting time during off peak hours. From this research, estimated theproper headway for peak period and off peak period to solve long waiting time. The willingness

210

Economic and operational analysis of public transportation in Pathein townshipDecember 2019, Yangon, Myanmar

to pay for the mode change to Hijet vehicle was 300 kyats that is the most significant value thepassenger want to pay per trip.
The result of this data the peak passenger volume is 122 per hour so that fourteen
vehicles need to operate daily with 15-20 min headway during peak and off period. The travel
speed range is between 30 – 50 km/hr considered for both urban road and rural area road.
Moreover, according to the people travel characteristics, socioeconomic factors, theirperception on the existing transit system, most of people would like to mode change with reduce
not only bus fare but also waiting time at bus stops. So that to solve the current problem, thevehicle should be good fuel efficiency, high speed, drive safely and faster than the existing
mode. In order to fulfill this option the Hijet vehicle is proposed from this research.
REFERENCES
D.Bharathan, L Chaney, R.B. Farrington, J. Lust bader, M.Keyser, and J. Rugh. An overview
of vehicle test and analysis from NREL’S AIC fuel use reduction research.
Elana S. Prassas, Roger P.Roess. Engineering economics and finance for transportation
infrastructure. Springer tracts on transportation and trafﬁc STTT.
John Wiley and Sons, Inc., Hobokon, New Jersey. Urban transit systems and technology.
Published simultancously in Canada.
Jeremy Mattson. Estimating Ridership of Rural Demand-Response Transit Services for the
General Public. National Center for Transit Research
Rakesh Bewal. People’s perception of public transport services in Oman.
https://www.researchgate.net/ publication/260190662
Steve Abley, Paul Durdin and Malcolm Douglass (2010). Integrated Transport Assessment
Guidelines, Report 422, Land Transport New Zealand (www.nzta.govt.nz); at
www.nzta.govt.nz/resources/research/reports/422.
Todd Litman. Transportation cost and benefit analysis: techniques, estimates and implications.
https://www.researchgate.net/ publication/ 235360398
Utpal Dutta. A Framework to Identify Economic and Community Benefits of the Proposed BRT
System in Southeast Michigan. Copyright © 2017 by author and Scientific Research Publishing
Inc. Published: June 12, 2017.
American Association of State Highway and Transportation Officials (2010). A Manual ofUser Benefit Analysis for Highways, 3rd Edition.
https://bookstore.transportation.org/collection_detail.aspx?ID=65.
Basic Speed/Fleet Size Relationships. H:\Projects\Transit course\Fleet relationships.doc
11/14/2006

New Technologies for Urban Safety of Mega Cities in Asia

211

ANALYSIS ON THE EFFECT OF LAND USE AND SOCIOECONOMIC CHARACTERISTICS ON
TRAVEL BEHAVIOR
T. AUNG1, KYAING2, K.K. LWIN3, and Y. SEKIMOTO4
Ph.D. Candidate, Department of Civil Engineering, Yangon Technological University, Yangon, Myanmar,
Associate Professor, Department of Civil Engineering, Yangon Technological University, Yangon, Myanmar,
3
Project Assistant Professor, IIS, The University of Tokyo, Tokyo, Japan,
4
Associate Professor, IIS, The University of Tokyo, Tokyo, Japan,
1

2

Keywords: land use, socioeconomic, modal split, commuting distance, multiple linear regression.
1. INTRODUCTION
Yangon, the former capital of Myanmar and the capital
city of Yangon region is located in lower Myanmar at theconvergence of the Yangon and Bago Rivers about
30 km(19 mi) away from the Gulf of Martaban. It has the
population of over five million in urban areas and the City
has an area of about 600 square kilometers. Therefore, thepopulation density of Yangon City in urban area is about
8600/km2. As many people from the rural areas and otherregions come to Yangon City for their better life andopportunities, the population and the city area have grownsignificantly since 1948. Due to these rapid growths inpopulation and urban structure, debates around urban
form sustainability have grown and focus on the shape andsize of cities, their relationships with daily travel patterns
and solutions to the challenges of urban sprawl anddecentralization. This study aims to investigate the effectof land use and socioeconomic effect on the travel
behaviors of Yangon city. To evaluate the effect of land
use and socioeconomic factors on travel behaviors,socioeconomic attributes, land use attributes and trip
attributes provided from JICA (Japan International
Cooperation Agency) Survey (2014) were used. By using
multiple regression model based on these data, it can be
examined how journey to work travel behavior is affectedby land use and socioeconomic factors.
2. METHODS OF ANALYSIS
Modal split (public transportation and private car usage)
were used as transport performance indicators toinvestigate the interaction between travel behavior andland use for journey to work. Journey to work is chosenbecause it is strongly influenced by mode choice and it iseasier to undertake due to its regularity and adjustment.
Two dependent variables were analyzed by using multiple
linear regression in SPSS software according to
independent variables, including socioeconomic index forareas (SEIFA), income, occupation, population density,
distance from CBD and car ownership. The
socioeconomic data, land use data and transport data werecollected from JICA survey which took place in 2014. In
Yangon City, the main modes of transport are private cars
and buses.
3. RESULTS AND DISCUSSIONS
According to this study, it was found that the mainmode used for intra trips in all areas except New Suburb

212

region is the walking mode and in New Suburb region,other modes such as motorcycle and bicycles are the mainmodes. People mostly use buses for inter-zonal trips andthe second most mode is private car and taxi in CBD areas,
inner city and outer city areas.
The factors affecting the usage of private car and public
transportation are analyzed by using multiple regression
model and the influenced factors for both modes areshown in Table.1.
Table.1. Regression Analysis for Public Transportation
and Private Car Usage
Public Transportation
Private Car
Variables
Coefficient
Variables
Coefficient
Constant-2.450Constant
1.683
CBD
Bluecollar
0.337-0.094
Distance
Whitecollar
0.821
Pop Density-0.051
Low HH
Low HH
0.333-0.112
IncomeInome
2 Cars+-0.9702 Cars+0.713
Adjusted R2
0.957
Adjusted R2
0.852
Based on these results, it can be found that low income
households mostly use public transportation rather thanthe private car and taxi while the households which own
more than two private car prefer to use private car as it has
positive relationship with private car. The blue collar staff
and white collar staff prefer to use public transportation as
it can reduce the cost of the travel.
3. CONCLUSIONS
From this analysis, it can be found the factors which
influenced the travel behaviors and by promoting the
public transport facilities and network, it will be aremedial measure to reduce the traffic congestion on roads.
REFERENCES[1] Wegener, M., and Fuerst, F. (2004): Land-Use
Transport Interaction: State of the Art. SSRN Electronic
Journal.10.2139/ssrn.1434678.
[2] Alqhatani, M., Bajwa. S., and Setunge, S., (2012).
“Land Use Transport Interaction: A Comparison of
Melbourne and Riyadh.” The 8th International
Conference on Traffic and Transportation Studies,
Changsha, China, procedia - social and behavioral
sciences 43, pp, 3-13.

Optimization Model to Estimate
Cognitive Distances for Cognitive Maps
from Travel Data

Hiroyuki HASADA1 and Yudai HONMA2
1
Graduate Student, Graduate School of Engineering, the University of Tokyo, Japan
hasada-hiroyuki649@g.ecc.u-tokyo.ac.jp
2
Associate Professor, ICUS, IIS, the University of Tokyo, Japan
ABSTRACTMaps are critical elements for us to recognize a travel distance between two arbitrary
points. In fact, we utilize a variety of maps, such as map-apps or route-maps, to travel as
efficiently as possible. On the other hand, such "best" route, which we believe it is theshortest, frequently contains some errors because of the accuracy of maps or thelimitation of our recognition. From this point of view, many earlier studies discussed
cognitive distances on mental maps, but it is difficult to measure them quantitatively fromlarge amount of data. In this study, we propose a new optimization model to estimate
cognitive distances from travel data. The travel data contains route information, and it
can be regarded as a result of their best selection in mind. Conversely, it must be possible
to estimate cognitive distances that their choice becomes the best as a result. Based on
this idea, we fix a network topology and prepare variables for each link to express
cognitive distances. The objective function of our model is to minimize the difference
between the graph-distance of the selected route and that of the shortest path. For
numerical examples, we solved the problem on small networks and verified the accuracyof estimation by fluctuating the correct distance. This study has great potential; we canreflect our activities to market areas and urban planning with obtained cognitive
distances in an area, or we can illustrate cartograms based on them. Solving our problem
in large networks and real travel data, including probe data, is essential future work.
Keywords: cognitive distance, travel data, optimization, cartogram
1. INTRODUCTION
When we go to a destination, we don’t always go along the shortest route a map indicates.
For example, we often take a detour to avoid stairs and steep slopes. We sometimes takea familiar route, not unfamiliar one off the beaten path. These behavior shows that theimage of a city we have is distorted from an ordinary map. The goal of our study is toobtain and visualize this distorted image.
One of methods to show distortions of cities, many what we call time-space maps, suchas maps by Sugiura (2014), were made. Most of the time-space maps were made bydrawing isolines in or distorting original maps in terms of only travel time from a point(Shimizu, 1992). It is comparatively easy to make these time-space maps, but travel time
between any points are ignored in these maps. On the other hand, some studies, such as
by Kilchenmann (1972), located points on a two-dimensional plane in terms of travel time
between any points, by using Multi-Dimensional Scaling (MDS). Since the distances213

December 2019, Yangon, Myanmar

shown in these studies focus on travel time, objective data, the distances are contrast to
subjective distances in our image of cities.
In addition, many studies, such as by Lynch (1960), obtained distances between points
and image of space we recognize. According to Montello (1991), methods to measurecognitive distances are broadly divided into five classes: psychophysical ratio scaling,
psychophysical interval and ordinal scaling, mapping, reproduction and route choice.
Studies have used an appropriate class of methods to purpose of the studies and data.
Psychophysical ratio scaling and psychophysical interval and ordinal scaling are methods
to measure the distances participants themselves express cognitive distances at the ratio,
interval or ordinal level. For example, Katayama et al (2001) used psychophysical ratio
scaling in order to identify some factors of physical environment that influencepedestrian’s cognitive distances. Mapping is a method to regard distances between points
on the maps, what we call mental maps, that participants draw as cognitive distances. Xu
et al (2001) measured cognitive distances in a simulated circulated space with this method
after participants walk in the space. Reproduction is a method to measure the distancesthat participants reproduce target distances on a straight line. Yanase et al (2006)
measured cognitive distances generated by ascending and descending stairs with thismethod. The above four classes of methods have a problem that it is difficult to obtaindata from many participants, because these methods put a great strain on them. Routechoice is a method to measure an ordinal scale of cognitive distances on the basis of route
choice data. This method has the assumption that humans usually choose to travel along
the shortest routes which they believe require the least effort. This method needs route
choice data of subjects and puts a little strain on them. This is the reason why it iscomparatively easy to measure cognitive distances many subjects have. However, Gärling(1988) pointed the problem that humans should choose routes which require the least
effort in terms of not only cognitive distances but also other factors like costs.
The purpose of this study is to propose an optimization model to estimate cognitive
distances from route choice data, travel data, and visualize cognitive maps as distancecartograms. We define cognitive distances as subjective distances derived from data of
our actual movement. The cognitive distances we define express accessibility in cities
determined by various factors such as psychological cognitive distances and cost.
Although the cognitive distances we define have the problems from the point of view ofpsychology, the cognitive distances and the cognitive maps from them can show ourimage of cites distorted from ordinary maps.
Few studies are available that show methods to compute cognitive distances from big
travel data. In this study, we verify accuracy of the model we propose by using large
amount of hypothetical travel data. This study contributes to computation of cognitive
distances from large amount of actual travel data. Since it become much easier to obtainbig travel data than before due to recent development of information and communication
technology, this model is useful for expression of image of cities many people have. This
image not only shows aspects and characteristics of cities but also enables us to design
cites adapted to our movement and sense. For example, location of public facilities andstores can be made more appropriate on the basis of this image. In addition, since thismodel can be applied to any scale of space, this model is useful for expression of imageof interior space of buildings. The image of interior space has not been so available andcan be utilized for better building layouts.

214

New Technologies for Urban Safety of Mega Cities in Asia

2. OPTIMIZATION MODEL
The optimization model we propose has the following three assumptions. The first
assumption is that travelers move on a network composed of nodes and links. This meansthat this model can be applied to not only cities but also buildings, for example, by
regarding rooms as nodes. The second assumption is that all travelers go along the path
which they believe is shortest in terms of cognitive distances. This means that travelers
sometimes make a detour in terms of actual distances. The third assumption is thatcognitive distances does not depend on travelers. In other words, all travelers recognize
the same set of cognitive distances corresponding to the links. Although in fact cognitive
distances vary a little between travelers, they have a common tendency as Lynch (1960)
described. Lynch emphasized the importance to see “public image” of cities. The
tendency of the cognitive distances is certainly the “public image” distorted from maps.
The optimization model is formulated with two design goals. The first goal is to make thepath where a traveler moves in fact on each travel shortest in terms of cognitive distances,
based on the second assumption. This goal is incorporated by minimizing difference interms of cognitive distances between the length of the path where each traveler moves
and the length of the shortest path from origin to destination. The second goal is to makea cognitive distance of a link closer to an actual length. This goal comes from the property
of cognitive distances estimated from travel data. Since travel data determines only an
ordinal scale of cognitive distances, it is necessary to determine a numeric scale in order
to visualize a cognitive map. In this model, the value which changes smallest from an
actual distance is calculated as the cognitive distance of each link, because cognitive mapon the basis of this shows the least extent of distortion of “public image” distorted from
maps. Formulation of the model is as follows and notation defined for this model follows.
Minimizesubject to

𝑝𝑝𝑝𝑝

𝑀𝑀𝑀𝑀 � 𝑤𝑤𝑤𝑤 𝑝𝑝𝑝𝑝 � � 𝑥𝑥𝑥𝑥𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑟𝑟𝑟𝑟𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 − 𝑢𝑢𝑢𝑢𝑜𝑜𝑜𝑜(𝑝𝑝𝑝𝑝)δ(𝑝𝑝𝑝𝑝) � + � �𝑟𝑟𝑟𝑟𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 − 1�
𝑝𝑝𝑝𝑝∈𝑃𝑃𝑃𝑃(𝑖𝑖𝑖𝑖,𝑖𝑖𝑖𝑖)∈𝛱𝛱𝛱𝛱𝑢𝑢𝑢𝑢ℎ𝑖𝑖𝑖𝑖 − 𝑢𝑢𝑢𝑢ℎ𝑖𝑖𝑖𝑖 ≤ 𝑙𝑙𝑙𝑙𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑟𝑟𝑟𝑟𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
𝑢𝑢𝑢𝑢ℎ𝑖𝑖𝑖𝑖 ≥ 0
𝑢𝑢𝑢𝑢ℎℎ = 0
𝑟𝑟𝑟𝑟𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 > 0

Indices𝑝𝑝𝑝𝑝
index of travelsℎindex of origin nodes on travels
𝑖𝑖𝑖𝑖, 𝑗𝑗𝑗𝑗
indices of nodes

Sets
𝑃𝑃𝑃𝑃
𝛱𝛱𝛱𝛱
𝑁𝑁𝑁𝑁
O

(𝑖𝑖𝑖𝑖,𝑖𝑖𝑖𝑖)∈𝛱𝛱𝛱𝛱

2∀ℎ ∈ 𝑂𝑂𝑂𝑂, (𝑖𝑖𝑖𝑖, 𝑗𝑗𝑗𝑗) ∈ 𝛱𝛱𝛱𝛱∀ℎ ∈ 𝑂𝑂𝑂𝑂, 𝑖𝑖𝑖𝑖 ∈ 𝑁𝑁𝑁𝑁∀ℎ ∈ 𝑂𝑂𝑂𝑂∀(𝑖𝑖𝑖𝑖, 𝑗𝑗𝑗𝑗) ∈ 𝛱𝛱𝛱𝛱

(1)
(2)
(3)
(4)
(5)

set of travels
set of links
set of nodes
set of origin nodes on travels

Variables
𝑟𝑟𝑟𝑟𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
a ratio of a cognitive distance between nodes i and j to an actual length 𝑙𝑙𝑙𝑙𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
Optimization Model to Estimate Cognitive Distances for Cognitive Maps from Travel Data

215

December 2019, Yangon, Myanmar

𝑢𝑢𝑢𝑢ℎ𝑖𝑖𝑖𝑖
potential (= path length) of node 𝑖𝑖𝑖𝑖,which origin is a node ℎParameters
𝑀𝑀𝑀𝑀
a big penalty to prioritize determination of an ordinal scale of cognitive distances
𝑤𝑤𝑤𝑤 𝑝𝑝𝑝𝑝
weight of travel 𝑝𝑝𝑝𝑝
𝑝𝑝𝑝𝑝
𝑥𝑥𝑥𝑥𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
1 if a traveler on travel p pass a link between nodes 𝑖𝑖𝑖𝑖 and 𝑗𝑗𝑗𝑗, 0 otherwise
𝑙𝑙𝑙𝑙𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
an actual length of a link between nodes 𝑖𝑖𝑖𝑖 and 𝑗𝑗𝑗𝑗
𝑜𝑜𝑜𝑜(𝑝𝑝𝑝𝑝) an origin node on travel 𝑝𝑝𝑝𝑝
𝛿𝛿𝛿𝛿(𝑝𝑝𝑝𝑝) a destination node on travel 𝑝𝑝𝑝𝑝

The first term of objective function (1) minimizes the difference in terms of cognitive
distances on each travel between the path length where each traveler moves and theshortest path length. The path length where each traveler moves is obtained to calculate
𝑝𝑝𝑝𝑝
the sum of only the link length which the traveler pass in fact. 𝑥𝑥𝑥𝑥𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑙𝑙𝑙𝑙𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑟𝑟𝑟𝑟𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 is the length of thelink between nodes 𝑖𝑖𝑖𝑖 and 𝑗𝑗𝑗𝑗 in terms of cognitive distances if the link is passed, and 0
otherwise. The shortest path length is obtained in a variable 𝑢𝑢𝑢𝑢𝑜𝑜𝑜𝑜(𝑝𝑝𝑝𝑝)𝛿𝛿𝛿𝛿(𝑝𝑝𝑝𝑝) by using the dualof the shortest path problem. Formulation of the dual is shown below and is the LP to
maximize potential 𝑢𝑢𝑢𝑢ℎ𝑘𝑘𝑘𝑘 of destination node 𝑘𝑘𝑘𝑘,which origin is an origin node ℎ, in the
network. The difference between potential of node 𝑖𝑖𝑖𝑖 and node 𝑗𝑗𝑗𝑗 is always no more thanthe path length 𝑙𝑙𝑙𝑙𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 between the nodes, where constraints (7) hold. Therefore, maximizing
𝑢𝑢𝑢𝑢ℎ𝑘𝑘𝑘𝑘 is equivalent to finding the greatest lower bound for the length of the shortest pathfrom origin to destination. In the first term of objective function (1), the shortest path
lengths are obtained by minimizing −𝑢𝑢𝑢𝑢𝑜𝑜𝑜𝑜(𝑝𝑝𝑝𝑝)δ(𝑝𝑝𝑝𝑝) . Constraints (2) — (4) correspond toconstraints (7)—(9). M is a penalty large and used in objective function (1) to prioritize
minimizing the differences between the path lengths where travelers move and theshortest path lengths. This is because determination of an ordinal scale of cognitive
distances from travel data is prior to determination of a numeric scale.
Minimizesubject to𝑢𝑢𝑢𝑢ℎ𝑖𝑖𝑖𝑖 − 𝑢𝑢𝑢𝑢ℎ𝑖𝑖𝑖𝑖 ≤ 𝑙𝑙𝑙𝑙𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
𝑢𝑢𝑢𝑢ℎ𝑖𝑖𝑖𝑖 ≥ 0
𝑢𝑢𝑢𝑢ℎℎ = 0

𝑢𝑢𝑢𝑢ℎ𝑘𝑘𝑘𝑘(6)∀(𝑖𝑖𝑖𝑖, 𝑗𝑗𝑗𝑗) ∈ 𝛱𝛱𝛱𝛱∀𝑖𝑖𝑖𝑖 ∈ 𝑁𝑁𝑁𝑁

(7)
(8)
(9)

The second term of objective function (1) minimizes the square of the difference on eachlink between 1 and a ratio of a cognitive distance to an actual length. The reason why theratio is used is to evaluate distortions of long links and short links equally.
3. VERIFICATION METHODS
3.1 Materials
To verify accuracy of the model we propose, we prepared an idealized network of a city.
The network consists of 25 nodes and 43 links (Figure 1). The nodes are given position
coordinates and actual lengths of the links are given Euclidian distances of end nodes.
We generated hypothetical travel data in the following three steps. Step 1: we changed
the actual length of each link at random. These changed lengths are equivalent to public

216

New Technologies for Urban Safety of Mega Cities in Asia

image of the network. Each of the changed lengths are obtained by multiplying a random
number which follows a gamma distribution. An average of the distribution is 1 and a

Figure 1: Idealized network composed of 25 nodes
variance is 0.5. Step 2: we generated pairs of origin and destination nodes at random. The
number of the O-D pairs is parametric in order to verify whether the model can be applied
to large amount of travel data. We set the values of the number of the pairs to 10, 100 and
1000, and repetitions of the pairs are allowed. Step 3: we obtained the shortest path, travel
data, in the network composed of the changed lengths for each of the O-D pairs generated
by using Dijkstra method. In this study, weights of all travels are 1.
3.2 Verification from three points of view
We verify accuracy of the model from three points of view: lengths of the links, travel
data and cartograms. In terms of lengths of the links, we estimate lengths of the links,
which are equivalent to cognitive distances, from the hypothetical travel data by using the
optimization model and compare the estimated lengths and the changed lengths, whichwere used to generate the hypothetical travel data. In terms of travel data, we generate
travel data in the network which links have the estimated lengths. We obtain the shortest
path for each of the O-D pairs which were used to generate the hypothetical travel data
by using Dijkstra method. We compare the travel data generated in the changed andestimated networks. In terms of cartograms, we visualize the changed and estimatednetwork as cognitive maps. We use metric MDS to locate nodes on a two-dimensional
plane. Metric MDS is optimization problem designed to approximate given dissimilarities
𝑡𝑡𝑡𝑡𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 , the shortest path lengths between any nodes in this study, to direct distances 𝑑𝑑𝑑𝑑�𝚤𝚤𝚤𝚤𝚤𝚤𝚤𝚤
between any located nodes on a two-dimensional plane and minimize called stress 𝜎𝜎𝜎𝜎
defined as shown in (10) (Leeuw, 2009). We solve this problem by using SMACOF(Scaling by MAjorizing a COmplicated Function). We compare obtained cartograms
visualizing the changed and estimated networks.
2
𝜎𝜎𝜎𝜎 = � �𝑡𝑡𝑡𝑡𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 − 𝑑𝑑𝑑𝑑�𝚤𝚤𝚤𝚤𝚤𝚤𝚤𝚤 �(10)𝑖𝑖𝑖𝑖<𝑖𝑖𝑖𝑖∈𝑁𝑁𝑁𝑁

Optimization Model to Estimate Cognitive Distances for Cognitive Maps from Travel Data

217

December 2019, Yangon, Myanmar

Figure 2 shows the flowchart of verification methods explained above. We verify
accuracy of the model by generating O-D pairs at random 10 times where the number of
O-D pairs is each value.

Figure 2: Flowchart of verification methods

Figure 3: Changed and estimated lengthsof links (10 O-D pairs)

Figure 4: Changed and estimated lengthsof links (100 O-D pairs)

Figure 5: Changed and estimated lengthsof links (1000 O-D pairs)

Figure 6: Match rate of travel data where
10, 100 and 1000 O-D pairs

4. RESULTS
Figure 3, 4 and 5 show comparison of lengths of the links. Figure 3, 4 and 5 are scatterplots of the changed and estimated lengths of the links in the 10 times estimations where
the number of the generated O-D pairs is 10, 100 and 1000. In these figures, dashed lines
show that changed length equal to estimated length and points near the dashed lines mean

218

New Technologies for Urban Safety of Mega Cities in Asia

that lengths are estimated well. We obtained the result that the model we proposed
estimates cognitive distances relatively well. In addition, as the amount of travel data islarge, the accuracy of the estimation improves a little.

Figure 7: Cartogram visualizing changed
network

Figure 8: Cartogram visualizing estimatednetwork (10 O-D pairs)

Figure 9: Cartogram visualizing estimated Figure 10: Cartogram visualizing estimatednetwork (100 O-D pairs)
network (1000 O-D pairs)
Figure 6 show comparison of travel data. This figure is a box plot of match rate of travel
data where the number of the generated O-D pairs is 10, 100 and 1000. In this study,
match rate of travel data is defined as a ratio of the number of the O-D pairs where theshortest paths are the same in the changed and estimated networks to the total number of
O-D pairs. We obtained the result that travel data reproduced is relatively correct. In termsof not matched travels, the shortest paths are just a little different but have the almost
same distances.

Optimization Model to Estimate Cognitive Distances for Cognitive Maps from Travel Data

219

December 2019, Yangon, Myanmar

Figure 7 to Figure 10 show cartograms. Figure 7 is a cartogram visualizing the changed
network. Figure 8, 9 and 10 are cartograms visualizing the estimated networks where thenumber of the generated O-D pairs is 10, 100 and 1000. We obtained the result thatcartograms visualizing the estimated networks, estimated cognitive map, become closer
to a cartogram visualizing the changed network, correct cognitive map, where the amountof travel data is large. In these cartograms, node 23, 24 and 25 are far from the others
because travels from these nodes to the others always have much longer path lengths thandirect distances.
5. CONCLUSIONSThis study proposed the optimization model to estimate cognitive distances from travel
path data. This model is designed to make the path where a traveler moves shortest on
each travel in terms of cognitive distances and then make cognitive distances closer toactual lengths of the links. In addition, we demonstrated the usefulness of thisoptimization model. We verified the accuracy of this model from three points of view:
lengths of the links, travel data and cartograms. Although we used an idealized networkand hypothetical travel data, this verification is enough to show that this model enables
us to estimate cognitive distances and cognitive maps visualizing our distorted image ofcites from only travel data. When further studies estimate cognitive maps with this modelfrom real big travel data captured with positioning system such as GPS, realcharacteristics of cites are visualized and the usefulness of this model will be shown more.
In addition, this model has the possibility to express image of interior space of buildings
and contribute to realization of cites and buildings adapted to our movement and sense.
REFERENCES
Cadwallader, M., 1975. A Behavioral Model of Consumer Spatial Decision Making.
Economic Geography 51, 339-349.
Katayama, M., and Ohno, R., 2001. A Study of Pedesrian’s Cognitive Distance of acommuting Route. The Architectural Institute of Japan’s Journal of Architecture andPlanning 66(549), 193-198.
Leeuw, D. L. and Mair, P., 2009. Multidimensional Scaling Using Majorization:
SMACOF in R. Journal of Statistical Software, 31(3), 1-30.
Lynch, K., 1960. The image of the city. MIT press, Massachusetts.
Gärling, T., and Gärling, E., 1988. Distance minimization in downtown pedestrian
shopping. Environment and Planning A, 20(4), 547-554.
Montello, R. D., 1991. The measurement of cognitive distance: Methods and constructvalidity. Journal of Environmental Psychology 11(2), 101-122.
Okamoto, K., 1982. A Review of Cognitive Distance Studies. Japanese Journal of
Human Geography 37(5), 429-448.
Shimizu, E., 1992. Time-space Mapping and Its Application in Regional Analysis.
Infrastructure Planning Review 10, 15-29.
Sugiura, K., 2014. Folds of Time, Wrinkles of Space… Attempts to Make [Time-SpaceMaps] (in Japanese). Kajima Institute Publishing, Tokyo.
Xu, H., Matsushita, S., and Nishide, K., 2001. Characteristics of Cognitive Maps:
Simulation study on pedestrian path choice and spatial cognition (Part II). The
Architectural Institute of Japan’s Journal of Architecture and Planning 66(545), 173-179.

220

New Technologies for Urban Safety of Mega Cities in Asia

Yanase, R., and Sakita, M., 2006. A Study on Cognitive Distance Generated byAscending and Descending Stairs: Fundamental study for the spatial planning of largescale architecture based on a distance Part2. The Architectural Institute of Japan’s
Journal of Architecture and Planning 71(601), 33-38.

Optimization Model to Estimate Cognitive Distances for Cognitive Maps from Travel Data

221

Mathematical Relationship between
Minimization of Travel-time and Detouring Behavi
or on Grid Networks:
A Case Study of Yangon Downtown
Yudai HONMA1 and Kimiro MEGURO2
Associate Professor, ICUS, IIS, the University of Tokyo, Japan
yudai@iis.u-tokyo.ac.jp
2
Professor, Director of ICUS, ICUS, IIS, the University of Tokyo, Japan
1

ABSTRACTThe downtown of Yangon-city is a typical grid-like network, and it is a very congested
area in terms of both blocks and streets. In this study, we focus on the mathematical
relationship between the shortest time route and deviation behavior on grid networks andclarify the fact that the bottlenecks in secondary streets would be serious elements to
reduce the network's potential in downtown Yangon. Road patterns of Yangon-city
downtown are tricky because the traffic capacity of north-south streets and that of eastwest streets are quite different. Lots of secondary North-South streets are much narrower
than arterial East-West streets. This capacity difference makes the traveler incur a longer
distance. The mechanism of this phenomenon is as follows. (i) travelers try not to use
secondary North-South streets as much as possible. (ii) This principle makes traveler
detour from the shortest-distance route. (iii) Such deviation behavior accelerates the flow
volume increase of streets. What we emphasize though the study is that significant
unbalance of streets would accelerate further traffic congestions.
Keywords: downtown Yangon, grid network, deviation, bottleneck
1. INTRODUCTION
Yangon city, Myanmar, has large road networks that are crowded with traffics. Notably,
the downtown area in Yangon city always suffers heavy traffics, and we need a long time
to move within the area. The road network in the downtown area is a typical grid-likenetwork with hierarchical road types, and it is difficult to move smoothly on the secondary
narrow streets. Apparently, the reason is huge illegal parking cars in the street by road
users. It is essential to clarify how these undesirable behaviors make worse the potentialof the Yangon road network.
There are two most common measures to evaluate the ability of road networks, “travel
distance” and “flow volume” (Vaughan 1987). It should be noted that travel distances andflow volumes have clear theoretical relationships (Koshizuke 1999). Precisely to say, as
travel distances in an area become longer, flow volumes also become larger. It is natural
because both measures indicate the activeness of movement. Therefore, there are plentyof earlier studies which focus on distances and/or flow volumes on road networks. For
example, Fujita and Suzuki (2003) focus on the idealized circular-radial network andanalytically derive both average distance and flow volumes. Meanwhile, there are otherstudies that assume other types of networks. One example of a grid network would be222

December 2019, Yangon, Myanmar

held by Koshizuka (1996), and the analysis based on Euclidian distance was done by
Ghosh (1951). Furthermore, Kurita (2001) assumed a circular disk city and compared
several types of idealized road patterns. Similarly, Ukai and Toriumi (2017) defined ndirectional distance and theoretically analyze the distance distribution in a circular region.
Likewise, Miyagawa (2014) has assumed hierarchical road networks in his studies.
In this research, we focus on both distance and flow volumes on the road network in
downtown Yangon. We explicitly consider the hierarchical structure of the road networkand consider the difference in travel speed between arbitral streets and secondary streets.
Then, we calculate the distance of the shortest-time route in various speed settings. These
calculations clarify that unfavorable deviation behaviors increase as the speed of
secondary roads decreases. All of These results points out the fact that the bottlenecks insecondary streets would be serious elements to reduce the network's potential in
downtown Yangon.
2. FORMULATION
2.1 Basic Concepts
First, we explain about grid network. The glid network can be categorized as one of theroad metrics. As another typical road metrics, there is the circular-radius network. As
shown in Figure 1, the downtown area of Yangon city can be regarded as a typical grid
network.
In the grid network, the route which connects two points in the shortest-distance is rather
simple. Usually, it consists of two directional and orthogonalized movements within only
a few turning like Figure 2-(b). The important point is that even if we assume ahierarchical grid network like Figure 2-(a), the characteristics of the shortest-distanceroute is still simple.
On the other hand, the route which connects origin-destination in the “shortest-time” ismore complicated. Since it is deeply related to the travel speed of each link, it becomesprominent with a hierarchical grid network. As described in Figure 2-(c), they also consistof two-directional and orthogonalized movements, but the number of turns would be
multiple times.
The most important point in this study is that these two routes are different, and thedifference becomes larger when the travel speed of each link is different like thehierarchical road network. Obviously, the shortest-distance route is not the “shortest” interms of “time”. Likewise, the shortest-time route is not the “shortest” in terms of“distance”. It means that we cannot simultaneously optimize both measures. In thefollowing subsection, we formulate these phenomena and examine the unfavorable
influences on the road networks. Hereafter, we abbreviate the shortest-distance route as
the SD route and the shortest-time route as the ST route.
2.2 Mathematical models
Let us suppose a directed graph 𝐺𝐺𝐺𝐺(𝑁𝑁𝑁𝑁, 𝐸𝐸𝐸𝐸) as a road network where 𝑁𝑁𝑁𝑁 is a set of nodes and𝐸𝐸𝐸𝐸 is a set of links. Furthermore, we denote each link as 𝑒𝑒𝑒𝑒 ∈ 𝐸𝐸𝐸𝐸, and 𝑑𝑑𝑑𝑑𝑒𝑒𝑒𝑒 indicates the traveldistance of link 𝑒𝑒𝑒𝑒 and 𝑡𝑡𝑡𝑡𝑒𝑒𝑒𝑒 indicate the travel-time of link 𝑒𝑒𝑒𝑒.
A mathematical problem to solve the SD route from origin 𝑜𝑜𝑜𝑜 ∈ 𝑁𝑁𝑁𝑁 to destination 𝑑𝑑𝑑𝑑 ∈ 𝑁𝑁𝑁𝑁 is
as follows:
New Technologies for Urban Safety of Mega Cities in Asia

223

min. ∑𝑒𝑒𝑒𝑒∈𝐸𝐸𝐸𝐸 𝑑𝑑𝑑𝑑𝑒𝑒𝑒𝑒 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒SD(𝑖𝑖𝑖𝑖 = 𝑜𝑜𝑜𝑜)−1SDSD
s.t. ∑𝐼𝐼𝐼𝐼(𝑖𝑖𝑖𝑖) 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒 − ∑𝑂𝑂𝑂𝑂(𝑖𝑖𝑖𝑖) 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒 = � 0 ∀𝑖𝑖𝑖𝑖 ∈ 𝑁𝑁𝑁𝑁 ∖ {𝑜𝑜𝑜𝑜, 𝑑𝑑𝑑𝑑}(𝑖𝑖𝑖𝑖 = 𝑑𝑑𝑑𝑑)−1𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒SD = {0,1} ∀𝑖𝑖𝑖𝑖 ∈ 𝑁𝑁𝑁𝑁

(1)
(2)
(3)

where 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒SD = 1 if link 𝑒𝑒𝑒𝑒 is used as a part of the SD route, and 0 otherwise. Furthermore,
𝐼𝐼𝐼𝐼(𝑖𝑖𝑖𝑖) is a set of inflow links of the node 𝑖𝑖𝑖𝑖, and 𝑂𝑂𝑂𝑂(𝑖𝑖𝑖𝑖) is a set of outflow links of the node 𝑖𝑖𝑖𝑖.

Expression (1) is the objective function, and it calculates the distance of the route.
Constraint (2) is a flow-constraints and it assures the route connectivity. Constraint (3) isfor 0-1 variables.
Similarly, the following problem is to solve the ST route from origin 𝑜𝑜𝑜𝑜 ∈ 𝑁𝑁𝑁𝑁 to destination
𝑑𝑑𝑑𝑑 ∈ 𝑁𝑁𝑁𝑁:
min. ∑𝑒𝑒𝑒𝑒∈𝐸𝐸𝐸𝐸 𝑡𝑡𝑡𝑡𝑒𝑒𝑒𝑒 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒ST(𝑖𝑖𝑖𝑖 = 𝑜𝑜𝑜𝑜)−1STST
s.t. ∑𝐼𝐼𝐼𝐼(𝑖𝑖𝑖𝑖) 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒 − ∑𝑂𝑂𝑂𝑂(𝑖𝑖𝑖𝑖) 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒 = � 0 ∀𝑖𝑖𝑖𝑖 ∈ 𝑁𝑁𝑁𝑁 ∖ {𝑜𝑜𝑜𝑜, 𝑑𝑑𝑑𝑑}(𝑖𝑖𝑖𝑖 = 𝑑𝑑𝑑𝑑)−1𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒ST = {0,1} ∀𝑖𝑖𝑖𝑖 ∈ 𝑁𝑁𝑁𝑁

where 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒ST = 1 if link 𝑒𝑒𝑒𝑒 is used as a part of the ST route, and 0 otherwise.

224

Your paper title

(4)
(5)

(6)

December 2019, Yangon, Myanmar

2.3 The relation between the SD and ST route
Note that the “shortest” route under any measures does not pass through the same link
twice. Therefore we can express both the SD route and the ST route as a set of links asfollow:SD
𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜= {𝑒𝑒𝑒𝑒|∀𝑒𝑒𝑒𝑒 ∈ 𝐸𝐸𝐸𝐸, 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒SD = 1 for OD pair (𝑜𝑜𝑜𝑜, 𝑑𝑑𝑑𝑑)}
ST
𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜= {𝑒𝑒𝑒𝑒|∀𝑒𝑒𝑒𝑒 ∈ 𝐸𝐸𝐸𝐸, 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒ST = 1 for OD pair (𝑜𝑜𝑜𝑜, 𝑑𝑑𝑑𝑑)}

(7)
(8)

𝐷𝐷𝐷𝐷𝑖𝑖𝑖𝑖𝐷𝐷𝐷𝐷𝑡𝑡𝑡𝑡𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑒𝑒𝑒𝑒�𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 � = ∑𝑒𝑒𝑒𝑒∈𝑅𝑅𝑅𝑅 𝑑𝑑𝑑𝑑𝑒𝑒𝑒𝑒 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒(9)

In addition, we define a function to calculate the total distance (time) as a function ofroute 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 as follows:𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

𝑇𝑇𝑇𝑇𝑖𝑖𝑖𝑖𝑇𝑇𝑇𝑇𝑒𝑒𝑒𝑒�𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 � = ∑𝑒𝑒𝑒𝑒∈𝑅𝑅𝑅𝑅 𝑡𝑡𝑡𝑡𝑒𝑒𝑒𝑒 𝑥𝑥𝑥𝑥𝑒𝑒𝑒𝑒(10)

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆) ≥ 𝐷𝐷𝐷𝐷𝑖𝑖𝑖𝑖𝐷𝐷𝐷𝐷𝑡𝑡𝑡𝑡𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑒𝑒𝑒𝑒(𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜)
𝐷𝐷𝐷𝐷𝑖𝑖𝑖𝑖𝐷𝐷𝐷𝐷𝑡𝑡𝑡𝑡𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑒𝑒𝑒𝑒(𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
𝑇𝑇𝑇𝑇𝑖𝑖𝑖𝑖𝑇𝑇𝑇𝑇𝑒𝑒𝑒𝑒(𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 ) ≤ 𝑇𝑇𝑇𝑇𝑖𝑖𝑖𝑖𝑇𝑇𝑇𝑇𝑒𝑒𝑒𝑒(𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 )

(11)
(12)

𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜

Now, we obtain two inequalities which are quite important in the study:First, Inequality (11) indicates a situation that will be happened in the real world. In
general, people tend to use the ST route than the SD route because they can empiricallyrecognize the travel speed of each link. Then, (11) indicates that people need to incur
more distance the SD distance. Such “deviation” behavior from the SD route increases intraffic volume. Meanwhile, (12) corresponds to another scenario that people single-

New Technologies for Urban Safety of Mega Cities in Asia

225

mindedly use the SD route. In that case, as (12) shows, people are obliged to bear moretravel-time than the ST route.
3. NUMERICAL RESULTS
3.1 Network and Demand Data
The road network we used for the downtown area of Yangon is described in Figure 3. As
shown, it is a typical grid-like network, but the efficiencies in moving between West-Eastand that of North-South are very different. Precisely to say, there are many “narrow andsecondary” North-South streets which are not recorded in our GIS Data. Since the spanof arterial North-South streets is long, these secondary roads are frequently utilized tohelp the North-South movement. However, at the same time, lots of cars are parked on
the secondary roads, and the travel speed of their roads is quite slow. Meanwhile, the spanof arterial West-East streets is relatively short, and there is no secondary street.
In this numerical example, we regarded the exact locations of building as OriginDestination (OD) points, which are also shown in Figure 3. There are 5558 OD points,
and therefore the total number of OD pairs is (5,558 × 5,557)/2 = 15,442,903. In
addition, to describe the movement using secondary North-South streets, we assume thateach OD point can vertically access the nearest arterial West-East streets as shown in
Figure 4. As a result, the movements are somehow idealized but we believe that it highly
simulates the real situations.
We calculated both the ST routes and the SD routes for all pairs. For arterial roads, we
assume that the travel speed is 𝑣𝑣𝑣𝑣1 =20[km/h]. Meanwhile, to examine the impact of slowdown in secondary North-South streets, we prepared the following six cases, 𝑣𝑣𝑣𝑣2 ={20,10,8,6,4,2,1}[km/h].
3.2 Results based on the route of the shortest time

We discuss the results based on the route of the shortest time route.
Figure 5 shows the distance distribution of the shortest time route at various speeds of 𝑣𝑣𝑣𝑣2 .
Similarly, Figure 6 shows aggregated flow volumes on the networks. Remind that the ST
route is equivalent to the SD route when all link speed is the same (𝑣𝑣𝑣𝑣1 = 𝑣𝑣𝑣𝑣2 =20km), that
is, Figure 5,6-(a) shows the most favorable case in terms of traffics. Meanwhile, as shownin Figure 5,6-(b) and (c), both travel-distance and aggregated flow volumes are increased
as a result of decreasing of the secondary links speed 𝑣𝑣𝑣𝑣2 . These are the results of deviation
behavior form the SD route. Especially from Figure 6-(c), we can confirm that the arterial
North-South street on the center is much more congested then Figure 6-(a), and lots ofother arterial North-South streets are more utilized as well. The facts indicate that theoccurrence of bottlenecks on secondary streets will be a critical factor of deviation
behaviors AND traffic increasing on arterial streets.

226

Your paper title

December 2019, Yangon, Myanmar

New Technologies for Urban Safety of Mega Cities in Asia

227

4. CONCLUSION
In this study, we numerically discuss the influence of bottleneck occurred in secondary
North-South streets in downtown Yangon from the viewpoints of travel-time, traveldistance, and flow volume.
Since the road network is a typical grid-like network with a hierarchical road type, the ST
route and the SD route would become different. Especially when we assume that people
would use the ST route for movements, the above results showed the fact that thebottleneck in secondary North-South streets promotes people’s deviation behavior andthe increase of traffic volumes. Even if we assume that people follow the SD route, theslow-down of secondary streets contributes to the increase of travel time.
REFERENCES
R. Vaughan, 1987, Urban Spatial Traffic Patterns, Pion.
T. Koshizuka, 1999, “Comparison of Road Network Patterns with Respect to Travel
Distance and Passing Volume,” Journal of the City Planning Institute of Japan, Vol.34,
pp763-768.
S. Fujita, and T. Suzuki, 2003, “Average Trip Length and Traffic Flow in a Disk City
with Multi-ring Routes,” Journal of the City Planning Institute of Japan, Vol.38, pp.421426.
T. Koshizuka, 1996 “Comparison between Low and High Buildings with Respect toTravel Distance,” Journal of the City Planning Institute of Japan, Vol.31, pp.31-36,.
B. Ghosh, 1951 Random distances within a rectangle and between two rectangles,
Bulletin of the Calcutta Mathematical Society, Vol.43, pp.17-24.
O. Kurita, 2001, “Theory of Road Patterns for A Circular Disk City, Journal of the City
Planning Institute of Japan,” Vol.36, pp.859-864.
T. Ukai, and S. Toriumi, 2017, “Distribution of n-directional distance in a circular region,”
Journal of the City Planning Institute of Japan, Vol.52, pp.1327-1334.
M. Miyagawa, 2014, “Optimal allocation of area in hierarchical road networks,” The
Annals of Regional Science, 53, pp.617-630.

228

Your paper title

Optimization of building footprint extraction
model with color and texture analysis in
Yangon city
Hein Thura Aung1, Sao Hone Pha2
and Wataru Takeuchi3
1

Post-graduate Student, Department of Electronic Engineering,
Yangon Technological University, Myanmar
heinthuraung@ytu.edu.mm, heinthuraung@gmail.com
2
Director, Remote Sensing and GIS Research Center,
Yangon Technological University, Myanmar
3
Professor, Institute of Industrial Science,
The University of Tokyo, Japan

ABSTRACT
Automatic building footprint extraction using machine learning and deep learning saves
a lot of time and human source, and makes future updates easier. Creation of training
datasets for those learning algorithms is one of the most important steps in theextraction process especially when the feasibility of training samples is limited. In thisresearch, different townships of Yangon City are clustered based on color and texture
analysis. First, non-building areas of Yangon City are removed by using digitalbuilding model (DBM) which is derived from GeoEYE stereo RGB satellite image. Then,the whole Yangon City image is split according to the boundaries of thirty different
townships. After that, for each image of each township, the average and standard
deviation for color histogram analysis, and three features for textural analysis, mean
Euclidean distance, variance, and skew, are calculated. Based on the color histogram
and textural analysis, thirty different townships are clustered by using k-meansclustering algorithm. By looking at the color analysis and clustering results, training
dataset representation for the whole Yangon City such as from where the training
images should be extracted, can be decided.
Keywords: GeoEYE RGB image, digital building model, GLCM, clustering, training
dataset representation229

1. INTRODUCTION
Yangon is the largest city in the country and formal capital of Myanmar. Its area is
growing seven times in forty two years from 1973 to 2015 (Sritarapipat et al., 2018)
without proper urban planning and management. Urban population has also increased
about two and half times from 1972 to 2014 (Ministry of Immigration and Population,2015). With that rate of increase, proper management of urban resource management
such as food and water, transportation management, emergency response, disaster
response and so on, are very important. Urban related database such as urban building
maps are one of the essential things for urban related applications. Manual creation ofurban building maps takes much more time and human resource, and more difficult in
future updates. Automatic extraction needs image processing techniques, machinelearning and deep learning algorithms.
In (Lopez et al., 2015, p. 201), (Oztimur Karadag et al., 2015) and (Kabolizade et al.,2010), several datasets such as optical image, light detection and ranging (LiDAR)
dataset were used to detect building footprints. They combined several image
processing techniques with machine learning algorithms such as support vector machine(SVM) classification. Their research works need multi spectral images including red,green, blue (RGB) and near infra-red (NIR) bands. In (Vakalopoulou et al., 2015) and(Zhang et al., 2016), they used convolutional neural network (CNN) to detect building
footprints. CNN is deep learning algorithm which needs a lot of training samples. In(Zuming Huang et al., 2016) and (Chen et al., 2017), they used two datasets including
near-red band and digital surface model (DSM). (Bittner et al., 2018) also used multiple
datasets including RGB, IR bands and panchromatic images. All these research works
are based on convolutional neural network (CNN) which is a very powerful deeplearning algorithm. However, in order to CNN, a lot of training samples are required.
The research works in (Hein Thura Aung et al., 2018a) and (Hein Thura Aung et al.,2018b) indicate how training samples could affect the extraction performance of deeplearning algorithm. Due to the high price of very high resolution satellite images,
availability of training samples for automatic building footprint extraction is limited. So,
in this research work, color and texture analysis of RGB GeoEYE satellite image are
performed in order to optimize building footprint extraction model by selecting the mosteffective area as training samples.

230

2. METHODOLOGY
Figure 1 shows the flow chart of this research. As shown in Figure 1, the RGB image of
GeoEYE satellite of the study area is masked with digital building model (DBM). The
RGB image of the study area is columns and rows with meter spatial resolution. It iscomprised of thirty townships including urban and suburban areas. The digital building
model of the study area is columns and rows with meter spatial resolution.
Firstly, the non-building regions of RGB image of Yangon city is suppressed with athreshold value of DBM image. After that, the average of image histogram elements,
mean and standard deviation of each band in the masked RGB is calculated. In order tocompare the image histogram statistical elements of different townships, normalized
difference indices for mean and standard deviation values between each pair of
townships are calculated. And then, townships with highest frequencies of being
enlisted in the lowest three normalized difference mean and standard deviation index
values are considered.
For textural analysis, three texture features, mean Euclidean distance, variance and skew,
are calculated. After calculation of three texture features, k means clustering is used inorder to classify each texture feature image into five classes based on texture analysis
values. After clustering, the distribution of each class in the image is used to consider
the suitability of townships for training dataset.
2.1 Normalized Difference Index
As the townships in Yangon city have different columns and rows, it is very difficult tocompare mean and standard deviation values alone. Instead, normalized difference
mean index and normalized difference standard deviation index between each pair of
townships are calculated as shown in equation 1 and equation 2.
(1)(2)
For example, for calculation of normalized difference indices of Ahlone Township andBahan Township, the subtraction of mean values of Ahlone and Bahan is divided by theaddition of mean values of those two townships. Similarly, other pairs of townships arecalculated. Higher index values indicate higher difference between two townships
whereas lower index values represent lower difference.
After calculation of normalized difference indices for mean and standard deviation of231each township, the frequencies of enlisted townships in the lowest three index values
are considered for training dataset optimization.
2.2 Texture features
In this section, three texture features, mean Euclidean distance, variance and skew, arediscussed.
2.2.1 Mean Euclidean distance (MED)
Mean Euclidean distance is the average of the differences between the center pixel ofthe moving window and other pixels in that window (ERDAS, Inc, 2010). Equation 3
shows the calculation of MED for a single band.
(3)is the digital number (DN) value of a spectral band at pixel , is the DN value of thewindow’s center pixel for a spectral band and is number of pixels in a window
2.2.2 Variance
Equation 4 shows how to calculate the variance (ERDAS, Inc, 2010). Variance iscalculated as the average of the differences between mean value of a window and DNvalue of each pixel in the window.
(4)is the DN value at pixel , is number of pixels in a window and is the mean of themoving window where .
2.2.3 Skew
Equation 5 shows how to calculate skew (ERDAS, Inc, 2010).
(5)
is the DN value at pixel , is number of pixels in a window, is the mean of the moving
window where , and is variance.
2.3 K means clustering
K means clustering is partitioning a data set into distinct, non-overlapping clusters(James et al., 2013). K means clustering can be done by equation 6.
(6)
The term in the curly bracket represents the squared Euclidean distance. Firstly, arandom number, from to , is assigned to each observations. denote clusters. is the232number of observations in the cluster. Equation 6 represents to minimize thedifferences between the centroid of each of the K clusters and every observation i.e.,each observation is assigned to the cluster whose centroid is closest in terms of
Euclidean distance. A good clustering is one for which the within-cluster variation is as
small as possible (James et al., 2013).

3. RESULTS
In this section, color and texture analysis results are discussed. Depending on the
results of K means clustering, optimization of building footprint extraction model is also
discussed.
3.1 Color analysis
For color analysis, normalized difference indices for mean and standard deviation
between every pair of thirty townships are calculated. Figure 2 shows the frequencies
of enlisted townships in the lowest three normalized difference mean and standard
deviation index values.
As shown in Figure 2, Botahtaung and Dawbon townships include in the lowest threemean index values for five townships. Bahan, Dagon, Dagon Myothit (South),Hlaingtharya, Insein, Kyeemyindaing, Mingalardon and Tamwe are enlisted in thelowest three mean index values for four townships. Dagon Myothit (East), Mayangone,
Mingalar Taung Nyunt, Sanchaung and Seikkan Townships have only once in lowest
frequencies in the bottom three mean index values. For lowest three normalized
difference standard deviation index values, Ahlone, Dagon Myothit (North),
Kyeemyindaing, Latha and Thingangyun Townships have highest frequencies followedby Bahan, Botahtaung, Dagon Myothit (South), Insein, South Okkalapa, Seikkan,
Thaketa and Yankin townships with being enlisted in four townships.
3.2 Texture analysis
Figure 3 shows some sample images how five classes are clustered depending on the
MED values. Other texture features, variance and skew, have similar occurrence.
Black areas represent masked area with DBM image. As shown in Figure 3, Class 1, 2,
and 3 represent low texture areas such as rooftops and plane-like surfaces whereas Class

233

4 and 5 represent high texture areas such as boundaries and edges.
Figure 4 shows the distribution of each class in the texture image of MED. According
to Figure 4, Dagon Myothit (Seikkan) and Seikkan Townships have lowest Class 4
distribution as Dawgon Myothit (Seikkan) is mostly suburban area and Seikkan is just a
township with ports full of containers and fewer buildings than other urban areas. As aresult of having fewer buildings and containers, those two townships have higher
contribution for Class 1 and Class 2 which represent lower texture level.
Figure 5 shows distribution of five classes in Variance texture image. Similarly, Dagon
Myothit (Seikkan) and Seikkan Townships have higher contribution for Class 1 and 2,
whereas lower contribution for Class 4 and 5. Figure 6 shows distribution of fiveclasses in Skew texture image. Similarly in MED and Variance texture images, Dagon
Myothit (Seikkan) and Seikkan Townships have higher contribution of Class 1 and 2,
and lower contribution for Class 4 and 5. For all three texture images, downtown areas
such as Botahtaung, Latha, Mayangone, Kyeemyindaing and Dawbon and South
Okkalapa Townships have high contribution in Class 4 and 5.
4. DISCUSSION
According to Figure 2, Botahtaung and Kyeemyindaing Townships have highest
enlisted frequencies in the lowest three normalized difference mean and standard
deviation index values. Both of them includes in urban areas where most of them arecovered with buildings. Bahan, Dagon Myothit (South) and Insein Townships also havehigh enlisted frequencies. Dagon Myothit (South) and Insein Townships are sub urban
areas which are covered with trees and buildings, and although Bahan Township is inurban area, it is also covered with trees and buildings. Kan Daw Gyi Lake which is oneof the two major lakes, is also located in Bahan Township. Insein, Ahlone,Thingangyun and Latha Townships also have high enlisted frequencies. Those four
townships are also covered with vegetation and buildings. Although Latha Township isurban area, half of it is covered with both tress and buildings and the other half ismostly buildings.
From Figure 4, 5 and 6, only Dagon Myothit (Seikkan) and Seikkan Townships havevery different class distributions. Dagon Myothit (Seikkan) is mostly covered with barelands with small vegetation and farms, and some buildings. Seikkan Township is
mostly covered with impervious floor, containers and warehouses. Botahtaung andKyeemyindaing Townships have similar distributions of classes for variance as shownin Figure 5 and 6, but they have different distribution for MED as in Figure 4. Only
Bahan and Dagon Myothit (South) Townships have similar distribution for MED as

234

shown in Figure 4, but all Bahan, Dagon Myothit (South) and Insein Townships have
similar distributions for variance and skew as shown in Figure 5 and 6.
Latha and Thingangyun Townships have similar distributions for MED as in Figure 4,
but all Ahlone, Latha and Thingangyun Townships have similar distributions forvariance and skew as in Figure 5 and 6.
According to the color and texture analysis, training dataset should be selected from allor any of Botahtaung, Kyeemyindaing, Bahan, Dagon Myothit (South), Insein, Ahlone,
Latha, and Thingangyun Townships.
5. CONCLUSIONSIn this research, monocular RGB GeoEYE satellite image is analyzed with image
histogram statistics such as mean and standard deviation, and texture features which aremean Euclidean distance, variance and skew. According to the results, townships withsimilar spatial and spectral properties from visualization have similar color and texture
statistical values. Some townships such as Dagon Myothit (Seikkan) and Seikkan
Townships have different spatial and spectral properties, so they cannot be chosen for
training dataset. The color and texture analysis of Yangon City gives eight different
townships that are suitable for training dataset representation for the whole Yangon City.
So, as future plan, some of those eight townships will be selected as training dataset andperformance of pix2pix will be evaluated again.

REFERENCES
Bittner, K., Adam, F., Cui, S., Korner, M., Reinartz, P., 2018. Building Footprint
Extraction From VHR Remote Sensing Images Combined With Normalized DSMs Using
Fused Fully Convolutional Networks. IEEE Journal of Selected Topics in Applied Earth
Observations and Remote Sensing 11, 2615–2629. https://doi.org/10/gd7zc2
Chen, K., Fu, K., Gao, X., Yan, M., Sun, X., Zhang, H., 2017. Building extraction fromremote sensing images with deep learning in a supervised manner, in: 2017 IEEE
International Geoscience and Remote Sensing Symposium (IGARSS). Presented at the2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE,
Fort Worth, TX, pp. 1672–1675. https://doi.org/10.1109/IGARSS.2017.8127295
ERDAS, Inc, 2010. ERDAS Field Guide.
Hein Thura Aung, Sao Hone Pha, Wataru Takeuchi, 2018a. Automatic building
footprints extraction of Yangon City from GeoEYE monocular optical satellite image by235

using deep learning, in: Asian Conference on Remote Sensing 2018. Presented at the39th Asian Conference on Remote Sensing, Kuala Lumpur Malaysia, pp. 1987–1996.
Hein Thura Aung, Sao Hone Pha, Wataru Takeuchi, 2018b. Performance evaluation ofbuilding footprint delineation in Yangon City using deep learning with different training
datasets, in: 9th International Conference on Science and Engineering. Presented at the
9th International Conference on Science and Engineering, Yangon Technological
University.
James, G., Witten, D., Hastie, T., Tibshirani, R. (Eds.), 2013. An introduction tostatistical learning: with applications in R, Springer texts in statistics. Springer, NewYork.
Kabolizade, M., Ebadi, H., Ahmadi, S., 2010. An improved snake model for automatic
extraction of buildings from urban aerial images and LiDAR data. Computers,
Environment
and
Urban
Systems
34,
435–441.
https://doi.org/10.1016/j.compenvurbsys.2010.04.006
Lopez, E.R., Santos, H.F., Ana, R.R.C.S., Samalburo, S.J.D., 2015. Evaluation of
Building Footprint Generation from LIDAR Data and Orthoimages using Object-based
Image Analysis Technique, in: 36th Asian Conference on Remote Sensing. Presented atthe 36th Asian Conference on Remote Sensing, Manila, Philippines.
Ministry of Immigration and Population, M., 2015. A changing population: Yangon
region figures at a glance. Department of Population, Myanmar.
Oztimur Karadag, O., Senaras, C., Yarman Vural, F.T., 2015. Segmentation Fusion for
Building Detection Using Domain-Specific Information. IEEE Journal of Selected
Topics in Applied Earth Observations and Remote Sensing 8, 3305–3315.
https://doi.org/10.1109/JSTARS.2015.2403617
Sritarapipat, T., Takeuchi, W., The University of Tokyo 6-1 Komaba 4-chome, Meguro,
Tokyo 153-8505, Japan, 2018. Land Cover Change Simulations in Yangon Under
Several Scenarios of Flood and Earthquake Vulnerabilities with Master Plan. Journal ofDisaster Research 13, 50–61. https://doi.org/10/gd52wk
Vakalopoulou, M., Karantzalos, K., Komodakis, N., Paragios, N., 2015. Building
detection in very high resolution multispectral data with deep learning features, in:2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
Presented at the IGARSS 2015 - 2015 IEEE International Geoscience and Remote
Sensing
Symposium,IEEE,
Milan,
Italy,
pp.
1873–1876.
https://doi.org/10.1109/IGARSS.2015.7326158
Zhang, Q., Wang, Y., Liu, Q., Liu, X., Wang, W., 2016. CNN based suburban building
detection using monocular high resolution Google Earth images, in: 2016 IEEE

236

International Geoscience and Remote Sensing Symposium (IGARSS). Presented at the
IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium,IEEE, Beijing, China, pp. 661–664. https://doi.org/10/gftsgh
Zuming Huang, Guangliang Cheng, Hongzhen Wang, Haichang Li, Limin Shi,
Chunhong Pan, 2016. Building extraction from multi-source remote sensing images via
deep deconvolution neural networks, in: 2016 IEEE International Geoscience andRemote Sensing Symposium (IGARSS). Presented at the IGARSS 2016 - 2016 IEEE
International Geoscience and Remote Sensing Symposium, IEEE, Beijing, China, pp.
1835–1838. https://doi.org/10.1109/IGARSS.2016.7729471

237

MONITORING RESULTS OF PATHEIN BRIDGE TOWERS AND BEARINGSKHIN MAUNG ZAW1, WIN BO2, AMY AUNG2, K. MATSUMOTO3, and K. NAGAI4
Associate Professor, Department of Civil Engineering, Yagon Technological University, Yangon, Myanmar,
Postgraduate Students, Department of Civil Engineering, Yagon Technological University, Yangon, Myanmar,
3
Associate Professor, Division of Engineering and Policy for Sustainable Environment, Hokkaido University, Japan,
4
Associate Professor, Institute of Industrial Science, University of Tokyo, Japan,
Correspond to Khin Maung Zaw (ukmzaw@gmail.com)
1

2

Keywords: Pathein Bridge, bridge monitoring, tower tilting, bearing movement
1. INTRODUCTION AND BACKGROUND
Pathein Bridge is one of the most important bridges in
Ayeyarwady Region, connecting its capital Pathein towestern coastal areas and the southern part of RakhineState. According to the 2012 bridge inspection report [1]of the Ministry of Construction, it was found that thebridge had lost a great deal of camber since completion,and it may be due to the tilting of main towers (shown in
Figure 1.a) towards the river [2].
The bridge towers were built on the alluvial soil and,hence, the horizontal force of main cable may moveconcrete anchorage blocks or the tower foundation may
rotate due to differential settlement. Most hangers were
found to be inclined towards Pathein side (shown in
Figure 1.b) [3]. Hence, in order to check whether towertilting is still continued or not and whether the bearings(shown in Figure 2) are working properly or not, themonitoring system was installed on both sides ofdownstream towers including two inclinometers, two
displacement transducers, temperature sensors and two
portable data loggers.

(a)(b)
Figure 2: (a) Fixed bearing on Pathein side and (b)expansion bearing on Chaung Tha side. [3](a)(b)
Figure 3: (a) Tower inclination and (b) Bearing
displacement with respect to temperature. [3]According to the results of regression analysis, the rateof movement of expansion bearing is found to be about
2.02 mm/˚C (shown in Figure 3.b) but there is no
significant movement of fixed bearing on Pathein side.

(a)(b)
Figure 1: Inclination of (a) tower and (b) hanger of Pathein
Bridge. [3]
2. RESULTS AND DISCUSSIONS
According to the results of regression analysis ofmonitoring data from November 2017 to April 2018, there
is no significant change in the value of tower inclination
degree. The results also indicate that the values ofinclination degree are very small, and it may be due to theeffect of temperature fluctuation. Hence, it can beconcluded that the tower is in stable condition. The
inclination degree of the tower along the bridge axis
direction is about 0.0015 degree per degree centigrade,
and along the transverse direction is about 0.0009 degree
per degree centigrade (shown in Figure 3.a) [3].

238

3. CONCLUSIONSPathein Bridge had lost a great deal of camber sincecompletion and, hence, the monitoring system wasinstalled on both sides of downstream towers in order tocheck the condition of tower tilting and the movement ofbearings. According to the monitoring results, it can beconcluded that the towers and bearings are in stablecondition. The inclination degree of the tower along thebridge axis direction is observed to be about 0.0015
degree/˚C, and along the transverse direction is about
0.0009 degree/˚C. The rate of movement of expansion
bearings is found to be about 2.02 mm/˚C and there is no
significant movement of fixed bearing on Pathein side.
REFERENCES[1] Japan Infrastructure Partners. Bridge Inspection
Report to Ministry of Construction, Myanmar. 2012.
[2] K.M. Zaw, Y. Suzuki, and K. Sugiura. Proceedings ofConstruction Steel, JSSC, Vol.23 (2015) 364-371.
[3] Win Bo. Ph.D. Thesis, Department of Civil
Engineering, Yangon Technological University. 2018.

SEISMIC HAZARD ASSESSMENT IN YANGON CITY USING THE EMPIRICAL
EARTHQUAKE EVALUATION METHOD
Yoshito YOKOE1, Takaaki IKEDA2, Takumi MATSUMOTO1, Atsuya MINAGAWA 1
1

Graduate student , Civil and Environmental Engineering, Nagaoka University of Technology, Niigata, Japan,
2
Professor, Civil and Environmental Engineering, Nagaoka University of Technology, Niigata, Japan,
Correspond to Mr. Yokoe(s173282@stn.nagaokaut.ac.jp)
Keywords: Ground motion simulation, Source model, EMPR, Scenario earthquake

1. INTRODUCTION
Yangon city is the largest city in Myanmar with apopulation of about 5 million. Sagaing fault, which
extends about 1500 km in the central part of Myanmar islocated in near Yangon City (Figure 11)), the risk ofearthquakes in Yangon City is very high. It is necessary totake disaster measures before the next earthquake occurs.
In this study, we attempt strong ground motion prediction
for Yangon City against crustal earthquake along theSagaing fault using the empirical ground motion
prediction method2).
2. SCENARIO EARTHQUAKE
Table 1 shows parameter of scenario earthquake.
Magnitude was set to 7.3 based on the 1930 Pyu
earthquake in Myanmar. Figure 2 shows location of
scenario earthquake. Fault distance to target site is about
25km. Fault size was 30km × 15km. Fault length wasestimated by Matsuda’s method3). Fault width was
assumed half of fault length. Fault dip angle was set to 90
deg. assuming the strike slip earthquake.
3.METHOD AND RESULTWe used EMPR1) for predicting strong ground motion. It
is nonstationary strong motion prediction models which
was proposed by Sugito et al2). It can be evaluated strong
ground motion on engineering base with Vs=500-600m/s
in consideration of fault rupture process.
In this study, we divided fault plane into 18 (6 × 3, see
figure 2), and we calculated 18 series that changed therupture starting point. Table 3 shows result of strong
ground motion prediction. The maximum acceleration is388.8 cm/s2. Figure 3 shows acceleration waveform. The
maximum acceleration of the surface ground exceeds 500
cm/s2 assuming amplification factor of surface layer is 2.0.
REFERENCES[1] Michael, F. R. et al.: The role of strike-slip faulting in the history of the Hukawng Block and the J
ade Mines Uplift, Myanmar, Proc. Geologists' Association, 130, 2, 126-141, 2019.
[2] Sugito, M. et al.: Strong Motion Prediction on RockSurface by Superposed Evolutionary Spectra, 12WCEE,
2000.
[3] Matsuda, T.: Magnitude and Recurrence Intervalof Earthquake from a fault, zishin, 2, 28, 269-283,
1975(in Japanese).

Figure 1. Outline map of Myanmar showing the two mostsignificant strike-slip fault belts1)

Figure 2. Location of the target site and scenario
earthquake

Figure 3. Predicting strong ground motion
Table 1. Source parameter of scenario earthquake
Location
16.8547N, 96.4283 E
Magnitude (Mw)
7.3
Size (L×W)
30km × 15km
Depth (Upper end of fault)
10km

Dip angle
Seismic moment (M0)90 degree
3.52 × 1019 Nm

Table 2. Result of strong ground motion prediction
Max.
Ave.
Ave.+1σ
Acceleration (cm/s2)
388.8
280.1
328.9
Velocity (cm/s)
43.2
28.4
35.6

239

EFFECT OF SURFACE GROUND CHARACTERISTICS ON STRUCTURAL DAMAGE
Haruki SUZUKI1, Takaaki IKEDA2 and Yukiko KOJIMA3
Graduate student, Nagaoka University of Technology, Niigata, Japan,
2
Professor, Nagaoka University of Technology, Niigata, Japan
3
Assistant Professor, National Institute of Technology, Nagaoka College, Niigata, Japan
Correspond to Mr. Suzuki (s173253@stn.nagaokaut.ac.jp)
1

Keywords: Earthquake damage investigation, Effects of Surface Geology, 2019 off Yamagata Prefecture earthquake
1. INTRODUCTION
On June 18, 2019, at 22:22 (JT), an Mw6.4 earthquake
occurred off the coast of Yamagata Prefecture. A
maximum acceleration of 1191.3 gal was also observed ata nearby seismic station. Strong ground motions weregenerated at near source area, but there was no major
damage. Main damage is roof tiles damage of the wooden
house. A damage rate of roof tile at Koiwagawa area was
the highest in damage area. On the other hand, Oiwagawa
area and Wasada area which are adjustment in Koiwagawa
had minor damage. Therefore, in order to clarify thedifference in damage between Koiwagawa, Oiwagawa,and Wasada, we investigated the ground conditions at
each site.

Frequency of peak H/V spectral ratio correspond to
predominate frequency of surface layer.
3. RESULTS
From the H/V spectral ratio shown in Figure 2, H/V
spectral ratio of Koiwagawa is dominant around 5 to 7 Hz,
and Oiwagawa and Wasada are exceeding 10 Hz. The
natural frequency of wooden houses is usually 2 to 10 Hz.
Predominate frequency of surface layer at Koiwagawa
falls in the range of the natural frequency of wooden house.
On the other hand, predominate frequency of other site is
greater than natural frequency of wooden house.
Therefore, it is thought that the damage situation of study
sites was affected by ground charactristics.

2. INVESTIGATION SITE
The study sites are the Koiwagawa, Oiwagawa, andWasada. Figure 1 shows the location of the epicenter andstudy sites. Considering the topographical conditions,surface layer at each site was composed by sandy soil
mainly. As shown in Figure 1, the epicentral distance ofstudy sites are almost the same, so the input groundmotion is considered to be the same.

Figure-2 H/V spectral ratio of each area

Figure-1 Location of epicenter and study sites
Kojima et al.1) has evaluated of the roof tile damage
from an aerial photograph. They were reported thatdamage rate of roof tile was 28.6% in the Koiwagawa,
1.0% in the Oiwagawa and 2.6% in the Wasada. It wasthought that damage of roof tile related to characteristics
of surface layer.
Therefore, we conducted microtremor measurement atstudy site and evaluated predominate frequency of surface
layer by H/V spectral ratio of microtremor measured. H/V
spectral is Horizontal-to-Vertical spectral ratios.

240

4. CONCLUSIONSIn this earthquake, many roof tiles were damaged innear source area, but the damage was different at near sites,
so the characteristics of the surface layer were evaluatedby H/V spectral ratio of microtremor measured. As a result,it was found that there is a correlation between the
predominate frequency of the surface layer and thedamage situation.
REFERENCES[1] Y. Kojima et al.: Damage investigation of 2019 off the
yamagata prefecture earthquake, Proc. of the 39th JSCE
Earthquake Engineering Symposium, 2019 (undersubmission, in Japanese).
[2] Nakamura, Y.: A method for dynamic characteristics
estimation of subsurface using microtremor on the groundsurface, Q. Rep. Railw. Tech. Res. Inst.,30,25–30, 1989.

SOURCE MODELING AND GROUND MOTION SIMULATION
OF THE MID-SCALE CRUSTAL EARTHQUAKE
T. IKEDA1
1

Professor, Department of Civil and Environmental Engineering, Nagaoka University of Technology, Nagaoka, Japan
Correspond to Prof. T. IKEDA (ikeda@vos.nagaokaut.ac.jp)

Keywords: ground motion simulation, source modeling, empirical Green’s function method, mid-scale crustal
earthquake
1. INTRODUCTION
Recently, structure or lifeline system damages causedby the mid-scale earthquake were reported. Generally,
damage scale by mid-scale earthquake was not so serious,
but that earthquake is often generated. So it is importantthat study of the source modeling the mid-scale
earthquake. In this study, we attempted to make a source
model of mid-scale earthquake by the forward modeling[1]using empirical Green's function method[2].
2. SOURCE MODELING
Target earthquake is 2017 Nagano prefectureearthquake of Mw5.2 in Japan. Figure 1 shows locationsof the epicenter and near seismic stations.
We set single strong motion generation area (SMGA)
referred to observation waveform. As a result, we make asource model with single SMGA which located in nearhypocenter (Figure 2). Figure 3 shows the synthesized
acceleration waveforms, velocity waveforms anddisplacement waveform of EW component at each target
stations compared with the observed ones. Synthesized
acceleration waveform and velocity waveform at
NGNH18 which is the nearest station were good
agreement with observed ones. Especially, synthetic
waveform can reproduce pulse waveform.
Figure 4 shows relationship between seismic momentand short period source spectrum. Scaling law was written
in this figure[3]. Relation between seismic moment andshort period source spectrum can be express scaling law.

Figure 1. Location of the epicenter of the 2017 Nagano
prefecture earthquake and seismic stations

Figure 2. The source model of the 2007 Nagano prefectureearthquake which composed 1 SMGA

3. CONCLUSIONS
We constructed the source model of the 2007 Nagano
prefecture earthquake with Mw5.2. The source model hasa single SMGA. Relation between seismic moment andshort period source spectrum can be express scaling law[3].
REFERENCES[1] Kamae, K. and Irikura, K., Source model of the 1995
Hyogo-ken Nanbu earthquake and simulation of nearsource ground motion, BSSA, Vol.88, 400-412., 1998
[2] Irikura, K., Prediction of strong acceleration motion
using empirical Green's function, Proc. 7JEES,151-156.,
1986.
[3] Dan, K. et al., Short-period source spectra inferredfrom variable-slip rupture models and modeling ofearthquake faults for strong motion prediction by semiempirical method, Journal of Structural and Construction
Engineering, AIJ, No.545, 51-62. 2001.

Figure 3. Comparison of the observed and synthetic
waveforms of EW component at target station.

Figure 4. Relation between seismic moment and shortperiod source spectrum.

241

SESSION GENVIRONMENT INFORMATICS: GIS/REMOTE SENSING,
TRANSPORTATION, WATER RESOURCES, INFRASTRACTURE
MANAGEMENTExtraction of damage situation in Yamagata
coast earthquake using UAVYukiya TANIGUCHI1, C. K. Gadagamma2 and Muneyoshi NUMADA3
1
Student, Graduate School of Interdisciplinary Information Studies,
Institute of Industrial Science, the University of Tokyo, Japan
taniguchi-yukiya312@g.ecc.u-tokyo.ac.jp
2
Project-Assistant Professor, Institute of Industrial Science,
The University of Tokyo, Japan
3
Associate Professor and Director, Institute of Industrial Science,
the University of Tokyo, Japan
ABSTRACTOn June 28, 2018, a magnitude 6.8 earthquake occurred around the coast of Yamagata
Prefecture. A seismic intensity of 6 or more was observed in Murakami City, Niigata
Prefecture, and a seismic intensity of 6 or less was observed in Tsuruoka City, Yamagata
Prefecture. Also, seismic intensity 5 was observed from Hokkaido to the central part ofJapan. Around the epicenter, many houses were destroyed, along with landslides andliquefaction occurred. On the other hand, in recent years, surveys using UAV have beenused at disaster sites. Also, aerial photographs from paragliders (Para-Motor, PM)allows for a wider range of surveys than UAV. In this study, aerial images of the affectedareas were taken from UAV and paraglider at Koiwagawa and Nezugaseki in Tsuruoka
City, which were damaged by the Yamagata-Oki earthquake. From the taken aerial
images, a three-dimensional model was created, and the model was analyzed to extract
damaged areas and mapped to GIS.
Keywords: Aerial image, GIS, Image analysis, Photogrammetry, Remote sensing,Image analysis
1. INTRODUCTION
On June 28, 2018, a magnitude 6.8 earthquake occurred on the coast of Yamagata
Prefecture. In the vicinity of the epicenter, many houses were damaged, many people
were injured, roads were depressed, and the landslides occurred. Tsuruoka City in
Yamagata Prefecture is the top 10 largest area among all 1,741 municipalities of Japan.
In such a wide disaster area, the distance from the city hall where the disaster response
headquarters was established to the center of the damaged area is long way, so it isimportant how to grasp the disaster situation in the wide-area. Understanding the damage
situation immediately after the disaster will lead to efficient initial responses.
In recent years, measurements and surveys using UAV have been used at disaster sites.
By drawing a route for automatic navigation, aerial photographs with even side wrap andoverlap are taken quickly in a short time. On the other hand, UAV is effective for certain
limited objects such as bridges, but it is necessary to collect data over a wide area by
flying for a long time in order to grasp the damage situation. In addition, incidents andaccidents associated with the spread of UAVs are increasing, and the law strictly restricts
UAV flight, and many other issues restrict an overall understanding of the disastersituation.

244

December 2019, Yangon, Myanmar

Therefore, in this study, the effectiveness of the motor paraglider is verified as a methodof grasping the damage situation in a wide area. Table 1 shows a comparison for UAV
and Para-Motor feature. A motor paraglider does not require a runway like an aircraft,
and the takeoff and landing are available even on the flat ground with 30m to 40m length.
Currently, motor paragliders can fly and take aerial images freely almost anywhere except
for some prohibited areas such as around the airfield. Setting time to take-off is about 15
minutes, flight speed is about 35km / h, the noise is low same as 50cc motorbike.
Moreover, flight in urban areas and residential areas is unrelated to noise. It is very lowcost, speedy, and can be surveyed in a wider range area than UAV.
In this study, by using UAV and Para-Motor (PM) at Koiwagawa and Nezugaseki in
Tsuruoka City, damaged by the Yamagata-Oki earthquake, aerial images of the affectedareas were taken to analyze the situations.
Table 1. A comparison for UAV and Para-Motor feature
Flight time
Flight distance
Noise
LicenseRegulation by law

UAV
20 minutes
4 km
Necessary depending on place
Civil Aeronautics ActPM
4 hours
10 km
Same as 50cc motorbike
Necessary
Nothing

2. METHOD
On July 1st and July 2nd, 2019, we deployed a UAV and a PM along the coast of
Tsuruaoka and Nezugaseki where damages such as building collapses and landslides had
occurred. Figure 1 shows the landslide points and the collapsed area of the buildings
where aerial photographs were taken in this study. The red stars in Figure 1 show theplace where the landslide occurred, and the yellow polygons are the areas where thecollapse of the buildings occurred.

Figure 1. Disaster area in Tsuruoka

New Technologies for Urban Safety of Mega Cities in Asia

245

2.1. UAV
In order to grasp the damage situation of Nezugaseki, aerial images were obtained from
UAV. A Phantom 4 Professional with a 4K camera was used as UAV. The flight altitude
and lap rate were set up as uniform using the operation system Litchi which is automaticnavigation application to construct 3D models with necessary figures. Figure 1 shows aroute map of UAV by automatic navigation. The flight speed was 28 km / h and the flighttime was 11 minutes.
2.2 Para-Motor (PM)PM (Figure 3) was flied along coast of Tsuruoka city from the ground of Atsumi JuniorHigh School by the route in Figure 4. The flight distance was 15.6km, the flight time wasabout 32 minutes. Aerial images were taken by EOS 6D at every second, the overlap wasover 80%.

Figure 2. Automatic navigation map of UAV

Figure 3. Paramotor

Figure 4 Flight route of Paramotor

246

Extraction of damage situation in Yamagata coast earthquake using UAV

December 2019, Yangon, Myanmar

2.3 3D analysis
3D models were created by using PhotoScan in order to create the ortho photo combinedfrom aerial images by UAV and PM.
2.4 Image analysis
In this study, it was focused on the threshold of RGB image to extract the damaged parts.
All the damaged buildings were covered with blue sheets. For the RGB values of the blue
sheets, blue has high reflection characteristics. Therefore, the pixels of the higher
brightness of the blue threshold were extracted using raster calculation by ArcGIS. The
brightness value of the blue color was set to 245 RGB values or more.
Also, it was focused on the reflection characteristics of the soil to extract landslide. The
soil has high red reflection and low green reflection characteristics among RGB values.
Therefore, landslides were extracted by subtracting Green from Red and showing theresult with a value greater than 0 in the aerial images.
3. RESULTS
3. 1. 3D analysis
Figure 5 shows a 3D model of Nezugaseki created by aerial images from UAV. Figure
6 shows another 3D model of the area near Koiwagawa (coast of Tsuruoka-city) createdby aerial images from PM. The 3D model acquired by UAV was combined with the entire
shooting range, and a single orthoimage was created. The blue roof was applied to theblue part of the roof, and the building collapsed. The three-dimensional model is takenfrom the Para-Motor in Figure 6 is a combination of the shooting area on the south sidefrom the Atsumi Junior High School at the takeoff point. Due to a large number of shots
and the fact that the camera GPS was turned off, it was not possible to build the entire
shooting area into a single orthoimage in this study.
3.2 Image analysis
Figure 7 shows the original images of building collapse and landslide used for image
analysis. The image of the building was obtained from UAV, and the image of thesediment disaster was obtained from Para-Motor. Figure 8 shows the result of extracting
the collapsed part of the building and the sediment disaster part from the RGB informationby the GIS raster calculation committee. In the collapse of the building, the blue sheet
area was extracted by focusing on the blue threshold. However, other parts with high blue
thresholds, such as road white lines and white car bodies, have also been misrecognized.
Figure 9 shows the same image extracted from the orthoimage constructed from the
Nezugaseki 3D model. In Figure 9, in addition to the blue sheet, other parts having a highblue threshold were also extracted. Moreover, in the collapsed part of earth and sand fraud,
it expressed with the spectrum in order with the low threshold among the extracted pixels.
Focusing on the reflective properties of the soil, forest, and soil were distinguished bysubtracting the green threshold from the red threshold.

New Technologies for Urban Safety of Mega Cities in Asia

247

Figure 5. 3D model of Nezugaseki

Figure 6. 3D model of are near Koiwagwa

Figure 7. Original images taken by UAV and Paramotor

Low
Figure 8. Extraction of damaged buildings and landslide

248

Extraction of damage situation in Yamagata coast earthquake using UAVHighDecember 2019, Yangon, Myanmar

Figure 9. Extraction of damaged buildings by orthophoto
4. DISCUSSIONSIn both UAV and Para-Motor, it was possible to quickly obtain aerial images forgrasping the situation at the disaster site. However, in UAV, from the viewpoint of battery
capacity, the flight time was less than 20 minutes, at most about 30 minutes. Also, it isdifficult to take an aerial shot at a distance of more than 1km from the operator from theviewpoint of laws and radio communication distance in Japan. However, Para-Motor wasable to shoot at an altitude higher than UAV and a wide area over 10km. In the image
analysis, the fossil is currently only the threshold value of the RGB image, so in theextraction of the collapsed part of the roof, in addition to the blue sheet, reactions such ascars and white lines with high blue threshold values were also seen.
5. CONCLUSION
In this study, the authors examined the effectiveness of UAV and Para-Motor with a realcase of a disaster the Yamagata-Oki earthquake. UAV was able to take aerial photographswith a uniform lap rate by automatic navigation. On the other hand, a flight of less than
20 minutes and a radius of about several hundred meters was the limit. On that point,
Para-Motor was able to fly for more than 30 minutes in this study. Depending on the typeof engine, it is possible to fly for more than 4 hours. In the future, as a Para-Motor device,
we plan to construct a sensor that can transmit disaster information in real time during
aerial photography. Also, we will plan to build a mechanism that automatically estimates
the damage status of a large area of images taken by a motor paraglider using AI.
ACKNOWLEDGMENT
The authors are grateful to HIROO NISHIMURA for operating and shooting of ParaMotor.
REFERENCES
K., Suzuki, and O. Kobayashi, 2007, Mechanism of Roll Control Response
Characteristics in an Aircraft and a Paraglider, Transactions of the Japan Society for
Aeronautical and Space Sciences, Vol. 55, No. 42, 337-343.
Mario A. R. E., Abrahim N., 2019, The uses of unmanned aerial vehicles –UAV’s- (ordrones) in social logistic: Natural disasters response and humanitarian relief aid, Procedia
Computer Science, Volume 149, 375-383.
Leandro D. O. S., Renata A. D. M. B., Vânia B. G. C., 2017, The use of UAV andgeographic information systems for facility location in a post-disaster scenario,
Transportation Research Procedia, Volume 27, 1137-1145.

New Technologies for Urban Safety of Mega Cities in Asia

249

Study on Impacts of Parking on Congestion byDifferent Parking Management Systems
May Pyai Sone Win
ME (Transportation Engineering), Civil Engineering. Department
Yangon Technological University, Myanmar
Maypyisonewin1990@gmail.com
ABSTRACT

Parking demands daily increase especially in commercial zones within Yangon Central
Business District (CBD). Along the CBD roads and streets, on-street parking types can be foundmostly. The problems for parking users are long-rest parking, less parking information access,parking prices, scarce resources for new parking yard and loose rule and regulation.
Consequence issues of on-street parking types are troubled on traffic congestion and roadcapacity in the streets. Therefore, to solve and reduce these issues, the parking management
systems are required. The objective is to reduce the impacts of on-street parking in traffic
stream.
The study area is selected to the most famous crowded market within CBD area called Thein
Gyi Market. The market possesses on-street parking types and is complexed with many cargo
trucks, shopping light-truck, cars and taxi on traffic stream the whole worked time and locatesin the Shwedagon Pagoda; one of busiest roads of downtown. The data are collected with InOut Survey for parking demand, measuring geometric characteristics of parking yards,
questionnaires to shoppers, drivers and shop owners and cycle time in the selected signalizedintersections for road capacity. Statistically analysis is made and then a relationship is derived
between the parking management system and traffic capacity to reduce the impact of on-street
parking on congestion.
The results of the study clearly indicate that the reduction in impact of on-street parking oncongestion is greater when cargo trucks are restricted in on-street parking along the road withparking management systems. The study suggests possible reduction factors that can be usedin road capacity estimations when on-street parking is allowed in an urban transport corridor.
This study has potential to improve the parking management systems of on-street parking in
CBD and then satisfy to the road users, shoppers and people annoying reduction due to traffic
congestion.
Keywords: on-street parking, traffic congestion, road capacity, land use, parking management
systems

1. INTRODUCTION
Parking is called the place to rest the vehicles at the time of intervals, the whole night, the whole
day and so on. The drivers always stop the vehicles at the parking to go to their origins ordestinations. Parking is one of the major problems that are created by the increasing road traffic.
It is an impact of transport development. The availability of less space in urban areas has
increased the demand for parking space especially in Central Business District. This affects themode choice and also has a great economic impact. For solving the parking problems, parking

250

December 2019, Yangon, Myanmar

management includes as an important role. Parking management means the strategies like
reducing the requirements of parking, making the effective use of existing parking, improving
parking facilities, searching new parking resources, identifying the parking policies and rules
for the government and so on.
The selected study area, Thein Gyi Market used to congest along the Shwedagon road due toon-street parking especially in peak hours. The Shwedagon road is the six lanes undivided oneway road and on-street parking takes half of the road lanes according to the data collection.
This on-street parking type is 90 degree parking.
2. LITERATURE REVIEWThis section provides a brief literature review of land use and parking management strategy
and its relation to traffic congestion.
2.1 Parking Concepts and Land Use
Parking facilities and programs are of considerable importance in traffic engineering. Most
persons to urban and regional commercial centers are accessed primarily by cars. The viabilityof these areas depends on the availability of convenient parking facilities adjacent to or easily
accessible to desired destinations, especially off-street parking facilities. Parking studies areparking demand, average peak period parking demand, peak period of parking demand, total
parking demand, parking capacity, parking volume, parking supply analysis and parking
duration. The commercial land use provides opportunities for a broad range of retail and service
commercial and professional office as well as regional shopping demand.
2.2 Parking management strategy
Parking provision represents a major financial overhead, in terms of the additional land required,construction as well as its on-going maintenance and management. Restricted parking zoning
management system is used and the traffic regulation order fails to define what a “restrictedstreet” is and it does not prescribe that it is a contravention to park in a restricted street during
prescribed hours.
3. METHODOLOGY
The figure illustrates the methodological flow chart for the study.

New Technologies for Urban Safety of Mega Cities in Asia251

3.1 In-out Survey
In this survey, the occupancy count in the selected parking lot is taken at the beginning. Then,the number of vehicles that enter the parking lot for a particular time interval is counted. The
number of vehicles that leave the parking lot is also taken. The final occupancy in the parking
lot is also taken. Here the labor required is very less. Only one person may be enough. But wewon’t get any data regarding the time duration for which a particular vehicle used that parking
lot. Parking duration and turnover is not obtained. Hence we cannot estimate the parking farefrom this survey. For quick survey purposes, a fixed period sampling can also be done. This isalmost similar to in-out survey. All vehicles are counted at the beginning of the survey. Thenafter a fixed time interval that may vary between 15 minutes to i hour, the count is again taken.
Here there are chances of missing the number of vehicles that were parked for a short duration.
3.1.1 Key observation
The observations and findings of the in-out survey which assisted in the development of thesurvey methodology have been discussed in this section. The parking zones and major land uses
present were initially documented prior to undertaking the survey, to ensure all movements
related to parking were accounted.
4. Objectives and Problem statement
The main objective is to reduce the impact of on-street parking in traffic stream. The specificobjectives are To reduce queue lengths of vehicles in a period of traffic signals in selected junctions
 To reduce the times of parking-waiting by stopping in traffic streams
 To reduce the inefficient use of existing parking.
The problem statements are Inadequate parking spaces
 Need for various acceptable parking management systems
 Scarce resources for new parking yard constructions and Loose rules and regulations.
5. ILLUSTRATIONS

5.1 Layout of illustrations

252

Your paper title

December 2019, Yangon, Myanmar

7. UNITS AND SYMBOLSY = Parking duration (hours)
X1 = Arrival Time (hours)
X2 = Trip Purpose
X3 = Parking fees
X4 = Types of vehicles
7.1 Equations
Y = 10.589 – 0.189X1 – 2.405X2 + 0.156X3 + 0.523X4 + 2.709(1)

Y = Parking duration
X1 = Arrival Time
X2 = Trip Purpose
X3 = Parking fees
X4 = Types of vehicles
REFERENCES
ON-STREET PARKING ON STATE ROADS; VIRGINIA P. SISIOPIKU, Ph.D.
Chapter-41. Parking Studies; Transportation Systems Engineering
Chapter-37. Capacity and LOS Analysis of a Signalized I/S; Transportation Systems
Engineering
Chapter-34. Design Principles of Traffic Signal ; Transportation Systems Engineering
New Technologies for Urban Safety of Mega Cities in Asia

253

Chapter-4: Traffic Engineering Studies; Traffic and Highway Engineering, Fourth Edition,
Nicholas J. Garber and Lester A. Hoel
Chapter-11: Parking: Studies, Characteristics, Facilities, and Programs; Traffic Engineering,
Third Edition, Roger P. Roess, Elena S. Prassas, William R. McShane
Chapter-4: Traffic Engineering Studies; Traffic and Highway Engineering, Fourth Edition,
Nicholas J. Garber and Lester A. Hoel
Impacts of On-street Parking on Road Capacity;
http://www.atrf.info/papers/2015/files/ATRF2015_Resubmission_141.pdf

254

Your paper title

ECONOMIC ANALYSIS OF HIGHWAY IMPROVEMENT(CASE STUDY: YANGON-BAGO HIGHWAY)
Moe Thet Thet Aye1, Kyaing2
Ph.D Candidate at Transportation Engineering, Department of Civil Engineering, Yangon Technological
University, Yangon, Myanmar,2
Associate Professor, Department of Civil Engineering, Yangon Technological University, Yangon, Myanmar,
1

Keywords: Transportation, Economic Analysis, Cost, Benefit, B/C ratio, Net Present Value (NPV)
1. INTRODUCTION
Economic analysis of highway is a multi-disciplinary
activity involving highway engineers, economists andstatisticians. Construction and maintenance of highways
are financed by the government or authorized company,
whereas the highway user is the general public. Costs go
to the government or authorized company and the benefits
go to the public. It is not concerned with the sources offinancing, but only with an analysis of the costs andbenefits to the road-user and the consequences to all
sections of the society of a scheme, and establishing its
economic viability. It is also essentially a study for the
future and therefore, the analysis should estimate thefuture traffic, costs and benefits.
2. DATA COLLECTION
Nowadays, the Yangon-Bago Highway Road of 32
miles and 6 furlongs (52.7 km) is responsible with BOT
system by Max Highway Company Limited. Therefore,
traffic volume data and financial status of this highway arecollected from this company.
3. BENEFIT-COST (B/C) RATIO METHOD
There are a number of variations of this method, but asimple procedure is to discount all costs and benefits totheir present worth and calculate the ratio of the benefits
to costs. Benefits are positive flows, while costs arenegative flows. Thus, the savings in transport costs are
considered as benefits. If the benefit-cost ratio is morethan one, the project is worth undertaking. The advantageof the B/C ratio method is its simplicity; hence, it is widelyused by highway engineers.
4. MAINTENANCE AND TRANSPORTATIONCOSTS
The cost of road maintenance is a function of
pavement condition, the rate of deterioration and themaintenance standard applied by a road agency.
Transportation costs comprise the costs of vehicle
operation and travel time.
5. TRAFFIC GROWTH STUDY
Based on the traffic volume data between 2015
and 2018, the 3-year growth factor between 2015 and2018 would be 1.749. Assuming linear growth in the
future, the annual growth rate would be (1.749–1.0) /3 =0.249, or 24.9% on this highway

Table 1. Maintenance Costs of Yangon-Bago Highway(Year 2015-2018)Year
2015-20162016-20172017-2018
Total

Maintenance Costs(kyats million)
3200.33143.81061.67405.7

Table 2. Collected Toll Fees (kyats million) for YangonBago Highway (Year 2018)
Htauk Kyant
Bago Toll
Toll
2018
5098.078

6110.8028

Table 3. Vehicle Operating Cost (VOC)2018
To BagoTo Yangon
Annual Cost
9,748,101,505
7,469,981,801(kyats)Total Annual Cost
17,218,083,306(kyats)All financial costs are converted into economic
costs by applying a Standard Conversion Factor (SCF) of
0.85
From this analysis,• Net Present Value (NPV) = 9527,548,680 kyats• Benefit-Cost Ratio (BCR) = 1.63 %• The rate of return considered desirable fortransport infrastructure projects = 12 %.
6. CONCLUSIONS
The results of economic appraisal in most cases
will show that the economic returns from roadmaintenance far exceed those from investments in newroad construction. In countries where the road condition is
generally good but with high volumes of traffic, economic
appraisal will generally show that investments in capacity
improvement will generate higher economic returns.
REFERENCES[1] Henry Kerali. Economic Appraisal of Road Projects in
Countries with Developing and Transition Economies.
July 2003.

255

STUDY ON CHANNEL MIGRATION ASSESSMENT IN BRIDGE AREAS ALONG AYRYARWADY
RIVER
MYINT MYAT OO1, CHO CHO THIN KYI2, and WIN WIN ZIN3
Staff Officer, DUHD, Ministry of Construction, Nay Pyi Taw, Myanmar,
Associate Professor, Civil Engineering Department, Yangon Technological University, Yangon, Myanmar,
3
Associate Professor, Civil Engineering Department, Yangon Technological University, Yangon, Myanmar,
1

2

Keywords: Channel Migration, Bridge Sustainability, Erosion-Deposition, Remote Sensing, Satellite Imagery
1. INTRODUCTION
Rivers and streams are self-regulatory in that they
adjust their forms in response to environmental changes
which may occur naturally or sometimes may be resultsof human activities. Both activities distort the natural
quasi-equilibrium of a channel [1]. It is vital to monitor
the migration of channel which can provide the important
information for analysis of river morphology. River
monitoring can also be recognized as a key issue for rivermanagement and training [2]. Recent developments inremote sensing technologies opened up unprecedented
capabilities to perform high quality monitoring programfor a wide range of environmental fields including river
systems [3]. The goal of this study is to assist the bridge
monitoring works by means of remote sensing and GIS
techniques which are currently undertaking by Ministry ofConstruction with conventional techniques.
2. STUDY AREA
The Ayeyarwady River is the most importantcommercial waterway and the backbone of the country. It
is originated from the confluence of Maikha and Malikha
Rivers and flows relatively straight North to South before
emptying through the Ayeyarwady Delta into theAndaman Sea. The total length of Ayeyarwady River isabout 2,210 km and 15 bridges along the Ayeyarwady
river according to Ministry of Construction. But Maubin
Bridge and Daydaye Bridge are excluded from the study
because both bridges and not located on the main channelof the Ayeyarwady River. All of Ayeyarwady bridges areconstructed as steel truss bridges with concrete pierfoundation. The lengths of bridges are ranged between
750 m and 4120 m.
3. METHODS AND MATERIALSThe data set of Landsat Imagery is obtained from the
US Geological Survey (USGS) Global Visualization
Viewer including the archives of Landsat 5 Thematic
Mapper (TM), Landsat 7 Enhanced Thematic Mapper
Plus (ETM+), and Landsat 8 Operational Land Imager
acquired between 1987 and 2017. For the processing andanalysis of satellite imagery, Google Earth Engine is used.
In order to detect the changes of the channel between 1987
and 2017, the surface water of the river in each temporal
image was extracted individually.
4. RESULTS AND DISCUSSION
The study period of my research is between 1987 and2017. According to the study, the bridges along the
Ayeyarwady River can be divided into three main groups,
bridges in low, moderate and high migration areas
respectively. Bridges located in the upper Ayeyarwady are
fronting with the low channel migration, while bridges
located in central Ayeyarwady and delta area are facing

256

with the threats of high channel migration as shown in
Table 1. Although most of the bridges are located on theleast channel migration point of each bridge site, some of
the bridge sites are not meet the criteria required for thebest site for the bridge, for example, (i) Bo Myat Tun
Bridge, (ii) Ayeyarwady Bridge (Nyaungdon), (iii)
Ayeyarwady Bridge (Pakokku), and (iv) Ayeyarwady
Bridge (Tigyaing). Among these bridges, Bo Myat Tun
Bridge is a bridge which faced the obvious amount of
threat from channel migration during the study period inwhich the channel near the Bo Myat Tun Bridge has thetendency of shifting to the right by means of erosion at theright bank and deposition at the left bank which is the
major threat to bridge sustainability.
Table 1. Channel Migration of Ayeyarwady Bridges
BridgeMigration Location
Bala Min Htin Bridge
Moderate
Upper
AYY Bridge (Sinkhan)
Low
Upper
AYY Bridge (Tigyaing)
Moderate
Upper
Yadana Thinga Bridge
Moderate
Upper
AYY Bridge (Yadanabon)
High
CentralInnwa Bridge (Sagaing)
High
CentralAYY Bridge (Pakkoku)
HIghCentralAnawrahtar Bridge
High
CentralAYY Bridge (Magway)
High
CentralAYY Bridge (Malun)
Low
CentralNawaday Bridge
High
CentralAYY Bridge (Nyaungdon)
High
Delta
Bo Myat Tun Bridge
High
Delta
5. CONCLUSION
In this study, the channel migration in bridges areas
along Ayeyarwady River can easily be identified
throughout the study period by using remote sensing and
GIS techniques. Most of the high channel migration areas
are found in delta and central Ayeyarwady. The channel
migration in each bridge is subjected to various causes.
This study is carried out based on the 30-m resolution
Landsat imagery dataset and there will be better result forriver monitoring if finer satellite images are available.
REFERENCES[1] D. Rosgen, H.L. Silvey, Applied River Morphology,
2nd Edition, Wildland Hydrology, Colorado, 1996.
[2] R. Koech, P. Langet, L. Kumar, Monitoring River
Channel Dynamics Using Remote Sensing and GIS
Techniques, Geomorphology, Volume 325 (2018) 92-102.
[3] M.G. Tulbure, M. Broich, S.V. Stehman, A.
Kommareddy, Surface water Extent Dynamics from Three
Decades of Seasonally Continuous Landsat Time Series at
Subcontinental Scale, Remote Sens. Environ, 2016.

IMPROVING HISTORICAL REANALYSIS DATASET FOR HYDROLOGICAL MODELLING BY
INTEGRATING LIMITED OBSERVED DATA AND BIAS CORRECTION
S.S. BHAGABATI1, A. KAWASAKI2 and M. OGAWA3
Project Researcher, Department of Civil Engineering, The University of Tokyo, Tokyo, Japan,
Project Professor, Department of Civil Engineering, The University of Tokyo, Tokyo, Japan,
3
Associate Professor, International Education Center, Kanazawa University, Kanazawa, Japan
Correspond to S.S.BHAGABATI (seemanta@hydra.t.u-tokyo.ac.jp)
1

2

Keywords: Nineteenth century, historical analysis, bias correction
1. INTRODUCTION
Droughts are natural disasters that affect agriculture,
flora and fauna, natural resources as well as disrupt human
livelihood. Globally they affect millions of people
annually and over a million people had died as a result ofdroughts since 1974 [1]. Droughts are quite common
natural disaster in India, with one drought in every three
years in some part of India [2]. The biggest and most
severe drought happened in the year 1876, claiming over
5 million lives, the effects of which lasted until the year
1878. It was termed as the “Great Famine”.
2. METHODOLOGY
Although there has been some statistical analysis of theGreat Famine, spatial analysis including the extent andseverity has not been conducted. The primary reason
being the lack of observed datasets in the Nineteenth
century (as advanced hydrological models require
multitude of datasets).
In recent years, multiple reanalysis datasets have beenreleased which provides a continuous global gridded
dataset for many different meteorological andhydrological parameters. Although, the availability ofsuch data for the Nineteenth century is very limited. One
such dataset which contains these datasets is the NOAACIRES
Twentieth
Century
Reanalysis(V2c)(https://www.esrl.noaa.gov/psd/data/gridded/data.20thC_
ReanV2c.html). It contains data for 1851-2012.
But upon conducting quality check for the recent years(unable to conduct quality check for earlier years due tolack of available/base data), by using JRA55(https://jra.kishou.go.jp/JRA-55/index_en.html) as basedata, it was found that it contains large bias.

Figure 1. Box plot of bias of a location for 1991-2014
Fig 1 shows the box plot of the overall monthly bias fora location over for the time period 1991-2014. Upon
further checking it was found that bias both temporal andspatial i.e., it has different characteristics of bias fordifferent locations and time periods (figure 2)

Figure 2. Comparison of spatial bias of two locations inthe south-western India for the years 1991, 2001 and 2011.
3. CONCLUSIONSIn this research we are trying to bias correct a historicalreanalysis dataset in order to use it to conduct advancedhydrological simulations, thereby reconstructing the Great
Famine in the Indian sub-continent. So far, we haveidentified the characteristics of the different biases for thedifferent grids over the Krishna River basin located in thewestern India. Next step is to develop an approach to use
the current biases as a reference point to correct the
NOAA dataset for nineteenth century. This is currently awork in progress.
REFERENCES[1] United nations (UN): Trends in Sustainable
Development 2008–2009. United Nations publication,
United Nations Division for Sustainable Development(2008)[2] M.K. Goyal, V. Gupta, S. Eslamian. HydrologicalDrought: Water Surface and Duration Curve Indices.
Handbook of Drought and Water Scarcity: Principles ofDrought and Water Scarcity, 2017257

Study on code of practices for quality control, healthand safety management in construction industry
Htet Wai Yee Aung1
1
Master of Science in Engineering, Construction Management,
Civil Engineering Department, Yangon Technological University,
Myanmarhtetwaiyee@gmail.com
ABSTRACT
Nowadays, Myanmar construction industry has developed in recent years but still need to improve thequality control, health and safety management in construction industry. Therefore, this paper mainly
focuses on the study of the code of practices for the quality control and health and safety management inconstruction industry, Yangon, Myanmar. Firstly, field observation and questionnaires survey are carriedout to know the existing quality control, health and safety management in some construction projects. Afterthat the code of practices for quality control, health and safety management for the selected case study
Reinforced Concrete Building project are prepared by using checklists. This paper provides the checklists
for substructure, superstructure and finishing works in accordance with the approved code of practices
such as Myanmar National Building Code and other international codes of practice such as American
Society for Testing Materials, American Concrete Institute for quality control checklists, Work Health and
Safety Code of Practice 2015 – Safe Work Australia and Occupational Health and Safety and Working
Conditions 2019 for health and safety checklists. The findings of the study showed that some quality
problems are occurred in construction projects that can damage the end user safety and lack of health andsafety management can cause accidents or injuries for employees in project site. Similar dimensions andoutcomes make it feasible to combine quality and safety management into a single high-performancesystem. As a result, the health and safety management can enhance the quality control system. From
construction management point of view, time and cost can be saving and quality can be improved by
combining the quality control and health and safety management as a single high performance system.
Key works: questionnaires survey, code of practices, quality control, health & safety management

1. INTRODUCTION
Quality control and safety management are increasingly important in construction industry.
Quality Control is the part of quality management system focused on fulfilling quality
requirements, whereas quality assurance is the part focused on providing confidence that
quality requirements will be fulfilled. The Quality Management System (QMS) in
construction industry refers to quality policy, planning, implementation, measure andevaluation, management reviews and continual improvement. Quality control is criticallyimportant to a successful construction project and should be adhered. Inspection during
construction will prevent costly repairs after the project is completed [1]. A good quality
control system can also be ensured the workplace safely. Thus the safety workplace gives thegreat quality from construction management view. From safety perspective – Workplace
Health and Safety Management is prepared for the Occupational Health and Safety,
Environmental Impact Assessment, preventive or mitigation measures are prepared for theEnvironmental Safety, Quality Assurance and Quality Control are prepared for the End user258

December 2019, Yangon, Myanmar

Safety. In health and safety management systems – policy, organizing, planning, measuring,audits and review are concerned [2].
2. AIMS AND OBJECTIVE(1) To understand the importance of quality control system and safety management inconstruction industry(2) To know the code of practices which are widely used in Myanmar constructionindustry(3) To improve the quality control and health and safety management that are based oncode of practices.
3. EXISTING CONDITIONS OF QUALITY CONTROL, HEALTH AND SAFETY
MANAGEMENT
There are nine selected case study projects which are situated in Yangon, Myanmar. All
projects are constructed by local contractors. The case study projects are shown in table 1.
Table 1: Summary of case study projects
No
1
2
3
4
5
6
7
8
9

Company
Project 1
Project 2
Project 3
Project 4
Project 5
Project 6
Project 7
Project 8
Project 9Storey4-Storey
4-Storey
4-Storey
4-Storey
3.5-Storey
4-Storey
5-Storey
4-Storey
4-Storey

Type
RC
Steel
RC
Steel
RC
Steel
RC
Steel
Steel

Location
Bahan Tp.
East Dagon Tp.
Insein Tp.
East Dagon Tp.
Thilawa Thanlyin Tp.
East Dagon Tp.
Thanlyin Tp.
East Dagon Tp.
East Dagon Tp.

The observations of quality control and health and safety management for the selected casestudy projects are presented as follows: The questionnaire survey and results for quality data,
survey results based on checklists for quality control in case study projects are presented. The
questionnaire survey and results for health and safety management, survey results for
accidents in case study projects are also presented in the following.
3.1 Questionnaire Survey and Results for Quality Control in Case Study Projects
There are two types of respondents participated in the questionnaire survey. They are workers
and engineers. The respondent rate is 35% of workers and 65% of site engineers respectively.
3.1.1 Visual survey in case study projects
According to the visual survey, some of the quality defects were occurred in case study
projects such as the honeycombs occurred in the wall, the concrete cracking occurred at apron
and drain and the partition is damaged because of the poor quality are described in thefollowing figures.
New Technologies for Urban Safety of Mega Cities in Asia

259

(a)
(b)
(c)
(d)
(e)
Figure 1: (a, b, c) Wall honey comb, (d) Concrete cracking at apron and drain, (e) Poor quality
in partition
3.1.2 Surveyed Results for Quality Control in Case Study Projects
The quality data including policy, plan, procedure, checklists, inspection, testing andmaintenance are surveyed from project 1, 2, 3, 4, 5, 6, 7, 8 and 9. The percentage of quality
data in policy is 44.44, the percentage of plan is 44.44, the percentage of procedure is 44.44,
the percentage of checklists is 56.56, the percentage of inspection is 66.67, the percentage oftesting is 66.67 and the percentage of maintenance is 44.44. The surveyed data for citation
projects are described in Table 2.
Table 2: Surveyed data for quality in case study projects
No

CompanyStoreyType

1

Project 1

4-StoreyRC

2

Project 2

4-Storey

Steel

3

Project 3

4-StoreyRC

4

Project 44-Storey

Steel

5

Project 5

3.5Storey

RC

6
7
8
9

Project 64-Storey Steel
Project 75-StoreyRC
Project 84-Storey Steel
Project 94-Storey Steel
Percentage of Quality Data

YES

Quality Data

PolicyPlan

Proced
-ure

Check
list

Inspec-tion

Testing

Mainte-nance

44.44

44.44

44.44

55.56

66.67

66.67

44.44

NO

The project 1, 3, 5 and 7 are 100 % in quality data including inspection, testing, checklists,
policy, plan, procedure and maintenance. The project 2 is about 42.86 % and the project 4 isabout 28.57%. The project 6, 8 and 9 are zero percentage in quality data. The surveyed results
for case study projects are described in Table 3.

260

Study on Code of Practices for Quality Control, Health and Safety Management in Construction
IndustryDecember 2019, Yangon, Myanmar

Table 3: Surveyed results for the case study projects
Quality Data
No

Company

Project 1,3,5,7
2
Project-2
3
Project-4
Project4
6,8,9
YES
1

StoreyType

4-Storey

PolicyProcedure

Plan

RC

%

Check- Inspect Test- Maintlist-ion
ing enance100

4-Storey
4-Storey

Steel
Steel

42.86
28.57

4-Storey

Steel

0

NO

3.1.3 Surveyed Results for Quality Control Based on Checklists in Case Study Projects
The checklists are also used to investigate the quality control in case study projects. The
checklist for surveying and setting out, checklist for earthwork, checklist for backfilling,checklist for formwork and reinforcement, checklist for brick and block masonry, checklist
for flooring, checklist for external and partition wall, checklist for plastering, checklist for
painting, checklist for interior ceiling and checklist for fabrication work are used to determine
the existing condition of quality control in case study projects. The surveyed results for
quality control in case study projects are described in figure 2.
Checkl ist for fabri cation work
Checkl ist for plast ering and paint ing
Checkl ist for flooring
Checkl ist for formwork,…
Checkl ist for Surveying and setting…
0

2

NO

YES

4

6

8

10

Figure 2: Surveyed results for quality control using checklists
According to the surveyed results from figure 2, most of the work activities are not complied with the
prepared checklists and the checklists are not based on the code of practices. Therefore, as a result, thequality has damaged for these projects and the end user safety can be damaged.
3.2 Questionnaire Survey and Results for Health and Safety Management in Case Study Projects
There are two types of respondents participated in the questionnaire survey. They are workers
and site engineers. The respondent rate is 96% of workers and 4% of site engineersrespectively.
3.2.1 Surveyed Results for Safety(a)Figure 3: (a, b) Questionnaire survey for safety(b)

New Technologies for Urban Safety of Mega Cities in Asia

261

According to the surveyed results for safety from figure 3, the answers “NO” and “DON’T KNOW”
from the respondents had more percentage than the answers who said “YES”. There have no safety
culture and tool box meeting. Besides, the workers did not know exactly the location and usage of fire
extinguisher. There have no sufficient personal protective equipment for workers. Only 38% of
respondents said that their site provided about safety and about 44% of respondents said that
their site did not provide safety. About 18 % of respondents said that they did not know about
safety as shown in figure 3.
3.2.2 Surveyed Results for Health(a)(b)
Figure 4: (a, b) Questionnaire survey for health
According to the survey results for health from figure 4, there have no smoking area for workers, nosufficient purified drinking water and good toilets and basins for employees. Only 26% of respondents
said that their site provided about health and about 67% of respondents said that their site did
not provide about health and safety. About 7 % of respondents said that they did not know
about health and safety as shown in figure 4.
3.2.3 Surveyed Results for Welfare(a)Figure 5: (a, b) Questionnaire survey for welfare(b)According to the survey results for welfare from figure 5, there have no physical exercises and nocanteens for workers. The welfare facilities are poorly prepared in the proposed site. Only 12% of
respondents said that their site provided about welfare and about 63% of respondents said that
their site did not provide about welfare. About 18 % of respondents said that they did notknow about welfare as shown in figure 5.

262

Study on Code of Practices for Quality Control, Health and Safety Management in Construction
IndustryDecember 2019, Yangon, Myanmar

3.2.4 Surveyed Results for Accidents in Case Study Projects
The accidents were found in case study project because there have no good health and safety
management and without any remedial actions when causing the accidents. Some accidents such as
falls from height, struck by a moving vehicle, struck by falling objects, rebar impalement
hazard, scaffolding collapse, transportation accidents, slips, trips and falls, chemical burns anddermatitis from wet concrete were occurred. These surveyed results are described in figure 6.
16
14
12
10
8
6
4
2
0

Figure 6: Surveyed results for accidents in case study project4.

IMPROVEMRNTMANAGEMENTOFQUALITY

CONTROL,HEALTHAND

SAFETYThe checklists for quality control and health and safety are prepared including substructure,
superstructure and finishing of the selected case study project because inspection checklist
forms are critical quality control tools for the entire construction industry. Then, health andsafety management can enhance the quality control system. Besides, the checklists for quality
control and health and safety are also based on the code of practices in order to improve thequality of construction projects and reduce quality deficiencies and some accidents inconstruction projects.
4.1 Case Study Project
The selected case study project is 4 stories RC residential building and located in
Mingalardon Township, Yangon. In order to improve the quality control and health and safety
management in this case study project, the quality control checklists and health and safety
checklists for substructure, superstructure and finishing are prepared. These preparedchecklists are also based on the code of practices such as Myanmar National Building Codeand other international code of practices.
4.2 Preparation of Checklists for Substructure, Superstructure and Finishing
The checklist for surveying and excavation, the checklist for backfilling, the checklist forretaining wall, the checklist for rebar installation, the checklist for concreting work and thechecklist for formwork are prepared for the substructure of the case study project that aredescribed in table 4. The Checklist for Rebar installation (before, during, after), the Checklist
for Formwork (before, during, after), the Checklist for Concreting (before, during, after) andthe checklist for brick work are prepared for the superstructure of the case study project thatare described in table 5. The Checklist for Roofing, Checklist for ceiling work, Checklist for
Plastering, Checklist for Painting, Checklist for Electrical Installation Work, Checklist for
Plumbing & Sanitary are also prepared for the finishing of the case study project that aredescribed in Table 6. The quality control checklists are based on Myanmar National Building

New Technologies for Urban Safety of Mega Cities in Asia

263

Code, American Society for Testing and Materials and American Concrete Institute. The
health and safety checklists are also based on the Myanmar National Building Code, Work
Health and Safety Code of Practice 2015 (Safe Work Australia) and Occupational Safety,
Health and Working Conditions, 2019.
Table 4: Preparation of checklists for substructure
Item

SUBSTRUCTURE

Code of Practices
for Health and
Safety1)Checklist for surveying -Myanmar
National -Work Health andand excavation
Building Code, 2016
Safety Code of-American Society for Practice 2015 (Safe2)Checklist for backfilling3)Checklist for retaining Testing and Materials Work Australia)
wall-Occupational
4)Checklist
forrebar -American Concrete
Safety, Health andinstallation (before, during, InstituteWorking
after)
Conditions, 20195)Checklist for concreting
work (before, during, after)6)Checklist for formwork(before, during, after)
Checklist’s Name

Code of Practices for
Quality Control

Table 5: Preparation of checklists for superstructure
ItemSUPERSTRUCTURE

Code of Practices for
Quality Control

Code of Practices
Checklist’s Namefor Health and
Safety1)Checklist
forRebar -Myanmar
National -Work Health andinstallation (before, during, Building Code, 2016
Safety Code ofafter)-American Society for Practice 2015 (SafeTesting and Materials Work Australia)2)Checklist for Concreting-American Concrete-Occupational(before, during, after)
Institute
Safety, Health and3)Checklist for formwork
Working Conditions,(before, during, after)
20194)Checklist for brick work
Table 6: Preparation of checklists for finishing

264

Item

Checklist’s Name

FINISHING

1)Checklist for Roofing2)Checklist for ceiling work3)Checklist for Plastering4)Checklist for Painting5)Checklist for Electrical
Installation Work
6)Checklist for Plumbing &Sanitary

Code of Practices
for Quality
Control-Myanmar National
Building
Code,
2016-American Society
for Testing andMaterials-American
Concrete Institute

Code of Practices
for Health and
Safety-Work Health and
Safety Code ofPractice 2015 (SafeWork Australia)-Occupational
Safety, Health andWorking Conditions,2019

Study on Code of Practices for Quality Control, Health and Safety Management in Construction
IndustryDecember 2019, Yangon, Myanmar

5. CONCLUSION
From the Construction Management point of view – Time, Cost and Quality are the key
elements. These key elements are also related to each other. From the time perspective – there
have no frequent repair, reconstruction and maintenance for the defects because of the goodquality control system. The time also saving because safety management can enhance thequality control system and can prevent the accidents and injuries of workers. From the cost
perspective– the good quality control and health and safety management can reduce the cost
overruns because there have no deficiencies or weakness about quality and no accidents or
injuries to employee about health and safety. From the quality perspective – the project canachieve target quality goal within the target time and specified budget with safe environment
for the employees throughout the whole project. By preparing the quality control checklists
and health and safety checklists based on MNBC and other international code of practices canprovide the good quality control and health and safety management for the constructionindustry. Besides, the checklists can be used in Myanmar construction industry because thesechecklists are based on Myanmar National Building Code that is intended to use forconstruction works in Myanmar.
ACKNOWLEDGMENT
The author would like to thank all of his teachers in Civil Engineering Department for theirsupporting, encouragement, useful suggestions, invaluable guidance and help till thecompletion of this journal.
REFERENCES[1] Anon. “Project Management for Construction, Chapter (13) Quality Control and
Safety during Construction” <http://www.cmu.edu>cee>PM book>.
[2] Phil Hughes and ED ferrette, “Introduction to “Introduction to Health and Safety inconstruction”, Fourth edition.
[3] Myanmar National Building Code, 2016.
[4] ASTM International, <https://www.astm.org>wiki>[5]ACI
Standard
Adoption–
https://www.concrete.org>standard.

AmericanConcrete

Institute,[6] Mr. Santash kumar Gangwar, 2019. “Occupational Health and Safety and Working
Conditions.”[7] Citation Case Study Projects from Ma Hsu Wutyee Htun, “Analyzing and CriticalThinking of Quality Problems for Construction Projects in Myanmar”.

New Technologies for Urban Safety of Mega Cities in Asia

265

DEVELOPMENT OF CUBIC SOIL CHAMBER FITTED WITH MULTI-DIRECTIONAL DISKTRANSDUCERS
Y. KAWAGUCHI1, M. OTSUBO2 and R. KUWANO3
Graduate Student, Institute of Industrial Science, The University of Tokyo, Japan,
Research Associate, Institute of Industrial Science, The University of Tokyo, Japan,
3
Professor, ICUS, Institute of Industrial Science, The University of Tokyo, Japan,
Correspond to Y.KAWAGUCHI (y-kawa@iis.u-tokyo.ac.jp)

1
2

Keywords: Elastic Wave Velocity, Model Experiment, Disk Transducer, Intrinsic Anisotropy, Dynamic Measurement
1. BACKGROUND
It is empirically known that the soil stiffnesses in thevertical and horizontal directions are not identical.
However, accurate measurement of multi-directional
stiffness is difficult; thus, the mechanism of the stiffness
anisotropy has not been fully understood. In many cases,
naturally existing ground has inherent anisotropy
depending on particle shape and deposition direction [1, 2].
Understanding fundamentals of the stiffness anisotropy
enables accurate prediction of ground deformation, which
contributes to reliable design of geotechnical structures.
2. SOIL CHAMBER
Aiming to develop a test device to evaluate the inherent
anisotropy of the soil stiffness accurately, a cubic soil box
equipped with disk-shaped piezoceramic transducers [3]in the three orthogonal directions was manufactured.
Tested materials were air-dried Toyoura sand and glass
beads, having the same median particle size of 0.24 mm
and 0.20 mm but with different sphericity. Glass bead isspherical but Toyoura sand has oval shapes. The model
ground was divided into 10 layers, and the dry material
was compacted in each layer. An overburden load of 2 kPa
was added vertically while the horizontal defamation wasrestricted, i.e. K0 stress state. S- and P-wave signals in x,y and z axes were measured for each material.
3. COMPARISON OF S-WAVE VELOCITY
Focusing on the three types of shear wave components,
SHH, SHV, SVH (the first and second subscripts stand for the
directions of propagation and oscillation), VS,HH for theglass bead sample is the largest, whereas VS,HH for the
Toyoura sand sample is the lowest. This agrees with theobservation in the field measurement that natural
materials tend to exhibit a largest VS,HH amongst the three
types [1]. Moreover, VS is generally greater in the Toyoura
sand sample than that in the glass bead sample in all axes
although the density is larger for the glass bead sample.
This may be due to effects of particle rigidity, the numberof contact points between particles, particle shape.
4. CONCLUSIONSThis study investigated the inherent anisotropy ofelastic wave velocity. The results revealed that nonspherical particles such as Toyoura sand exhibit a larger
elastic wave velocity that propagates and oscillates along
the horizontal plane although the horizontal stress is lower
than the vertical stress.

266

H: Horizontal V: VerticalFigure 1. Soil chamber and direction of wave propagation

SHH

SVH
SHV

e：0.552
spherical

Figure 2. S-wave propagation in glass bead sample

SVH
SHV

SHH

e：0.626
oval shape

Figure 3. S-wave propagation in Toyoura sand sample
REFERENCES[1] Clayton, C.R.I. (2011) Stiffness at small strain: research andpractice. Géotechnique, 61(1), 5–37.
[2] Santamarina, J.C. & Cascante, G. (1996). Stress anisotropy
and wave propagation: a micromechanical view. Can. Geotech.
Journal, 33(5), 770–782.
[3] Suwal, L.P. & Kuwano, R. (2013) Disk shaped piezo-ceramictransducer for P and S wave measurement in a laboratory soil
specimen. Soils and Foundations, 53(4), 510–524.

FORMATION AND EXPANSION OF SUBSURFACE CAVITYAND ITS POTENTIAL RISK OF COLLAPSINGR
R. KUWANO1, Y. OHARA2, and N. KOMINAMI2
Professor, ICUS, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan,
Former Graduate Student, Dept. of Civil Engineering, The University of Tokyo, Tokyo, Japan,
Correspond to Prof. Kuwano (kuwano@iis.u-tokyo.ac.jp)
1

2

Keywords: Sinkhole, Subsurface cavity, Ground cave-in
1. INTRODUCTION
A sinkhole or ground cave-in is usually initiated by theformation of cavity in the ground due to soil loss. Whenthe location of the cavity is deep in the ground, thedetection of the cavity is not easy. Then it is possible thatthe hidden cavity expands to eventually cause sudden
collapse.
In
thisstudy,
characteristics
offormation/expansion of cavity and surrounding groundloosening were investigated by a series of model tests,
aiming at evaluating potential risk of surface groundcollapse.
2. MODEL TEST OBSERVATION
Two-dimensional as well as three-dimensional cavity
formation tests were conducted using rectangular andcylindrical soil chambers having a small opening at thebase. Uniform clean sands were used for tested materials.
Water was supplied from either center or side of the soilchambers and soil with water was drained from the bottom
opening. Test apparatus are shown in Figure 1.

larger. The cover soil lost its stability when the width ofcavity grew too large.
When a wide cavity developed
in shallow ground, there is noroom for the arch action

When a narrow cavity isformed deep in the ground,the arch action works

××

Cover soil collapses

Water level

When water drains quickly, achimney-like narrow cavity forms

θ：angle ofreposeWhen water stays in the cavity,
fan-shape cavity develops
unstablearching

θ：angle ofreposeFigure 2. Cavity expansion process observed in two
dimensional tests
Figure 3 shows cavity formation in three-dimensional
tests. All cavities were chimney shape consisting ofdifferent diameters. Lower part had larger diameter, which
seemed to be influenced by the water level.

Laser displacement
sensor

10

-50

5

-100

0

0

A typical pattern of cavity formation and expansion
from two dimensional tests are shown in Figure 2. Whenwater drains quickly, a chimney-like narrow cavity
formed. The ceiling of the cavity was around the sameheight of ground water level. If water stays in the cavity,
fan-shape cavity develops and the width of cavity became

5
0

0

10

20

Location (cm)

30

20
15

0

10

-50

5

-100

0

0

10
20
Location (cm)

0
-20
-40
-60
-80
-100
-120
-140
-160
-180
-200

ground:20cm
water level:15cm

30

-150

Displacement (cm)Height: 40cmb) cylindrical soil chamber for three-dimensional tests
Figure 1. Test apparatus for cavity formation tests

-150

10

ground:15cm
water level:10cm
Displacement (cm)Impermeable
layer

Location (cm)

30

15

15
10
5
0

0
-20
-40
-60
-80
-100
-120
-140
-160
-180
-200

Displacement (mm)opening:
5mm

20Displacement (mm)Water supplied
from side

10

Displacement (cm)0ground:20cm
water level:10cm

Displacement (mm)15a) a rectangular soil chamber for two-dimensional tests

Loose sand20

Displacement (mm)Displacement (cm)ground:15cm
water level:5cm

Diameter: 30cm

collapse

010
20
Location (cm)

30

6/9

Figure 3. Cavity formation observed in three dimensionaltests
3. CONCLUSIONS
The result of two and three dimensional cavity tests
implied that the process of cavity formation can be divided
into two part, the first part influenced by ground waterlevel and the latter part affected by soil property.
Approximate depths of the cavity ceiling can be estimatedby the ground water level and the risk of collapse can beroughly evaluated by the ratio of depth of cavity ceilingand cavity width.

267

SHAKING TABLE TESTS ON EFFECT OF REINFORCEMENT STIFFNESSON SEISMIC STABILITY OF GEOGRID REINFORCED SOIL WALLS
J. KUWANO1, and A.A. AJUDA2
Professor, Department of Civil and Environmental Engineering, Saitama University, Saitama, Japan,
PhD student, Department of Civil and Environmental Engineering, Saitama University, Saitama, Japan,
Correspond to Prof. J. KUWANO (jkuwano@mail.saitama-u.ac.jp)
1

2

Keywords: geogrid, shaking table test, retaining wall, stiffness arrangement
800
200

650

500

Optical targets
for Image analysisii) Backfill Dr = 90%(Toyoura sand)50

2. TEST OUTLINE
Geogrid reinforced soil wall models were constructedin rigid container. 8 wall segments were placed on top ofeach other and no additional connection was madebetween the panels. One geogrid was connected to eachpane. Length and stiffness of geogrid were changed. Wall
1: all 300 mm stiff geogrids, Wall 2: all 200 mm geogrids,
Wall 3: 300 mm and 200 mm stiff geogrids alternatively,
Wall 4: 200 mm stiff and soft alternatively, Wall 5: Top 4
stiff and bottom 4 soft 200 mm geogrids, and Wall 6: Top4 soft and bottom 4 stiff 200 mm geogrids. The backfill
and soil foundation were constructed using dry Toyoura
sand to achieve the desired relative density of 90%.

Wall 4i) Foundation layer Dr = 90% (Toyoura sand)A1 - Accelerometer
Unit in (mm)1300

Figure 1. Test model (e.g rigid and soft alternatively)
Top Horizontal Displacement (cm)1. INTRODUCTION
Few studies are available for cases with multiple
reinforcement stiffness values along the wall. This study
attempts to investigate the effect of reducing thereinforcement stiffness value along the wall height indifferent manners under seismic load by means of shaking
table test using a sinusoidal wave with a predominantfrequency of 5 Hz.

10

Wall
Wall44Wall 2
Wall
2

8
6
4
2
0

0

200

400

600

Input base acceleration (gal)

3. EFFECT OF STIFFNESS ARRANGEMENT
Figure 2 shows the relationships of top displacement
and base acceleration, and the shear strain for the tested
walls. It is noted that wall with stiff uniform reinforcement(Wall 2) have more stability. However, by substituting halfof the stiff geogrid with soft geogrid in an alternatingmanner (Wall 4), the wall showed almost the same amountof displacement as Wall 2. By grouping the soft
reinforcement either in the upper (Wall 5) or lower part
(Wall 6) of the wall, the walls showed an increase inhorizontal displacement and bulging phenomena at midheight around critical stages. The shear strain wasdependent on the geogrid stiffness arrangement. The
lowest values of shear strain were observed for wall withstiff geogrid (Wall 2) followed by wall with alternating
stiffness (Wall 4), while, walls with grouped schemes(Walls 5 and 6) showed larger values of shear strain,suggesting the backfill movement was more compared toWall 2. The failure surface observed in shaking table test
(blue line) and obtained in two-wedge analysis (red line)
are shown in the figure. The failure surfaces of the wallswith different geogrid stiffness arrangements were almost
same as the wall with uniform stiffness geogrids.

268

Figure 2. Top displacement and base accel. (Walls 4 &2)
Wall 5Wall 2

Figure 3. Top displacement and base accel. (Walls 5&2)
Wall 6

Wall 2

Figure 3. Top displacement and base accel. (Walls 6&2)

SESSION H
SPECIAL SESSION: SATREPS/ WATER RESOURCES, DISASTER
MITIGATION AND URBAN PLANNNING

CLIMATE CHANGE SCENARIOS IN MYANMAR USING MRI-AGCM3.2S MODEL
W.W. ZIN1
1

Professor, Department of Civil Engineering, Yangon Technological University, Yangon, Myanmar,
Correspond to Prof. Win Win Zin (winwinzin@gmail.com)

Keywords: Climate change, MRI-AGCM3.2S, Myanmar
1. INTRODUCTION
Myanmar ranked second out of 183 countries mostaffected by extreme weather events between 1995 and2014 in the Global Climate Risk Index [1]. Climatechange threatens to compound the frequency and intensityof these events and, more importantly, to alter theconditions to which human and natural systems haveadapted over millennia [2]. Myanmar is now facing theimpacts of climate change, which threaten to undermine
our development prospects and exacerbate thevulnerability of our communities. With projected changes
in precipitation and temperature, considerable efforts
would be required to prepare the Myanmar in dealing with
the impacts of climate change on the different climatesensitive sectors.
In the present study,
MRI-AGCM3.2S was used tosimulate both the present-day climate (1981-2005) andprojected climate for near future (2020-2044) and far
future (2075-99) under the IPCC A1B scenario. MRIAGCM3.2S is developed by the Meteorological ResearchInstitute (MRI) and Japan Meteorological Agency (JMA).
In this research, 84 stations are considered to calculate therainfall percentage departure of Myanmar. 43 stations are
considered to calculate the temperature change of
Myanmar.
2. RESULTS AND DISCUSSION
The bias-correction was performed using two
different techniques: linear scaling and lumped quantile
mapping. Bias correction is capable of improving the
GCM-simulated outputs to a certain degree. When only
few stations are located within the region, these data sets
do not capture the realistic distribution in this large area.
In that case, it is difficult to obtain actual distribution fromvery limited number of observation. It is seen that lumped
quantile mapping method is better than linear scaling
method. Performance of bias correction was quantified bycoefficient of determination (R2) and root mean squareerror (RMSE). It was seen that the projected precipitation
will increase in 2030s and 2080s under A1B scenario.
Average annual precipitation change in future (20752099) relative to 1981-2005 base period is shown in
Figure 1.
3. CONCLUSIONSThe present and future average rainfall of Myanmar
was observed to fluctuate, but have shown an increasing
trend.

270

Figure 1. Average Annual Precipitation Change in Future(2075-2099) Relative to 1981-2005 Base Period
For future climate in 2030s and 2080s, outputs of thesimulations under the A1B scenario are presented. The
key findings are:• Annual maximum temperatures
are expected
to rise by 0.2 °C to 1.6 °C in 2030s;• Annual maximum temperatures are expected
to rise by 0.7 °C to 3.6 °C in 2080s;• In every region of Myanmar, rainfall is expected
to increase by the middle and end of century
REFERENCES[1] Kreft, S., Eckstein, D., Junghans, L., Kerestan, C., andHagen, U. Global Climate Risk Index 2015: Who Suffers
Most From Extreme Weather Events? Weather-Related
Loss Events in 2013 and 1994 to 2013. In: G. K. Joanne
Chapman-Rose, Daniela Baum (Ed.), Berlin, Germany:
Germanwatch, 2014,pp. 32.
[2]. Horton, R., De Mel, M., Peters, D., Lesk, C., Bartlett,R., Helsingen, H., Bader, D., Capizzi, P., Martin, S. andRosenzweig, C. Assessing Climate Risk in Myanmar.
New York, NY, USA: Center for Climate Systems
Research at Columbia University, WWF-US and WWFMyanmar, 2016.

Development of flood inundation map using HECHMS and HEC-RAS
Wai Toe1, Win Win Zin2, Zin Mar Lar Tin San3,
and Akiyuki KAWASAKI4
1
Master Student, Department of Civil Engineering, Yangon Technological University,
Myanmarwaitoe.water7@gmail.com
2
Professor, Department of Civil Engineering, Yangon Technological University,
Myanmarwinwinzin@gmail.com
3
Professor, Department of Civil Engineering, Yangon Technological University,
Myanmarzinmarlar@gmail.com
4
Professor, Department of Civil Engineering, The University of Tokyo, Japan

ABSTRACT
Flood is a common natural disaster that causes damages to life and property and also
effects the development of a country. 41990 people from Bago Township, 40 percent of
the total population, were struck by Bago Riverine Flood in 2018. The flood inundation
maps are developed using the Hydrologic Engineering Center – Hydrologic Modeling
System (HEC-HMS) and Hydrologic Engineering Center – River Analysis System (HECRAS) models. Firstly, flood events from 2014 to 2018 were selected for calibration andvalidation of the rainfall-runoff correlation in the hydrologic modeling system.
Furthermore, different return periods were also considered in the rainfall-runoff analysis.
The steady flows with different return periods such as 10-year, 50-year, 100-year with theeffect of Zaung Tu Dam were considered in the river analysis modeling system to evaluate
the flooded depth. In addition, river cross-sections and High-Resolution Digital Elevation
Model (DEM) were used to develop flood inundation maps using the 2D HEC-RAS model.
The developed 2018 flood inundation map was compared with the 2018 flood inundation
map extracted from the Synthetic Aperture Radar (SAR) image. Applications of theapproach presented in this study lead to flood mitigation using different scenarios andapproaches.
Keywords: Bago River, HEC-HMS, HEC-RAS, flood, rainfall-runoff analysis271

1. INTRODUCTION
Floods are the most common natural disaster that can be occurred around the world. It
causes significant damage to human life, infrastructures, social, health, and economy. A
natural disaster such as flood obstruct the development of a country and it becomes nosurprise that flood mitigation and flood risk reduction has become the most importantconsideration in many countries around the world. Some researcher say that Myanmar isthe second most natural disaster-prone country in the world and also the most 15th country
in the world which are struck by the floods due to climate change. In Myanmar, heavy
storm rainfall from southwest monsoons causes many flooding from July to October.
Flooding in the central plain and coastal areas caused by the heavy rainfall in themountainous region mostly north, east and west sides of the country. Myanmar’s climate
is influenced by the circulation of India Monsoon and the central dry zone and the
Ayeyarwady delta are facing extreme events such as extreme drought and extreme floods.
In July 2015, eleven states and regions among fourteen states and regions in Myanmar
were struck by seasonal monsoon flood, Kachin state, Chin state, Shan state, Rakhine
state, Mon state, Kayin state, Sagaing region, Magway region, Mandalay region,
Ayeyarwady region, Bago region, Yangon region. Among them, the worst four flooding
areas, Magway region, Sagaing region, Chin state, and Rakhine state were declared by
the Myanmar Government as a natural disaster zone. According to the Relief andResettlement Department (RRD), the number of people between 67000 and 110000
throughout the whole country was affected by the 2015 monsoon flood and 125 people
were killed by the flood. Ministry of Agriculture reported that 687200 acres of farmland
have been inundated and damaged by the flood. 2015 monsoon floods in Myanmar causedby the tropical cyclone Komen and it impacted not only social but also economic of thecountry.
Just recently 2018, the Magway region, the Bago region, the Tanitharyi region, Kayinstate, Mon state were hit by the 2018 monsoon flood. About 150000 people have been
displaced by 2018 monsoon floods and at least 16 people had died as stated by the
Department of Disaster Management (DDM). Although about 122000 people still
displaced at 263 evacuation sites, some of them have returned to their homes from
evacuation sites. The Union Government also led to a response in cooperation with theState and Regional Government and also with the help of international and nationalorganizations such as the UN, NGOs and civil society. 71,898 people have evacuated theirhomes during the 2018 monsoon flood in the Bago region. In other areas, 25083 people
in Kayin state, 18421 people in Mon State and 6583 people in Tanintharyi Region
displaced to their home. There were also about six fatalities in Mon state and five fatalities272

in Tanintharyi Region.
Bago Region is the most affected region in the 2018 heavy monsoon flood and this region
suffers the risk of flood year after year. According to historical flood records in the Bago
region, the 2018 monsoon flood is the most severe flood within 53 years. The recorded
water level of Bago City near Bago Bridge exceeded the danger water level (880 cm) andreached up to 936 cm on 29th July 2018. It was the highest record since 1966 and it kept
on 6 days above the danger water level. Most of the floods in the Bago region occur inJuly and August of a year, that means monsoon floods mostly occur. In 2011, the heavy
flood with the water level of 959 cm occurred in the Bago region and it damaged many
agricultural lands. The flood record in 2014 was 936 cm hit the Bago Region with the lossof paddy fields. And another high flood occurred at the end of July 2018 and according
to the Department of Disaster Management (DDM), 41990 of people displaced their home
as a result of the flood. Moreover, A lot of agriculture land was damaged by the 2018
monsoon flood. Although structure countermeasures were constructed to mitigate the riskof floods at the upstream of Bago River Basin, suitable flood management and flood
protection systems are needed to analyze.
In view of the above and severity of the damages and fatalities caused by extreme flood
events, it is requisite to establish the near real-time flood protection techniques. There is
no doubt that the flood hazard map is basic to analyze flood protection systems and floodrisk management. Moreover, it can reduce the impacts of the flood on the likelihood
and/or the impact of flood risk based on scientific research and findings. The mapping of
the flood hazard integrates with the schemes of flood prevention, protection, preparedness,
emergency response, risk reduction, and risk management. More importantly, the floodmodel can also be used to create hazard maps that indicate the levels of inundation due torainfall events of varying recurrence intervals. In this research, the flood inundation mapof the Bago River Basin was developed by coupling HEC-HMS (Hydrologic Engineering
Center Hydrologic Modelling System) and HEC-RAS (Hydrologic Engineering Center River Analysis System) with the geographical information system. And the flood hazard
maps are developed with different scenarios to mitigate the risk of Bago riverine flood.
Flood modeling to develop flood hazard maps includes the transformation of rainfall intoa runoff hydrograph throughout a watershed and/or the transformation of runoff into an
overland flow that is performed hydraulically. Modeling of flood applies to understand,assess and predict the flood risk on the human society and natural system. Additionally,
it can generate the flood hazard maps which indicates the levels of inundation,consequently, a timely warning can be issued to the people in the affected area.
The general purpose of this research is to develop the flood inundation map by realizing273

the solutions which can mitigate the risk of flooding in the Bago River Basin. This goalis performed by addressing the following modeling systems; (1) hydrologic modelingsystem by using HEC-HMS in rainfall-runoff-inundation processes of the river basin and
HEC-GeoHMS extension in ArcGIS to delineate the watershed from DEM; (2) hydraulicmodeling system by using HEC-RAS for the river analysis system of the study area and
HEC-GeoRAS in ArcGIS for the preprocessing and postprocessing of flood inundation
map developing; (3) compare the flood inundation maps developed in (2) with the ones
developed using SAR image for the same area. These all objectives are carried out by thehigh-resolution digital elevation model (DEM), surveyed cross-section data,
meteorological and hydrological data from DMH, DHPI, and IWUMD.
2. STUDY AREA AND DATA ANALYSIS
2.1 Study Area
The hydrologic model and hydraulic model were applied to the study area; the Bago River
Basin is listed in figure 1. Bago river originates from the Bago Yoma which is a range of
upland between the Ayeyarwady river and Sittaung river. The river flows through Bagoand Yangon regions and combines with Yangon river (Myitmaka river) and Pazundaungcreek and then enters the Gulf of Mottama. The Bago River Basin approximately locates
between 17° 13' 37.511" and 18° 25' 46.434" of North latitude and 95° 54' 36.623" and96° 30' 45.228" of East longitude in Bago region, Myanmar. It has a drainage area of 2725
km2. It covers a majority of Bago Region especially 74 percent of the total catchment
area in Bago District and 26 percent of the total catchment in Thar Yar Wady District.
Bago river is used predominantly for the purpose hydropower generation by DHPI at the
upstream of river and the other reservoirs Kodukwe, Salu, Shwe Laung, Mazin and
Zalukhtaw reservoirs located at the upstream of Bago river’s tributaries (Mazin and
Zalukhtaw reservoirs are at the downstream). Most of the reservoir was constructed forthe purpose of flood protection and irrigation in 2012. But the floods still occur manytimes. Figure 1 shows the location map of the study area and rainfall – water level stationsin the Bago River Basin. The basin is composed by the mountainous region at the
upstream of river and the low land areas at the downstream.
The length of Bago river from Zaung Tu Hydropower Dam to Zaung Tu Weir is about
90.38 km, the river starts from the downstream of Zaung Tu Dam and then flows freely.
The length of the river from Zaung Tu Weir to Bago Bridge is about 33.08 km and thelength from Bago Bridge up to Tarwa Gate is about 15.61 km long. Most of the river front274

areas are replaced by farm lands and residential areas. According to the information basedon the year 2015 land-used-land-cover map derived from SERVIR Mekong Land CoverPortal, the Bago River Basin is composed of 0.3 % of built-up areas, 40 % of mixed
Evergreen and deciduous, 23 % of Evergreen Broadleaf and 15% of crop land, 1.8 % of
Rice Paddy Field and other types of land covers. Built-up areas and Agricultural lands aremostly located in the floodplains of Bago River and the Bago city is at the downstreamof Bago River. Figure 2 lays out the land use map from SERVIR Mekong Land CoverPortal in (a), the soil map in (b) and the high-resolution digital elevation model in (c).

The hydrologic soil texture of Bago River Basin are Group C and Group D whichconstitute 81.03% of the total area followed by HSG Group C and 18.97% of the total
area by HSG Group D. The four Hydrologic Soils Groups are A, B, C and D where soil
group D has the greatest runoff potential. Group C soils are sandy clay loam. They have
low infiltration rates when thoroughly wetted and consist chiefly of soils with a layer that
impedes the downward movement of water and soils with moderately fine to fine structure.
Clay, clay loam, silty clay, silty clay loam and sandy clay consist in the hydrologic soil
group D. This HSG has the highest runoff potential and they have very low infiltration
rates when thoroughly wetted and consist chiefly of clay soils with a high swelling275

potential and a permanent high-water table, moreover soil which is at or near the surface
and over nearly impervious material.

Figure 2. (a) land use map from SERVIR Mekong Land Cover Portal, (b) the soil map of
Bago River Basin and (c) the high-resolution digital elevation model (Source: from
Seemanta Bhagabati).

Figure 1. (a) land use map from SERVIR Mekong Land Cover Portal, (b) the soil map of
Bago River Basin and (c) the high-resolution digital elevation model (Source: from
Seemanta Bhagabati).
2.2. Data Analysis
The calibration and validation of the model based on the available data set from the
Department of Meteorology and Hydrology (DMH), Department of Hydropower

276

Implementation (DHPI), Department of Irrigation and Water Utilization Management(IWUMD) and Irrigation Department (ID). The surveyed cross-sections data for the river
analysis system were supported by Satreps Project. There are two rainfalls and water levelstations from DMH, one station at Bago Bridge and one state at Zaung Tu village andonly daily rainfall data and water levels are available. But the water level from Zaung Tu
village is inappropriate to apply in this research. Furthermore, Daily rainfall data fromdam sites are also available. Although the specific data for example hourly data or nearreal-time data should be used for flood modeling, detailed information cannot apply by
the lack of certain data availability in the study area. The average rainfall and water levelof the Bago river basin for calibrated and validated flood events are listed in figure 3. The
red line shown in the figure is the danger water level. The danger water level of Bago
River is 880 cm at Bago Bridge but some area is inundated before the river water level
close to the danger level. In these flood events, the water level of 2014, 2015 and 2018
events was above the danger water level. The cumulative rainfall from 1967 to 2018 arein figure 4, the trend of the chart goes up slightly. But the cumulative rainfall will be lessand less due to climate change, although the maximum rainfall occurred.

Figure 2. Average precipitation and water level for simulated flood events of Bago
River Basin
Cumulative rainfall in 1969 was above 4000 mm and it was the most cumulative rainfall
within 51 years. The cumulative rainfalls for simulation events are listed in figure 5 (a)and figure 5 (b) shows the Zaung Tu dam released flows for flood simulation events.
Released flow from the dam is a key role in the Bago river basin’s flood simulation.
Data required for hydrologic modeling (HEC-HMS) are:277

(a) High-Resolution Digital Elevation Model (DEM):(b) Land use and Soil cover(c) Climate data (Precipitation)(d) Flow data (Dam released flows, Water Level)

And the following data are required for the hydraulic modeling system.

(a) Terrain Data(b) Geometry Data(c) Flow Data

Figure 4. Bago Cumulative rainfall from 1967 to 2018

Figure 5. (a) Cumulative Rainfall for flood simulation events (b) Dame released flows
for flood simulation events
3. Methodology
Hydrologic Modeling System, HEC-HMS and River Analysis System, HEC-RAS are twoof the most commonly used models in hydrologic and hydraulic modeling systems. HECHMS and HEC-RAS have been developed by the U.S Army Corps of Engineers to delivervital public and military engineering services, to energize the economy and reduce risks
from disasters. HEC-HMS is a generalized modeling system designed to simulate theprecipitation-runoff processes of watershed systems with a wide range of applicability.
This includes large river basin water supply and flood hydrology, small urban or natural278

watershed runoff, forecasting stream flow, depth-area reduction, assessing model
uncertainty, erosion and sediment transport, and water quality. Hydrologic modeling fora watershed involves infiltration, overland flow, computing rainfall excess, flood routing
from the upstream of reach to the outlet and subsurface flow simulation.
Runoff volume and peak discharge calculation is the first step in hydrologic modeling.
The rainfall losses involve tree canopy, land use and infiltration to the soil layer. Amongthem, infiltration through the soil is the key component in the calculation of runoff.
Infiltration refers to the amount of rainfall which passes through the soil layer. The
amount of infiltration rainfall is equivalent to the infiltration capacity of the soil layer. If
the amount of rainfall is greater than the infiltration capacity, the actual rate of infiltration
is equal to the rainfall amount. In other words, the actual infiltration rate is equal to theinfiltration capacity, if the infiltration capacity is less than the rainfall amount.
𝑓𝑓 = 𝑖𝑖 𝑖𝑖𝑖𝑖 𝑓𝑓𝑝𝑝 > 𝑖𝑖
(1)

and

𝑓𝑓 = 𝑓𝑓𝑝𝑝 𝑖𝑖𝑖𝑖 𝑓𝑓𝑝𝑝 < 𝑖𝑖(2)𝑖𝑖𝑒𝑒 = 𝑖𝑖 − 𝑓𝑓

(3)

= Infiltration capacityf= Actual infiltration rate
I
= Rate of rainfall
The excess rainfall is calculated from the following equation.
where fp

where ie is the excess rainfall.
The various methods are used to evaluate the infiltration capacity. In this study, the initialand constant rate loss method is used for the excess rainfall based on the hydrologic soil
group and land covers. The initial and constant method involves the parameters ofconstant rate, initial loss, and percent of impervious which show the physicalcharacteristic of the soil layer and land use. The estimated infiltration loss rates forhydrologic soil groups are published by Skaggs and Khaleel in 1982. Table 1 shows theestimated infiltration loss rates for hydrologic soil groups.
Table 1. Hydrologic soil group and infiltration rates (Skaggs and Khaleel, 1982)
Soil Group

Description

A
B
C

Deep sand, deep loss, aggregated silts
Shallow loess, sandy loam
Clay loams, shallow sandy loam, soils low in

Infiltration loss rate
(cm/hr)0.762 – 1.143
0.381 – 0.762
0.127 – 0.381

279

D

organic content, and soils usually high inclay
Soils that swell significantly when wet,heavy plastic clays, and certain saline soils

0.00 – 0.127

For the transform method, the time of concentration, t c was be calculated from thefollowing equation developed by Kirpich (1940).
𝑡𝑡𝑐𝑐 = 0.0195 . 𝐿𝐿𝑐𝑐 0.77 . 𝑆𝑆𝑐𝑐 −0.385(4)where Lc is the watershed length in meter, the longest flow path in HEC-HMS and Sc is
the slope (m/m) in the main channel.
The total runoff hydrograph involves direct runoff and baseflow. The separation of the
distribution of baseflow from the total runoff hydrograph is also important in thehydrologic modeling system. It also impacts on the shape of the flow hydrographs.
The hydraulic modeling system requires river cross-sections and Manning’s roughness
coefficients as its geometric parameters. The basic computational procedure is based on
the solution of the one-dimensional energy equation with energy losses evaluated by
friction through Manning's equation and contraction and/or expansion. The onedimensional energy equation is also called the standard step method.
𝑉𝑉 2

𝑉𝑉 2

1
2
+ 𝑆𝑆0 ∆𝑥𝑥 = 𝑦𝑦2 + 2𝑔𝑔+ 𝑆𝑆𝑓𝑓 ∆𝑥𝑥
𝑦𝑦1 + 2𝑔𝑔

(5)

Where Sf is the energy grade line slope, S0 is the channel bed slope.
3.2. HEC-HMS Model Development
The hydrologic model was developed using HEC-HMS Version 4.3 and has four
components to simulate the basic hydrologic processes of runoff generation fromprecipitation, its transformation, and combination with baseflow, and it’s routing towards
the outlet. These four components are (i) infiltration loss, (ii) direct runoff, (iii) baseflow,and (iv) channel routing.
The infiltration loss component based on the Initial and Constant method computes forthe volume of rainfall that falls on the watershed and addresses questions on how muchof rainfall infiltrates on the surface and when does it run off.
The direct runoff component using the Snyder Unit Hydrograph method describes two
critical processes in the transformation of excess precipitation to runoff which is 1)

280

translation or movement of the excess precipitation from its origin throughout thedrainage to the watershed outlet; and 2) attenuation or reduction of the magnitude of thedischarge as the excess is stored throughout the watershed. The baseflow model based on
the Recession method is used to explain the drainage from the natural storage of thewatershed. The channel routing model, using the Lag method, simulate the flow in thechannels towards the main outlet.
The development of the HEC-HMS model primarily involved the physical representationof watershed and streams within the Bago River Basin into hydrologic elements namelywatersheds reaches, and junctions interconnected in a dendritic network to simulate
rainfall-runoff processes. With a lumped-parameter approach, direct runoff is computed
using the Initial and Constant method for each watershed and routed and translated toward
each watershed’s outlet using the Snyder Unit Hydrograph model. The computed direct
runoff and baseflow hydrographs for each watershed are routed through channels (or“reaches”) towards the main outlet of the Basin using the Lag method. Modeling in There
are three specific components as a basin model, a meteorological model, and a set ofcontrol specifications. In the basin model, the termed "sub-basin", the physicalrepresentation of the basin model for each watershed and the river elements to simulatehydrologic processes are included. A meteorological model consists of a time series dataof rainfall used for the simulation. The control specification determines the simulation
time step and period or duration for model simulation and calibration. HEC-HMS’s
preprocessor, HEC-GeoHMS was used to prepare the basin model.
HEC-GeoHMS which is the extension of ArcView GIS software was applied to visualize
spatial information, the characteristics of the watershed, watershed delineation, spatial
analysis performance, and construct inputs to hydrologic models.
3.3. HEC-RAS Model Development
The HEC-RAS model of Bago River was developed by first constructing a geometricrepresentation of the rivers and their flood plains. This includes cross-sections, riverbanks,and centerline, and the flood plain boundaries (i.e. the domain). A high-resolution 10-m
DEM integrated with river observed cross-section data was used as the primary source ofthe cross-section data. Riverbanks and centerlines were digitized from the high-resolution
Worldview-2 image. All the model pre-processing was done in ArcView GIS 10.4.1 using
HEC-GeoRAS extension. HEC GeoRAS is the pre-processor of HEC RAS, and it
prepares the model’s geometric data. It is also used to assign basic model parameters.
This geometric data is then imported in HEC RAS for further model setup. Some of thecross-sections from the pre-processing stage were extended beyond the model domain

281

just to make sure all of the domains are covered. The flood depth and hazard maps for themodel result after are got from the post-processing stage. Flow resistance coefficients,
also called Manning’s roughness coefficients n, were assigned to the cross-section
segments (or the portion between cross-section points) using land-cover information fromthe SERVIR Mekong land-cover Portal. A look-up table based on the HEC RAS
Hydraulic Reference Manual was used to transform the land-cover classes to Manning’sn land-cover classes. As a hydraulic model, the HEC RAS model cannot run on its own
to provide the required information (flood depths). In a simulation run, it requires
information on how much water is entering at specific locations as well as water level
conditions at the downstream-most portion (e.g., outlet) of the model domain. Thisrequired information is called boundary conditions that need to be set to reflect (i) thevolume of water that the river receives (or inflow) from upstream watersheds and lateral
inflows and (ii) the elevation of the water surface at the outlet.
4. RESULTS AND DISCUSSION
4.1. Calibration
HEC-HMS calibration was performed for six different flood events of 2014 to 2018 in
the Bago River basin using daily flows discharge. Figures 3 (a), (b), (c), (d), (e) and (f)are the graphs that compare observed flow to simulated flow for the calibrated years, 2014
to 2016. The red dotted lines denote observed outflow measured at Bago gauge station,
at Bago DMH. The blue dotted lines denote the total simulated outflow at the Discharge
gauge. The calibration at event 2016B resulted in simulated outflow volume and peakflow almost the same as observed volume. At the outlet of the watershed, percent error involume, PEV and percent error in peak discharge, PEPD for calibrated years is shown in
Table 2.

282

Figure 3. Observed and Simulated flow for Calibrated year (a) Event-1, 29-Jul-2014 to
13-Aug-2014 (b) Event-2, 15-Jul-2015 to 12-Aug-2015 (c) Event-3, 12-Aug-2015 to 25Aug-2015 (d) Event-4, 5-Jun-2016 to 23-Jun-2016 (e) Event-5, 1-Jul-2016 to 29-Jul-2016(f) Event-6, 30-Jul-2016 to 21-Aug-2016
Table 2. Percent Error in Volume (PEV) and Percent Error in Peak Discharge (PEPD) of
the model for calibrated flood events
Observed

Simulated

Observed

Simulated

VolumeVolumeDischarge

Discharge

(mm)

(mm)

(mm)

(m3/s)(m3/s)(m3/s)

Event - 1

430.82392.53

8.9

956.7

853.4

10.8

Event - 2

597.59639.62

7.0

872.2

963.3

10.4

Event - 3

250.13237.96

4.9

737.1

760.7

3.2

Event - 4

207.64235.34

13.3

749.3

780.5

4.2

Event - 5

461.87465.53

0.8

739.5

697.5

5.7

Event - 6

303.75279.32

8.0

710.5

680.4

4.2

EventsPEV

PEPD

Since the model was mainly calibrated considering the outflow volume and peak283

discharge, the calibrated flow pattern poorly represented the observed flow for BagoDMH station. Also, the flow pattern could not be calibrated accurately as the outflow of
the watershed. Whereas, the flow trend of the event is similar to the observed flow at theoutlet station. Hence, the model is unable to simulate the short-term events accurately atthis outlet. Therefore the simulation for the short-term events must be performed. The
initial peaks seen in the calibrated flow at all the junctions are due to model warmup
period and thus can be ignored. Failure to simulate the peak flow and time of peak could
also be due to ambiguity in the precipitation data. Apart from this, some important
meteorological parameters such as wind speed and air pressure have not been included in
the model whereas wind plays an important role in the hydrological cycle. The
computational time step for simulation was set for 1day therefore; the computed outflow
data were also for the one-day interval. In this computation, the data of the precipitationand discharge are daily averaged data. This mismatch between the time interval of input
data and the output also created some level of error. Table 3 helps to evaluate the model
performance for calibration.
Table 3. HEC HMS Model Performance Evaluation result for Calibration
NashEvents

Sutcliffe

RMSE

Bias (%)

R-Squared`

Event-1

0.772

0.5

- 4.000.83

Event-2

0.837

0.4

9.37

0.9

Event-3

0.961

0.2

0.55

0.96

Event-4

0.829

0.4

15.42

0.88

Event-5

0.841

0.4

2.64

0.87

Event-6

0.935

0.3

5.41

0.95

The Nash-Sutcliffe Efficiency (NSE) for calibrated flood events found between 0.772 to
0.961 respectively. That is indicated a close relationship between the observed andsimulated flow and the model performance is good. Nash Sutcliffe efficiency (NSE)areobtained as 0.772, 0.837, 0.961, 0.829, 0.841 and 0.935 respectively for 2014, 2015 and2016 calibrated flood event. The validation process was done by these final parametervalues for another two storm events (2017 and 2018). The validation results of the 2017and 2018 flood events are as shown below in Figures 5 (a) and Figure 5 (b) respectively.
That is indicated a close and good correlation between the observed and simulated flow.

284

Figure 4. Coefficient of determination value for Calibrated years, (a)Event-1, (b) Event2, (c) Event-3, (d) Event-4, (e) Event-5, (f) Event-6
4.2. Validation
To verify the output of this model, validation was also performed for validation eventsfrom the year 2017 to 2018. This was performed to check if the models were able topredict the runoff at the discharge stations for the period other than calibrated one or not.
The resulting graphs for the validation period are shown in the figures below, Figures 5(a) and Figure 5 (b). Nash Sutcliffe efficiency (NSE) is obtained as 0.527 for the 2017
Validation event and 0.559 for Validation event 2018 respectively and shown in table 4
and table 5.
From the above results, some similarities and differences between these basin models canbe extracted and discussed herewith. There is no certainty for assigning values ofparameters in HMS. Any value can be assigned to the parameter to get a well calibrated
model. Therefore, even a set of values that do not have any physical relevance can result285

in a well-calibrated model. This could be possible in the HMS model. Therefore, seasonalparameterization may improve model performance. Simulation of rainfall-runoff
modeling for dendritic basins was performed based on historical time-series data and wascalibrated and validated with the observed flow in this research. With the ongoing global
warming and climate change effects, precipitation and temperature are in increasing trend
which implies higher runoff in the future.

Figure 5. Observed and Simulated flow for Validated year (a) Event-1, 2017 flood event(b) Event-2, 2018 flood event

Figure 6. Coefficient of determination value for Validated years,(a) Event-1, (b) Event-2

286

Table 4. Percent Error in Volume (PEV) and Percent Error in Peak Discharge (PEPD) of
the model for validated flood events
EventsObserved

Simulated

VolumeVolume(mm)(mm)

Event - 1

740.05

Event - 2

752.62

PEV

Observed

Simulated

PEPD

Discharge

Discharge(mm)(m3/s)(m3/s)(m3/s)

815.60

75.55

784.2

891.0

106.8

777.4524.83

1048.11387.7

339.6

Table 5. HEC HMS Model Performance Evaluation result for validated flood events
EventsNash-Sutcliffe

RMSE

Bias (%)

R-Squared`

Event-1

0.527

0.7

12.42

0.7

Event-2

0.559

0.7

5.5

0.83

287

4.2. Hydraulic Modelling with HEC-RAS
The results in the HEC-RAS model are shown below. Calibration and Validation Resultsof HEC-RAS Model calibration was performed by the unsteady flow data option using
the output flood hydrograph for two different flood events (2010, 2014, 2015, 2016, 2017and 2018) that were simulated from HEC-HMS model. The friction slope is assumed andcalibrated as 0.0001. The validation results with these final calibrated parameters for the2018 flood hydrograph simulated form the HEC-HMS model are also shown below in
Figure 4.9 respectively. In this flood inundation maps, the 2010 flood extent is the largest
inundation area.

Figure 4.9. Flood Externts for different inundation events (a) Profile 2017 Flood Event(b) Profile 2016 Flood Event(c) Profile 2015 Flood Event (d) Profile 2018 Flood Event(e) Profile 2014 Flood Event (f) Profile 2010 Flood Event288

5. Conclusions and Recommendation
The calibration for the hydrologic model was performed by the trial and error method in
the HEC-HMS model. The values of calibrated parameters are sensitive to thecharacteristic of the basin as well as the resolution of the digital elevation model. It
impacts the basin parameters such as slope which is important for the flood routing. The
parameter changes incorrectly vary the scheme of water balance equation. For the study
area which consists of a lot of topological changes, the resolution of the digital elevation
model (DEM) is critical. For the hydraulic model, the cross-sections for the HEC-RAS
model are extracted from DEM. The extracted cross-sections change the water surface
elevation of the river analysis system. Therefore, the resolution of the DEM is importantfor both models. The result shows that parameters corresponding to the hillslope provide
a large variation for different flood events.
As the author mention above, changes in the formation of cross-sections for the model
affect the water surface elevation of a river. Moreover, the sedimentation, scour,urbanization, levee construction impact on the formation of cross-sections. For this reason,
it is strongly recommended that the surveyed river cross-sections should be applied in thehydraulic model. Each surveyed river cross-section should have the minimum amount ofcross-section filter to an extent over the flood-prone area.
Although the high-resolution digital elevation model was applied in this research, theresolution of the model doesn’t extent over the whole river basin. The developer
consolidates the 30 m and 10 m DEM for this model, so the resolution at the upstream of
Zaung Tu Weir is not matched with the downstream resolution of the model. As possible,
the high-resolution digital elevation model which covers the whole river basin should be
used in the research.
There are only two rainfall and water level gauge stations form DMH in the river basin
and the data from the stations are available daily. One station from Zaung Tu Village
cannot be applied in this research because of data uncertainty. Therefore, new automaticrain gauges and water level stations should be installed at the places where the flowchange, for example, the downstream of Zaung Tu weir and Zaung Tu Dam. One stationfrom Zaung Tu Village cannot be applied in this research because of data uncertainty. To
mitigate the flood risk in the Bago river basin, departments related to Bago river should
be integrated.
But these current methods for managing facilities may not be sufficient to support planned
design functions, so further study of operation methods is necessary. A coordination
framework should be established between DMH, ID, and DHPI. This framework would289

utilize DMH hydrological and meteorological observation data for ID/HGPE/DHPI
operation of hydropower and reservoir facilities.

290

FLOOD RISK ASSESSMENT BASED ON QUANTIFICATION OF FLOOD DAMAGE
B.B. SHRESTHA1 and A. KAWASAKI2
1

Project Researcher, Department of Civil Engineering, The University of Tokyo, Tokyo, Japan,
2
Professor, Department of Civil Engineering, The University of Tokyo, Tokyo, Japan,
Correspond to Dr. B.B. SHRESTHA (shresthab@hydra.t.u-tokyo.ac.jp)

Keywords: Flood Risk Modeling, Damage Quantification, Social Impact, Vulnerability, Myanmar

2. ASSESSMENT OF FLOOD HAZARD AND RISK
Figure 1 shows overview of flood damage/risk
assessment in this study. Flood hazard and risk wereassessed in the Bago River basin of Myanmar. Floodcharacteristics such as flood depth and duration werecomputed using hydrological model named RainfallRunoff-Inundation (RRI) model developed by Sayama etal. [1]. The horizontal resolution of RRI model was 15 arcs grid cell (approximately 450m). The parameters of the
RRI model were calibrated with 2014 flood by comparing
calculated discharge with observed discharge at Bago
Station as shown in Figure 2. The calibrated parameters
were validated with 2015 and 2018 flood events.
HazardRainfallZ

Subsurface + Surface
Vertical Infiltration

1D Diffusion
in River2D Diffusion
on Land

Rainfall-Runoff-Inundation
Model Simulation

Exposure

Vulnerability

House Distribution/
Population

Field Investigation

Land CoverQuestionnaire Survey

Development ofdamage functions

Flood Damage/Risk
Assessment

Figure 1. Overview of flood damage/risk assessment
After hazard analysis, flood damage to residential
houses and agriculture sector (flood damage to rice-crops)

was assessed and quantified based on flood damage
curves. The population distribution data downloaded fromthe WorldPop were used to estimate distribution ofresidential houses, and the cropland areas in the study
basin were extracted using global land cover map
developed by International Steering Committee for Global
Mapping (Figure 3).
Basin Avg. Rainfall

Observed Discharge

Simulated Discharge

0
50

1600
1200

NSCE= 0.84
R2=0.89

800

400

100
150

200

Rainfall (mm/day)

2000

Discharge (m3/sec)

1. INTRODUCTION
Floods are the most frequently occurring water-related
disasters in the river basins of many countries, and theimpact of floods is becoming greater due to theirincreasing frequency and scale of flood events, and theconcentration of population and economic activities in theriver basins. Flood disasters can cause serious damage
such as loss of lives and destruction of infrastructures andproperties. Therefore, flood disaster risk mitigation plans
should be properly prepared and implemented for future
floods. However, such mitigation plans require analysis offlood hazards and quantification of risk for mitigating andmanaging flood risk for the future. In this context, thisstudy focuses on assessment of flood risk by quantifying
flood damage in the Bago River basin of Myanmar, which
is one of the most flood-prone river basins in Myanmar.
Assessment of flood hazard and risk in the Bago Riverbasin is very important since this basin plays an importantrole in economical contribution in the country’s economy
through agriculture production. Flood risk in the basin was
thus assessed by quantifying flood damage to housebuilding/assets and agriculture using hydrological anddamage estimation models.

0
250
2014/07/25 2014/07/30 2014/08/04 2014/08/09 2014/08/14 2014/08/19 2014/08/24 2014/08/29

Date

Figure 2. Comparison of calculated discharge withobserved discharge at Bago Station for 2014 flood
Flood Inundation

2014
flood

Population Distribution

Land Cover Map

BEF
BDF
NEF
NDF
Mixed Forest
Tree Open
Shrub
Herbaceous
SV
Cropland
Paddy Field
C/OVM
Bare area
Urban
Water Bodies

Figure 3. Flood inundation area during August 2014 flood,
population distribution and land cover map of study area
Flood frequency analysis was also conducted to estimate
the rainfall intensity for different return periods. Floodhazard and risk were assessed quantitatively for pastlargest flood and for different return period cases.
3. CONCLUSIONS
Flood hazard and risk were assessed quantitatively in
the Bago River basin of Myanmar. Identifying areas ofrisk based on flood damage quantification provides
essential information for designing future development
activities. The results of risk assessment can also be usefulto establish preventive measures, adaptation measures andpolicies required for flood damage reduction.
REFERENCES[1] T. Sayama, G. Ozawa, T. Kawakami, S. Nabesaka, K.
Fukami, Hydrol. Sci. J. 57 (2012) 298-312.

291

Estimation of Flood Discharge using with
WEB-DHM model in Bago River Basin
Sann Win Maung1, Zin Mar Lar Tin San2, Win Win Zin3
and Akiuki KAWASAKI4
1
Ph.D Candidate, Department of Civil Engineering, Yangon Technological University,
Myanmaruswinmg@gmail.com
2
Professor, Department of Civil Engineering, Yangon Technological University, Myanmar
zinmarlar@gmail.com
3
Professor, Department of Civil Engineering, Yangon Technological University, Myanmar
winwinzin@gmail.com
4
Professor, Department of Civil Engineering, The University of Tokyo, Japan
kawasaki@hydra.t.u-tokyo.ac.jp
ABSTRACT
Flooding has always been one of the major hazards in Myanmar, accounting for 11% of alldisasters. In Myanmar, the Bago River Basin is a flood prone area. During the last decade,many severe floods occurred in the Bago River Basin, at the monsoon season about the periodof July and August. Most of the floods are caused by the storm rainfall. The 2011 and 2018floods are historical record of Bago. In this paper, the Water and Energy Budget-based
Distributed Hydrological Model (WEB-DHM) was used for hydrological modeling as
determined for the discharge of flood. In this study, Hydro-SHEDS DEM is used for elevation
data of the Bago river basin. The Japanese 55-year Reanalysis JRA-55 data from the Japan
Meteorological Agency (JMA)is used for the meteorological data preparation of thishydrological model. This paper aim to compare the flood discharge from the hydrologicalmodeling and the calculated observe data of the past three year 2014, 2015 and 2016.
Keywords: Bago river basin, flood, rainfall, WEB-DHM
1. INTRODUCTION
A flood is a high flow or overflow of water from a river or similar source of water occurring
over a period of time. Heavy rain spell can result in an extra volume of water in the waterways,
leading to a rise in the water level of streams and rivers. A flood happens when the carrying
capacity of the waterways fails to hold the total volume of increased water at any given time
(UN-HABITAT, Myanmar, 2015).
Flooding has always been one of the major hazards in Myanmar, accounting for 11% of alldisasters. In Myanmar, the Bago River Basin is a flood prone area. During the last decade, many
severe floods occurred in the Bago River Basin, at the monsoon season about the period of Julyand August. Most of the floods are caused by the storm rainfall.
Flood protection measures can be structural (“hard”) or non-structural (“soft”). The former referto such defenses as dikes, dams and flood control reservoirs, diversions, floodways, etc.
Structural defenses have a very old tradition, as dams and dikes have been built since more thanfour thousand years.
Non-structural flood protection measures are: source control, zoning, flood proofing, insurance,
flood forecast-warning system, awareness raising and improving information, etc.

292

Estimation of Flood Discharge using with WEB-DHM model in Bago River BasinDecember 2019, Yangon, Myanmar

There is no flood protection measure guaranteeing complete safety. In many vulnerable areas,sufficient flood protection cannot be reached with the help of structural means only. Hence,
further flood risk reduction via non-structural measures is often indispensable. An optimal, sitespecific mix of structural and non-structural measures are being sought (Lucas Menzel,
Zbigniew W. Kundzewicz. 2003).
Hydrologic models use relatively simple mathematical equations to conceptualize andaggregate the complex, spatially distributed, and highly interrelated water, energy, andvegetation processes in a watershed.
In this study, the WEB-DHM hydrological model is used for estimating and forecasting theflood discharge of the Bago river basin.
2. STUDY AREAIn Myanmar, the Bago River Basin is a flood prone area. During the last decade, many severe
floods occurred in the Bago River Basin, at the monsoon season about the period of July andAugust. Most of the floods are caused by the storm rainfall. The 2011 and 2018 floods are
historical record of Bago.
The Bago River is confluent with the Yangon River and reaches the coastal water body. It is
located at about Latitude. 16°46'00"- 18°27'30" N and Longitude. 95°53'00"- 96°45'00" E. Its
head is found 190 km from Yangon, lying on Pegu Yoma (mountain) at an elevation of 630 m.
The length of the river-channel reaches, due to including complex meandering sections, over
340 km. However, its tributaries are not broadly developed, so the basin area is relatively small
at about 5,030 km2. The Bago River Basin is shown in Figure 1.
The Bago River is one of the most important and useful river basins in lower Myanmar forhydropower generation, irrigation use, fisheries, and navigation use (Shelly Win. 2014).
The two meteorological stations are located in the basin, Bago and Zaung Tu Station; the twopoints are the interesting points in this study. The average annual total rainfall at the Bago
station is around 3,000 mm. Floods occur every year (sometimes even more than once) in the
Bago River basin.
The Zaung Tu dam was constructed in 1996. The other three dams (Salu, Kodukwe, andShwelaung) were constructed in 2012.

Figure 1: Location Map of Study Area

New Technologies for Urban Safety of Mega Cities in Asia

293

3. METHODOLOGY
3.1. Overview of WEB-DHM model
The Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM), wasdeveloped by coupling a simple biosphere scheme (SiB2) with a geomorphology-basedhydrological mode. The model can estimate the water, energy and CO2 fluxes at a basin scale.
Contrary to traditional hydrological models, this model calculates evapo-transpiration based on
both water as well as energy balances for each model grid, creating a much more solid physicalfoundation (Bhagabati, S.S, 2018).
Figure 2 show the overall structure of the WEBDHM model. The Figure. 2 (a) shows the subbasin; (b) shows the sub-division from sub-basin to flow intervals; (c) shows the discretizationfrom a model grid to a number of geometrically symmetrical hillslopes; and (d) shows thedetailed process descriptions of the water moisture transfer from atmosphere to river, including
downward solar radiation, downward long wave

Figure 2: Overall Structure of WEB-DHM model (Lei WANG, Toshio KOIKE. 2009)
3.2. Model application
In this study, the first part of WEB-DHM model application is ArcGIS based tool analysis. The
major geospatial input data includes Digital Elevation Model(DEM), soil data, land use andstream network layers.DEM is the geospatial raster data containing the continuous elevation
values a topographic surface by the array of cells or pixels. It is used in ArcGIS to create thewatersheds and river networks and streams, sub-basins, and parameters for Hydrological
Response Units (HRUs) analysis. In this study, Hydro-SHEDS DEM is processed in a GIS
environment using
In this study, land use and land cover data were acquired from the SERVIR MEKONG LAND
COVER image (http://servir-rlcms.appspot.com/, n.d.).This data is used for HRU definition,and then allocate
The soil data for the study area was extracted from FAO (Food and Agricultural Organizationof the United Nations) Digital Soil Map of the World (DSMW)(http://www.fao.org/soilsportal/soil-survey/soil-maps-and-databases/en/, n.d.).

294

Estimation of Flood Discharge using with WEB-DHM model in Bago River BasinDecember 2019, Yangon, Myanmar

3.2.1. Terrain preprocessing
Terrain Preprocessing includes the projection of DEM (Digital Elevation Model) (Figure 3(a)),
DEM preprocessing as fill, flow accumulation and flow direction. Similarly, it includes thedelineation of the watershed and the hill slope calculation.
DEM preprocessing involves various internal processes required for the model. It involves fill,flow accumulation, flow direction and stream generation.
Watershed delineation is a process of extracting the boundary of a watershed. This can bedelineated from a DEM using the flow direction (Figure 3(b)), flow accumulation (Figure 3(c))
and the outlet of the watershed.
Hill slope calculation includes all the processing and calculation needed for the WEB DHM
model. Above three preprocessing steps are required to create the input for the Hill slope
calculation (The University of Tokyo. 2016).

(a)
(b)
(c)
Figure 3: Elevation model, flow direction and flow accumulation of Bago River Basin
3.2.2. Basin division processing
WEB-DHM uses the Pfafstetter algorithm developed by Otto Pfafstetter in 1989. Based on the
topology of the watershed, this algorithm can assign watershed IDs in a systematic manner. It
is a hierarchal system where watersheds are delineated from junctions on a river network. The
continental watersheds are represented as level 1. Higher level (Levels 2, 3, 4 etc.) represents
even finer tessellations of the land surface into smaller watersheds, which are sub watershedsof lower level watersheds. The Pfafstetter code for each basin is unique and is based on its
location on the overall drainage system and on the total drainage area upstream of thewatershed’s outlet. This file contains the information about the minimum and maximum width,height and roughness coefficient of all the sub basins. Sub-catchment number should bearranged in the descending order. These parameters can also be used for the model calibration
purpose. In this paper, 9 sub basins of Bago river basin were divided by using Pfafstetter
algorithm’s first level codification as shown in Figure 4 (a).
3.2.3. Soil data processing
The Soil data is processed from the FAO global soil map. The soil properties from the soil map
data are spatially distributed at approximately 9 km resolution grid size. The input data for
WEB DHM models is static. Soil data preparation in this study is shown in Figure 4 (b).
3.2.4. Land use data processing
The USGS Land Cover map which has global land cover characteristic database was developedon a continent basis. All continents in the global database share the same map projection(Lambert Azimuthal Equal area) and have a 1-km nominal spatial resolution and are based on

New Technologies for Urban Safety of Mega Cities in Asia295

1-km AVHRR data spanning April 1992 through March 1993. Land use data preparation in thisstudy is shown in Figure 4 (c).

(a)
(b)
(c)
Figure 4: Basin Division, Soil and Land use Map of Bago River Basin
3.2.5. LAI and FPAR processing
The Leaf Area index (LAI) defines an important structural property of a plant canopy as theone-sided leaf area per unit ground area. LAI is the ratio of total upper leaf surface of vegetation
divided by the surface area of the land on which the vegetation grows. LAI is a dimensionlessvalue typically ranging from 0 for bare ground to 6 for dense forest. The fraction of incident
radiation absorbed by greed canopy (FPAR) measures the proportion of available radiation in
the photo synthetically active wave lengths that a canopy absorbs. LAI and FPAR andbiophysical variables which describe the canopy structure and are related to functional processrates of energy and mass exchange. These parameters can be derived from satellite data MODIS.
3.2.6. Rainfall data processing
Rainfall is one of the main driving forcing for any hydrological model. This includes all formof water deposited on the earth’s surface and derived from atmospheric water vapor. Basicallyrainfall source can be of two types one is observed gauge data and another is satellite derived
or re-analysis data. There are several global datasets for precipitation that is freely available
online in the form of gridded raster dataset or asci files. In this study, observed guage data ofthe two target stations are used.
3.3 Meteorological Data Preparation
Besides Rainfall data, the Japanese 55-year Reanalysis JRA-55 meteorological data from theJapan Meteorological Agency (JMA) are used for WEB-DHM model. JRA-55 data are included
the time series datasets of air temperature, humidity, wind (u, v), pressure, long wave radiationand short wave radiation.
3.4 Efficiency value of Model Simulation
The efficiency criteria used in this study are presented and evaluated with (i) Coefficient ofdetermination (R2), (ii) Nash-Sutcliffe efficiency (ENS) and (iii) Root Mean Square Error(RMSE) (P. Krause, D. P. Boyle, F. B’ase, 2005)
3.4.1 Coefficient of determination (R2)296

Estimation of Flood Discharge using with WEB-DHM model in Bago River BasinDecember 2019, Yangon, Myanmar

The coefficient of determination R2 is defined as the squared value of the coefficient ofcorrelation according to Bravais-Pearson. It is calculated as:

Where,n[ ∑ (qsi-qs)(qoi-qo)]2
R 2= n i=1
2 n2∑ (qsi-qs) ∑ (qoi-qo)
i=1
i=1

(1)

= observed value at the i time interval= simulated value at the i time interval= average value of the observed discharge

qoi
qsi
qo

3.4.2 Nash-Sutcliffe efficiency (ENS)The efficiency E proposed by Nash and Sutcliffe (1970) is defined as one minus the sum of theabsolute squared differences between the predicted and observed values normalized by thevariance of the observed values during the period under investigation. It is calculated as:

Where,n2∑ (qoi-qsi)
i=1
E NS=1- n
2∑ (qoi-qo)
i=1

qoi
qsi
qo

(2)

= observed value at the i time interval= simulated value at the i time interval= average value of the observed discharge

3.4.3 Root Mean Square Error
The Root Mean Square Error (RMSE) value is the parameter error test and its value
approached to the zero means the least error parameter.

Where,n2∑ (Xoi-Ysi)
RMSE= i=1n(3)

= observed value at the i time interval= simulated value at the i time interval= number of sample data

Xoi
Ysi
n

4. RESULTS AND DISCUSSIONSIn this study, the simulation of the flood discharge in 2014, 2015 and 2016 were carried out
for the model calibration.
Bago Station (2014)

2000

0

Discharge (m3/sec)

1500
1000
500
0

y = 0.8905x + 30.189
R² = 0.6813
0

200

400

600

800

1000

1200

1400

100

1000
200

500
0

300

Rainfallobserve

Rainfall (cm)

Bago Station 2014

1500

Simulated

Figure 5: Comparison of Observed and Simulated Discharge at Bago Station in 2014

New Technologies for Urban Safety of Mega Cities in Asia

297

Discharge (m3/sec)

1200
1000
800
600
400
200
0

0

200

400

600

800

1000

Bago Station (2015)1600

y = 0.738x + 27.18
R² = 0.8257

0

1100

50

600

100

100

150

-400

200

1200

Rainfallobserve

Rainfall (cm)

Bago Station 2015

simulated

Figure 6: Comparison of Observed and Simulated Discharge at Bago Station in 2015

Discharge (m3/sec)

1200

600
400
200
0

y = 0.7384x + 22.384
R² = 0.7062
0

200

400

600

Bago Station (2016)

0

1000

50

800

100

600
400

150

200

200

0

800

1000

Rainfall (cm)

Bago Station 2016

800

Rainfallobservesimulated

Figure 7: Comparison of Observed and Simulated Discharge at Bago Station in 2016
Table 1. Statistical Parameters for Simulation Results of Bago Station
Events
R2
ENS
RMSE
2014
0.681
0.612
137.07
2015
0.825
0.815
93.33
2016
0.706
0.702
92.99
The comparisons of observed and simulated discharge at Bago station from 2014 to 2016 timeseries are shown in Figure 5 to 7. According to the Table 1, the statistical parameters for themodel simulation results of Bago station are acceptable level.

Discharge (m3/sec)

1800

800
600
400
y = 0.769x + 2.5778
R² = 0.7736

200
0

0

200

400

600

800

1000

ZaungTu Station (2014)

0

1300

50

800

100

300

150

-200

200

1200

Rainfallobserve

Rainfall (cm)Zaung Tu Station 2014

1000

Simulated

Figure 8: Comparison of Observed and Simulated Discharge at Zaung Tu Station in 2014
Discharge (m3/sec)

1200

500
400
300
200

0

0

100

200

300

400

500

600

700

0
50

700

100
200

150

-300

y = 0.6484x + 8.0969
R² = 0.7526

100

ZaungTu Station (2015)

800

Rainfall (cm)Zaung Tu Station 2015

600

200

Rainfallobserve

Simulated

Figure 9: Comparison of Observed and Simulated Discharge at Zaung Tu Station in 2015

298

Estimation of Flood Discharge using with WEB-DHM model in Bago River BasinDecember 2019, Yangon, Myanmar

400
200
0

y = 0.7827x + 0.893
R² = 0.8255
0

100

200

300

400

500

600

700

800

1200

ZaungTu Station (2016)

0
50

700

100
150

200

200
-300
Rainfallobserve

Rainfall (cm)

Discharge (m3/sec)

Zaung Tu Station 2016

600

Simulated

Figure 10: Comparison of Observed and Simulated Discharge at Zaung Tu Station in 2016
Table 2. Statistical Parameters for Simulation Results of Zaung Tu Station
Events
R2
ENS
RMSE
2014
0.773
0.756
62.51
2015
0.752
0.697
64.59
2016
0.825
0.793
46.26
The comparisons of observed and simulated discharge at Zaung Tu station from 2014 to 2016
time series are shown in Figure 8 to 10. According to the Table 2, the statistical parameters forthe model simulation results of Zaung Tu station are also acceptable level.
5. CONCLUSIONAt the Bago river basin, the topography of the upstream basin area is quite steep and thedownstream basin area is normal flat condition. Most of the flooded areas in Bago are theresidential area of the downstream basin area of Bago river basin. In this study, the simulated
discharge was compared with the daily observed discharge values of the two meteorologicalstations. All the results of WEB-DHM simulation showed reliable values and acceptable levelin statistical parameters for the selected three year. In this model simulation results, thestatistical parameters of Zaung Tu station are more reliable than Bago station.
REFERENCES
Bhagabati, S.S. 2018. “Development of a Near-Real Time Flood Inundation Analysis System
for a Deltaic Flat River Basin in a Data Scarce Region; Case of the Bago River basin,
Myanmar”. PhD Thesis. Department of Civil Engineering, School of Engineering, The
University of Tokyo.
Lei WANG, Toshio KOIKE. 2009. “Comparison of a Distributed Biosphere HydrologicalModel with GBHM”. Annual Journal of hydraulic Engineering- JSCE 53, 103-108
Lucas Menzel, Zbigniew W. Kundzewicz. 2003. “Non- Structural Flood Protection – A
Challenge”. International conference ‘Towards natural flood reduction strategies’, Warsaw, 613 September 2003
P. Krause, D. P. Boyle, F. B¨ase. 2005. “Comparison of Different Efficiency Criteria for
Hydrological Model Assessment”. Advances in Geosciences, 5, 89–97, 2005
Shelly Win. 2014. “Development of Flood Inundation Map for the Bago River”. M.E Thesis,
Department of Civil Engineering, Yangon Technological University, Myanmar.
The University of Tokyo. 2016. “GIS Tools for WEB-DHM using ArcGIS, User’s Maunual,
Version 2.0”. The University of Tokyo, Japan.
UN-HABITAT, Myanmar, 2015. “Manual of Flood; Causes, Effects and Preparedness”. UNHABITAT, Myanmar.

New Technologies for Urban Safety of Mega Cities in Asia

299

USMCA 2019, Yangon

Seismic Risk Assessment of Existing Timber Building:

A Case Study of Pyay Hostel in Yangon University
1

Wai Yan Soe, 2Kyaw Kyaw

1

Department of Civil Engineering, Yangon Technological University
Yangon, the Republic of the Union of Myanmar
swaiyan304@gmail.com
2
Department of Civil Engineering, Yangon Technological University
Yangon, the Republic of the Union of Myanmar
kyaw.u.kyaw@gmail.com
Abstract
Seismic Risk Assessment (SRA) involves determining the adverse consequences that people and society
might suffer as a result of future earthquakes. There are three components to seismic risk assessment: theseismic hazard, the vulnerability of structures in the region and the expected losses that result fromdamage. Myanmar lays one of the two main earthquake belts of the world with a complex seismo-tectonic
process. Most of the major cities in Myanmar including Yangon are located near the active Sagaing Fault
and seismicity of those areas is very high, in which most of historical buildings had been constructed oftimber frame. Among buildings in Myanmar, 82% of buildings are made of timber and bamboo, 2014
Myanmar Census. Due to the lack of maintenance, most of the timber buildings in Myanmar may beneeded to renovate. When renovating buildings it is necessary to assess the physical condition. Therefore,
seismic risk assessment of existing timber building: A Case Study of Pyay Hostel in Yangon University ispresented in this study. Pyay hostel (two-storey timber building) in Yangon University has been
established since 1924 and life time is about 100 years. It is necessary to investigate the existing seismic
performance condition of this building. According to the FEMA guideline, Rapid Visual Screening
technique (RVS) is an efficient method to quickly identify the seismic resistance of the building. To
implement this study, the seismicity of region, soil information and determination of pre-code building
were considered as pre-field survey data. According to the RVS data evaluation, detailed structural
evaluation is required for high seismicity performance and also not required for moderate seismic
performance.
Keywords: Seismic Risk Assessment (SRA), Pyay Hostel (two-storey timber building), Rapid Visual
Screening (RVS), Yangon
1. INTRODUCTION

Earthquake is one of the most serious natural hazards. Myanmar had experienced several highmagnitude earthquakes. Many of these events had a magnitude of 7 or greater and resulted in several
damages and significant causalities. Seismic Risk Assessment (SRA) involves determining the adverse
consequences that people and society might suffer as a result of future earthquakes. There are threecomponents to seismic risk assessment: the seismic hazard, the vulnerability of structures in the region
and the expected losses that result from damage. Myanmar lays one of the two main earthquake belts of
the world with a complex seismo-tectonic process. Most of the major cities in Myanmar including Yangon
are located near the active Sagaing Fault and seismicity of those areas is very high, in which most of300

USMCA 2019, Yangon

historical buildings had been constructed of timber frame. According to seismicity and records of previous
high magnitude earthquakes, some of the large earthquakes caused damages to some buildings and somecasualties in and around Yangon Region. Among buildings in Myanmar, 82% of buildings are made oftimber and bamboo, 2014 Myanmar Census. Due to the lack of maintenance, most of the timber buildings
in Myanmar may be needed to renovate. When renovating buildings it is necessary to assess the physicalcondition. . Although timber framed buildings are known to have a relatively low risk of damage inearthquakes, failure of timber framed buildings due to seismic excitation was largely limited to sites thatsustained ground deformations from liquefaction or landslide, or to vulnerable elements. Pyay hostel (twostorey timber building) in Yangon University has been established since 1924. The structural system of
the building is the valuable timber building technique in Myanmar. Now, its life time is about 100 years
old. According to the historical data, this building is one of the largest timber building and valuable historictimber building in Myanmar. Due to the visual survey, it has some circumstances: alteration of use anddetection of deterioration (corrosion defects, termite, seasoning defects and etc.). Some of the timber
beams and posts are suffering from those defects such as seasoning defects, corrosion, and otherenvironmental conditions. If it is not repaired by proper technique, the strength properties, workability
and serviceability will be reduced more. Thus, Seismic Risk Assessment of Existing Timber Building
especially for Pyay Hostel Building is presented.
2. OBJECTIVE

The main objective of this study is to advocate the importance of building vulnerability assessment
process and performance condition of existing timber building for the safety assessment and evaluation of
Pyay Hostel in Yangon University.
3. OVERVIEW OF THE CASE STUDY BUILDING

Pyay Hostel in Yangon University is now utilized for 111 female students from the Yangon
Education University. As the building was constructed on isolated reinforced concrete footings withtimber post and beam structural system, the building’s timber members lasted nearly a hundred years old.
Pyay hostel (two-storey timber building) in Yangon University has been established since 1924 and life
time is near 100 years. The dimensions of the building are 481ft. long, 52 ft. wide, 29 ft. height and theeach of the floor area is about 25000 sq.ft. This building is composed of timbers, such as Pyinkado(Ironwood) and Teak as shown in Figure (1).

Figure (1) Location Map and Photo of Pyay Hostel in Yangon University

301

USMCA 2019, Yangon

4. RAPID VISUAL SCREENING OF BUILDINGS FOR POTENTIAL SEISMIC HAZARD PROCEDURE(RVS PROCEDURE)

Vulnerability of the buildings is a critical determinant for earthquake risks. Experts say“Earthquakes don’t kill people, but unsafe buildings do”. Structural vulnerability is as measure of thedamage, a building is likely to experience when subjected to ground shaking of a specific intensity. In
general, dynamic response of a structure during ground shaking is a very complex behaviour. It depends
on a number of inter- related parameters that are often very difficult to predict precisely. These include
ground shaking that the building will experience, the extent to which the structure will be excited byresponse to the ground shaking: the strength of the materials in the structure; the quality of construction
and condition of individual structural elements; the interaction of the structural and non- structuralelements of the building; furnishings and contents present in the building at the time. Most of these factors
can be estimated, but never precisely known.
Seismic evaluation of existing buildings demands a three- tiered process Screening Phase (Tier 1),
Evaluation Phase (Tier 2) and Detailed Evaluation Phase (Tier 3) to assess either life safety or immediate
occupancy performance level of the building. Screening Phase (Tier 1) uses a Rapid Visual Screening(RVS) methodology, while tier (2) and tier (3) needs more detailed and sophisticated analysis. Since
Myanmar is adopting Myanmar National Building Code (MNBC) that is following International Building
Code for design as a first step, FEMA 154 is considered relevant for adaption as shown in Figure (2).

Figure (2) Three-tiered Process of Seismic Evaluation for Existing Buildings
Rapid Visual Screening (RVS) is a quick way of assessing the building vulnerability based on
visual inspection. Once identified as potentially hazardous, such buildings should be further evaluated bya design professional experienced in seismic design to determine if, in fact they are seismically hazardous.
The RVS procedure uses a methodology based on a sidewalk survey of a building and a data collection
form, which the person conducting the survey completes, based on visual observation of the building fromthe exterior, and if possible, the interior. If large number of buildings needed to be evaluated, carrying out
RVS of buildings minimizes the number of building that requires detailed assessment. Therefore, Rapid
Visual Screening will be useful for all buildings except lifeline structures where detailed vulnerability
assessment is always necessary. RVS procedure can be implemented relatively quickly and inexpensively
to develop a list of potentially hazardous buildings without the high cost of a detailed seismic analysis ofindividual buildings. FEMA has updated the Rapid Visual Screening of Buildings for Potential Seismic
Hazards: A Handbook (Third Edition) FEMA P-154/ January 2015.
5. SEISMICITY OF YANGON REGION

According to the Table 1, Ground motion for 0.2 sec Spectral Response acceleration for 0.2 Ss andmotion for 1 sec spectral response acceleration at 2% of Yangon are 0.77 and 0.31 accordingly.

302

USMCA 2019, Yangon

Table 1. Seismicity region determination from MECER spectral acceleration response
Seismicity

Spectral Acceleration Response, Ss

Spectral Acceleration Response, S1

Region(Short- period or 0.2 seconds)(Long- period or 1 seconds)

Low

Ss < 0.25g

S1 < 0.10g

Moderate

0.25g ≤ Ss < 0.50g

0.10g ≤ S1 < 0.20g

Moderate

0.50g ≤ Ss < 1.00g

0.20g ≤ S1 < 0.40g

High1.00 ≤ Ss < 1.50g

0.40g ≤ S1 < 0.60g

Very HighSs ≥ 1.50g

S1 ≥ 0.6g

High*Note: g = acceleration of gravity in horizontal direction
For Yangon Region according to the MNBC, SA (0.2s) falls under Moderately High Seismicity
Region category (0.50g < Ss < 1.00g) and SA (1s) falls under High Seismicity Region category (0.40g< S1 < 0.60g).
6. SOIL INVESTIGATION OF CASE STUDY BUILDING

Soil Type, also known as Site Class, has a major influence on amplitude and duration of shaking
and thus structural damage. The soil type should be identified during the planning stage and put into areadily usable map format for use during RVS. For the purpose of a rapid visual screening, the use of
geotechnical engineering reports may be impractical. If soil maps of the area are not available, soil typecan be estimated based on average shear wave velocity in the top 30 meters of soil, Vs 30. The investigation
result of shear wave velocity for Pyay hostel area is 300 m/sec.The shear wave velocity of Kamaryut area
is between 200 and 300 m/sec. Soil type D is mostly found in Yangon according to MNBC 2016.Therefore,soil type D is chosen for this building. Soil information map of Yangon area is shown in Figure (3).

Figure (3) Soil Information Map of Yangon area

303

USMCA 2019, Yangon
7. MATERIAL PROPERTIES OF CASE STUDY BUILDINGThe experimental study on physical and mechanical properties of existing timber members (Pyay
Hostel) are determined based on the ASTM Standard as shown in Figure 4.

Figure 4. Experimental Study of Existing Timber Members (Pyay Hostel)
According to the experimental results, it is found that the physical properties of teak and pyingado
used in this building are 10% and 14% of moisture content, and 0.56 and 0.8 for specific gravity. In themechanical properties of timber members, the modulus of elasticity values for teak and pyingado are
obtained 2.79x106 psi and 3.88x106 psi, and the modulus of rupture values of teak and pyingado are
1.94x104 psi and 2.81x104 psi respectively. On the other hand, it is found that the compressive strength ofteak and pyingado are 636.69 psi and 1210.75 psi respectively.
8. CONDITIONAL SURVEY OF CASE STUDY BUILDING

A timber condition survey provides an assessment of the physical condition of timber within abuilding. It can evaluate the load-bearing properties of the structural timbers such as beams, joists, posts,
rafters and purlins. It can also determine the condition of non-structural timber elements, such as
floorboards, staircases, wood paneling, windows, doors, architrave and skirting as shown in Figure (4).

Figure 4. Plan View of Case Study Building304

USMCA 2019, Yangon

A condition survey provides the project architect, engineer or contractor with confidence that theoriginal timber elements will meet the specified performance and appearance for the completed project.
The extent of a condition survey can vary depending on the client’s needs. It may involve a preliminary
inspection to assess the general condition of the timber and to identify whether there are significant defects.
This is then usually followed by a more detailed survey. The objective of the more detailed survey is toassess the condition and strength of the individual timber elements. This more detailed survey will identify
and evaluate any damage which may have been caused by decay, fungi, wood destroying insects and otherdefects. Timber bearing structures can have, under normal circumstances, a shorter working life than otherstructures. During an inspection of timber structures we observe material characteristics, structural modeland actual dimensions of elements and the possible actions of wood-decaying fungi or wood-destroying
insects as shown in Figure (5).

Figure (5) Natural & Seasoning Defect of Case Study Building
9. DETERMINATION OF CUT-OFF SCORES OF CASE STUDY BUILDING

Use of the RVS methodology on a community-wide basis enables the RVS Authority to divide
screened buildings into two categories: (1) those that are expected to have acceptable seismic performance;and (2) those that may be seismically hazardous and should be studied further. This requires that the RVS
Authority determines, preferably as part of the pre-planning process, an appropriate cut-off score.
RVS Cut-off score is calculated by equation (1).
S = -log 10 (Probability of Collapse) …………………………………………………… (1)For this building, 2% Maximum Considered Earthquake probability in 50 years described in MNBC;
S = - log 10 (0.02) = 1.699(taken as 1.7)
The score of 1.7 for MNBC is suggested as a cut-off for standard occupancy buildings, based onpresent seismic design criteria. Using this cut-off level, buildings having a score of 1.7 or less for MNBC
2016 should be investigated by a design professional experienced in seismic design. In some cases, ahigher cut-off score may be warranted for critical or essential facilities. A higher score indicates a smaller
probability of collapse. It does not, however, indicate a greater probability of other performance objectives
being met, such as continued operation.

305

USMCA 2019, Yangon
10. INSTRUCTION OF FILLING DATA COLLECTION FORM LEVEL (I) and (II)Level (I) and (II) Data Collection forms can be seen in Figure 6 and 7. Level (I) form can be
performed by a wide range of individuals, including civil engineers, structural engineers, architects, design
professionals, building officials, construction contractors, facility mangers, fire-fighters, or otherindividual with a general background in building design or construction. The screeners fill out the forms
and determine the scores to get seismic performance of the building. There are five different types of Level
I Data Collection Form, representing different seismicity regions; Very High, High, Moderately High,
Moderate and Low. The basic scores and score modifiers vary with seismicity regions.
Level (II) Data Collection Form is optional type and it should be filled by a civil or structural
engineering professional, architect, or graduate student who has experiences and background knowledge
on seismic evaluation of design of buildings. It should be noted that the screener applies same type ofseismicity region to both Level I and II Form. If possible, Level I and II should be screened by same
person. In Level II Data Collection Form, it includes four main sections;(1) Building information and adjusted base line score,(2) Structural modifiers to add to adjusted baseline score,(3) Observable non-structural hazard, and(4) Comments

Figure.6 Level (I) Data Collection Form

306

USMCA 2019, Yangon

Figure.7 Level (II) Data Collection Form
11. RVS RESULTS FOR CASE STUDY BUILDING

The main purpose of RVS results is to know the current situation of existing building in relation
to seismic hazard and other related hazards. The final RVS score of case study building for moderate highseismicity region is higher than cut-off score and for high seismic region is lower than cut-off score.
12. CONCLUSION

As a result of all experimental investigated of teak and pyingado, their results are reasonable andapplicable to use seismic safety assessment and evaluation of existing timber building. , the chemicaltreatment should be added to this building member for usage due to its nature of likely to be attacked by
insects. The investigation result of shear wave velocity for Pyay hostel area is 300 m/sec.The shear wave
velocity of Kamaryut area is between 200 and 300 m/sec. Soil type D is mostly found in Yangon according
to MNBC 2016. According to the FEMA guideline, Rapid Visual Screening technique (RVS) is anefficient method to quickly identify the seismic resistance of the building. To implement this study, theseismicity of region, soil information and determination of pre-code building were considered as pre-fieldsurvey data. According to the RVS data evaluation, detailed structural evaluation is required for highseismicity performance and also not required for moderate seismic performance.
ACKNOWLEDGMENT
At first, the author would like to express deep appreciation to Dr. Nyan Myin Kyaw, for his insightsuggestion and advice. And then, the author wishes to express his sincere gratitude to the Department ofEngineering, Yangon Educational University ,NDT Engineering Teams for their invaluable help andguidance. Finally, the author would like to express grateful thanks to all teachers and parents for theirsupports, kindness and unconditional love and all his friends for their helps and advices on his studying.

307

USMCA 2019, Yangon

REFERENCES[1] Khin Maung Zaw. 2002 “An Evaluation of Ultimate Strength and the Performance of Timber
Beams.” M.Engg. Thesis. University Teknologi Malaysia.
[2] Anon.1983. ASTM Standard Methods of Testing Small Clear Specimens of Timber D 143-09. 100
Barr Harbour Dr. PO Box C700 West Conshohocken, Pennsylvania 19428-2959, United States.
[3] MNBC2016, "Myanmar National Building Code 2016"[4] Hélder S. Sousaa, Jorge M. Brancoa, Paulo B. Lourençoa, “Use of bending tests and visualinspection for multi-scale experimental evaluation of chestnut timber beams stiffness”.
[5] FEMA. 2000. Rapid Visual Screening of Buildings for the Seismic Rehabilitation of Buildings.
FEMA 154, Federal Emergency Management Agency, Washington, D.C.
[6] FEMA. 2000. Prestandard and Commentary for the Seismic Rehabilitation of Buildings. FEMA
155, Federal Emergency Management Agency, Washington, D.C.

308

DIFFERENCE IN BUILDING COLLAPSE RISK IN YANGON DUE TO APPLICABLE DATASET
O. MURAO1, T. IKEDA2, M. KOSHIHARA3, K. MEGURO3, and T. SHWE4
1 Professor, IRIDeS, Tohoku University, Japan,

2 Professor, Nagaoka University of Technology, Japan,

3 Professor, ICUS, IIS, The University of Tokyo, Japan,
4 Professor, Yangon Technological University, Japan,

Correspond to Prof. O. MURAO (murao@irides.tohoku.ac.jp)
Keywords: urban vulnerability, Myanmar, vulnerability function, ground condition, building structure
1. INTRODUCTION
Myanmar has been increasingly thriving since thecivilian government led by President U Thein Sein wasestablished in 2011. However, similar to other Southeast
Asian countries, it is vulnerable to natural disasters suchas cyclones, floods, and earthquakes. Myanmar is at thegreatest urban disaster risk for earthquakes. This is largely
due to several populated, major cities such as Mandalay,
Naypyidaw, Bago, and Yangon developed along theSagaing Fault—a continental transform fault between the
Indian and Sunda plates. In the 20th century, 6
earthquakes at or above 7.0 magnitude have occurredalong the fault.
The authors have been involved in the SATREPS
project “Development of a Comprehensive Disaster
Resilience System and Collaboration Platform in
Myanmar” since 2014 and were responsible fordeveloping a vulnerability map in terms of building
collapse risk for Yangon as the earthquake-related disastergroup. However, Yangon City has not catalogued enoughdata for the assessment. Then, in 2019, we tried toevaluate its building collapse risk, as shown in Figure 1,
with existing ground condition data which was publishedin 1934 [1-2], and vulnerability functions for Japanesebuildings developed by the actual building damage dataset
due to the 1995 Great Kobe Earthquake. The results areclarified as follows:(1) Wooden buildings and RC account for 93.8% of allbuildings.
(2) Based on Tokyo Metropolitan Government’s
method, the 567 objective wards were categorized into
five ranks according to the building collapse risk value. It
indicated that wards in the Dawpon and Tharkayta
Townships, located in the west side of Pazundaung Creek,
were the highest. Some newly developed outskirts areas,such as Hlaingtharyar or Dala, also appeared as vulnerablewith Rank 4 and 5.
2. DATA USED FOR REVISION
By the end of August 2019, we collected groundcondition dataset and constructed vulnerability functions
for the buildings in Yangon based on field surveys
conducted in the SATREPS Myanmar Project. From theviewpoints above, this paper examines building collapse
risk for Yangon using the latest dataset.
These will be demonstrated in the presentation.

Figure 1. Distribution of building collapse risk in Yangonᆅ┙ซ౛
Township_border

Ward_border
Ward_border.Geology
Qal

±

Qvd
T-pa
T-pd

0

2.5

5

10

15

20
km

1:170,000

Figure 2. Ground condition classified by wards
REFERENCES[1] H. H. Aung: “Potential Seismicity of Yangon Regeon(Geological Approach),” Advances in Geosciences,
Vol.26, 139-151, 2010.
[2] H. L. Chhibber: “The Geology of Burma,”
Macmillan and Co. Limited, St. Martin’s Street, London,
1934.

309

Opening ceremony

YTU main gate

Prof. Myint Thein Rector of YTU, Prof .Khin Than Yu,
Prof. Kimiro Meguro, Director of ICUS, IIS, UTokyo (from left)

Key note speakers
Dr. Takayuki Miyoshi Nippon Koei Co., LTD (left) Dr. Toe Aung Direcotr of YCDCGroup photo of participants

311

Exhibitions

312

Presentation

Seminar Room 1 (Session B, D, F, H)

313

Presentation

Conference Room 1 (Session A, C, E, G)

314

Speakers

Closing Ceremony

Prof. Tun Naing, YTU Prof. Kimiro Meguro, UTokyo

Prof. Pennung Warnitchai, AITYoung-Researcher-Award recipients with Prof. Meguro (left) and Prof. TunNaing

315

Banquet party at Inya Lake Hotel, 9th night

Opening Speech, Prof. TunNaing, YTU

Closing Speech,
Prof. Kaori Hayashi, UTokyo

316

Lunch, Break time

Farewell Party at Esperade Lake View Hotel, 10th night

317

–

ITINERARY
Day 1
5:30

Pick-up at Hotel

6:00

Check in at the Yangon Airport Domestic Terminal (T3)

7:15

Flight 7Y121 Departure from Yangon Airport

8:35

Arrival at Nyaung-U airport

9:15

Bagan Viewing Tower

10:30-12:00
Bagan Seminar at Ball Room, Bagan Umbra Hotel, Nyaung U Township, Bagan
Moderator Mr. Miyoshi
10:30 – 11:00 “The history and cultural significance of Bagan (TBC)“
U Aung Aung Kyaw, Head of Bagan region, Ministry of Religious Affairs andCulture11:00 – 11:30 “Bagan as a UNESCO World Heritage site (TBC)”
U Than Zaw Oo, in charge of World Heritage registration, Ministry of
Religious Affairs and Culture
11:30 – 11:45

Q&A

11:45 – 12:00 “Introduction to Bagan: temples and famous sites to visit (TBC)” YTU students
12:30-

Lunch at Riverside restaurant

14:00-

Visit to historical area

18:30-

DinnerDay 2
9:00-16:00

318

Visit to Historical area–

Thase Pyin Taw Village

–

Sally

–

Mount Popa

16:30

Check in

17:35

Flight Y5201 Departure from Nyaung-U airport

18:55

Arrival at Yangon airport

Technical Tour on 11-12th,visit to BaganGroup photo from Bagan Viewing Tower

319

Seminar at Bagan Umbra hotel

Lunch time320

Visit to historical area

Manuha Temple

Ananda Temple

Shwezigon Pagoda

321

View of sunset

Dinner time

Nyaung-U Morning Market

Salay Yoke Sone Monastery at Salay

Group photo at Salay Yoke Sone Monastery322

Lunch time at Salay

Oil mining around Chauk

Thabyinnyu Temple

323

International Center for Urban Safety Engineering
Institute of Industrial Science, The University of Tokyo
4-6-1 Komaba, Meguro-ku,
Tokyo 153-8505, Japan
Tel: +81-3-5452-6472
Fax: +81-3-5452-6476
http://icus.iis.u-tokyo.ac.jp
E-mail: icus@iis.u-tokyo.ac.jp