Forefront and Challenges of Geospatial
Technologies for Environmental andDisaster Management in Southeast Asia
27 November 2010
Pathumwan Princess Hotel, Bangkok, Thailand

Organized by
Regional Network Office for Urban Safety (RNUS),
School of Engineering and Technology,
Asian Institute of Technology;
International Center for Urban Safety Engineering (ICUS),
Institute of Industrial Science (IIS), The University of Tokyo;
Chula Unisearch, Chulalongkorn University; andIIS Alumni Thailand Chapter
In cooperation with
Geo-Informatics and Space Technology
Development Agency (GISTDA);
Remote Sensing and GIS Association of Thailand(RESGAT);
Japan Society of the Promotion of Science (JSPS),
Bangkok office;and Japan Aerospace Exploration Agency (JAXA),
Bangkok office

Edited by
Dr. Akiyuki Kawasaki

FOREFRONT AND CHALLENGES OFGEOSPATIAL TECHNOLOGIES FORENVIRONMENTAL AND DISASTER
MANAGEMENT IN SOUTHEAST ASIA
November 2010
PREFACEDue to rapid and dynamic changes in economy, society and theenvironment in the context of globalization and localization, southeast Asia
faces many new challenges and opportunities such as politicaldemocratization, administrative decentralization and improved governance,
regional economic cooperation, trans-boundary resource management andsustainable development, gender bias-free, infectious diseases prevention,and disaster preparedness and response.
Among these many critical issues, consideration of the environmentand disaster is drastically increasing in the region due to record flooding anddraughts in recent years – especially in the Lower Mekong River basin.
At the same time, the potential of geospatial technologies such as
Geographic Information System (GIS) and Remote Sensing as promisingtools for integrated environmental and disaster information management andanalysis is increasing. Remote Sensing allows us to evaluate andunderstand the status of environment and disaster in near-real time withwide coverage at multiple scales, and GIS allows rapid arrangement ofgeospatial data infrastructure and comprehensive analyses of various kindsof data at a local level.
To address the raise of public awareness to these issues, a half-day
symposium, "Forefront and Challenges of Geospatial Technologies forEnvironment and Disaster Management in Southeast Asia," was held at the
Phatumwan Princess Hotel, Bangkok, Thailand, on November 27, 2010.
This symposium was co-organized by the International Center for Urban
Safety Engineering (ICUS), Institute of Industrial Science (IIS), theUniversity of Tokyo; the Regional Network Office for Urban Safety(RNUS), Asian Institute of Technology (AIT); Chula Unisearch,
Chulalongkorn University; and IIS Alumni Thailand Chapter.
The objectives of this symposium were:- To understand critical environmental and disaster problems inSoutheast Asia
- To share and exchange knowledge, information and opinions
among geospatial researchers, practitioners, and decisionmakers.
- To discuss forefront and challenges of geospatial technologies
for solving problems

November 2010, Thailand
November 2010, Thailand

In this symposium, we invited eight distinguished speakers in the fieldof geospatial technologies, environmental and disaster management fromThailand and Japan. Unfortunately, Prof. Haruo Sawada from ICUS, IIS,The University of Tokyo had to cancel his presentation due to a sudden
health problem.
Overall, the symposium was completed successfully, with interesting,informative and exciting presentations and lively questions and discussions.
We also obtained many positive evaluations through the questionnaire
sheets answered by the participants. We hope this symposium contributed topromoting information exchange, mutual communication and understanding
and research collaboration among universities, institutes, and private sectors
in Thailand and Japan.
Finally, we appreciate the University of Tokyo’s Institute of Industrial
Science (IIS) Alumni Association for financially supporting this symposium
as a pre-event of the 4th IIS Alumni Thailand Chapter party held at the samedate.
Akiyuki KAWASAKI,

Forefront and Challenging Geospatial Technologies for
Forefront and Challengesof Geospatial
Technologies
for Environmental
andEnvironmentand Disaster
Managementin Southeast Asia
Disaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Table of Contents
Page
Overview of space technology development in Thailand
Suvit Vibulsresth1

Monitoring, modeling and assessment of urban sustainability
Yoshifumi Yasuoka

3

Community-based Climate Centers
Anond Snidvongs

17‘Sentinel Asia’, ‘SAFE’ and JAXA’s earth observation activities
Shinichi Mizumoto

23

Role of JSPS Bangkok office for promoting research and education inSoutheast Asia
Wataru Takeuchi

41

Geospatial planning for flood water retention sites to mitigate flood anddrought in Chi River Basin, Thailand
Nitin Kumar Tripathi

47

Development of Tsunami Disaster Mitigation System considering thecharacteristics of the Indian Ocean Region
Kimiro Meguro

67

Approaches to identifying the areas at risk of flood and drought over
Northeast Thailand
Charat Mongkolsawat

87

Forefront and Challenges of Geospatial Technologies for Environmental andForefront
and Challengesof Geospatial
Disaster Managementin Southeast
Asia Technologies for Environmental andDisaster Management in Southeast Asia

SYMPOSIUM SUMMARY
November 27th, 2010
The International Center for Urban Safety Engineering (ICUS), theUniversity of Tokyo, and the Regional Network Office for Urban Safety(RNUS), AIT organized a seminar titled “Forefront and Challenging
Geospatial Technologies for Environment and Disaster Management inSoutheast Asia” at Pathumwan Princess Hotel (Room Jamjuree BallroomA) on November 27, 2010.
The seminar was held in half-day with eight distinguished speakers.
The seminar was inaugurated by Dr. Akiyuki Kawasaki, Regional Network
Office for Urban Safety (RNUS), and followed by the welcome and opening
speech by Dr. Suvit Vibulsresth, National Research Council of Thailand,
and member of IAA.
The speakers consists of Prof. Yoshifumi Yasuoka (Executive Director,
National Institute of Environmental Studies, Japan); Dr. Anond Snidvongs(Acting Executive Director, Geoinformatics and Space Technology
Development Agency (GISTDA); Mr. Shinichi Mizumoto (Director, Japan
Aerospace Exploration Agency (JAXA); Assoc. Prof. Dr. Wataru Takeuchi(Director, JSPS Bangkok office and IIS, The University of Tokyo);Dr. Nitin Kumar Tripathi (Director, UNIGIS, AIT); Prof. Kimiro Meguro(Director, ICUS, IIS, The University of Tokyo); and Assoc. Prof. Dr. Charat
Mongkolsawat (President, Remote Sensing and GIS Association of Thailand(RESGAT).
Among about 140 participants, 114 audiences retuned the questionnaire
sheet to the secretariat, and their replies were as follows:
The list of the organizations in which total 114 audiences attended theseminar:Number ofOrganization
audience
47
University
AIT

17

Chulalongkorn University

10

Srinakharinwirot University

7

Burapha University

3

Mahidol University

3

King Mongkut’s Institute of Technology

2aaNovember 2010, Thailand
November 2010, Thailand

Mahanakorn University

2

International Maritime Collage

1

Khon Kaen University

1

Prince of Songkla University

1

Thai Government

49

GISTDA (Geo-Informatics and Space Technology
Development Agency)

12

Royal Irrigation Department

11

Department of Alternative Energy Development andEfficiency

3

Department of Public Works and Town & Country
Planning

3

Office of Natural Calamity and Agricultural Risk
Prevention

3

Department of Groundwater Resources2

Department of National Park, Wildlife and Plant
Conservation

2

Hydro and Agro Informatics Institute2

Land Management Office2

Navy Hydrographic Department

2

Bureau of Royal Rainmaking and Agricultural Aviation

1

Department of Drainage and Sewerage

1

Department of Mineral Resource

1

Electricity Generating Authority of Thailand

1

Office of the Public Sector Development Commission

1

Royal Thai Survey Department

1

Water Resource Engineering

1

Private sector
ASDECON Corporation Co., ltd

b
b

13
4

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Panya Consultant Co., Ltd

2

ATP Consultant Co., ltd

1

Chevron Thailand

1

Design Div. Public Work

1

ESIRT

1

Picito Co., Ltd

1

Team Consulting Engineering and Management Co., Ltd

1

The Environmental Research and Training Center

1

International or foreign organization

5

JAXA (Japan Aerospace Exploration Agency)

3

JICA (Japan International Cooperation Agency)

1

UNESCAP (United Nations Economic and Social
Commission for Asia and the Pacific)

1

Additional desired seminar topics:
JSPS• JSPS and its activities with Thailand• Role of JSPS ban
Environmental• Environmental impact prediction• Strategy for Environmental Policy• Health & environment
Tsunami• Development of Tsunami Disaster mitigation system considering
the characteristics of Indian ocean region• Development of Tsunami disaster mitigation system
Climate• Community-based climate centers• Effect from climate change• Data Sharing and Climate Change Research• Water management under climate change in the future• Adaptation in climate change• Global climate change: impacts & mitigation• Community based climate centers• Scientific prediction of climate change phenomenon

Forefront and Challenges of Geospatial Technologies for Environmental andForefront
and Challengesof Geospatial
Disaster Managementin Southeast
AsiaTechnologies for Environmental andDisaster Management in Southeast Asia

ccNovember 2010, Thailand
November 2010, Thailand• Monitoring modeling and assessment of climate variability inhigher mountain
Flood water• Geo spatial planning for flood water retention site
• Approaches to identifying areas at risk of rough and flood over
Northeast Thai
• Flood disaster in 2010 and the west
GIS
• GIS and MIS Application for groundwater management• GIS for traffic management• GIT for rural urban linkage
Disaster• Disaster mgt. Warming prevention• Mitigations of Disaster• Protection and monitoring in disaster
Other• Applying of Historical data matching• Coastal and Ocean data observation techniques• Change detection forest• Approaches to identifying areas at risk
• Should have more than study area in southeast Asia
• Applications in rural development• Application of lease on land for civilization
Comments:
Time management• Some speaker don't care about their time frame of presentation• Too much packed schedule what discouraged the frequently
asking of questions to the presenters• The duration was too shortVenue• Should have covered other aspects such as rural development
application• I insist for further continuity of such seminars for technology
transfer and update recent developments in the area of geoinformation• complement and application• real case, real time
• Very good seminar in field of disaster management.
Contents• The room with 2 big columns blocking the audience• Vision obstructionddForefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48• The conference room is not suitable for meeting.
• May consider other room
Other
• Promoting of research may be done actively by travelling touniversity in the area. All university would be appreciate tocooperate• The promotion may be done in government unit or agencies.
• Overall it was a nice arrangement• Overall the event was very well-organizedForefront and Challenges of Geospatial Technologies for Environmental andForefront
and Challengesof Geospatial
Disaster Managementin Southeast
AsiaTechnologies for Environmental andDisaster Management in Southeast Asiaee

ICUS Report 48
ICUS Report 48

Welcome board

ICUS & RNUS booth

JSPS booth

JAXA boothRegistration

Welcome participant

Opening ceremony (Dr. Akiyuki Kawasaki)

Dr. Suvit Vibulsresth

Forefront and Challenges of Geospatial Technologies for Environmental andForefront
and Challengesof Geospatial
Disaster Managementin Southeast
Asia Technologies for Environmental andDisaster Management in Southeast Asiaii

November 2010, Thailand
November 2010, Thailand

ii
ii

Prof. Yoshifumi Yasuoka

Dr. Anond Snidvongs

Mr. Shinichi Mizumoto

Dr. Wataru Takeuchi

Dr. Nitin Kumar Tripathi

Prof. Kimiro Meguro

Dr. Charat Mongkolsawat

Participants

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

After-seminar: Alumni Party

Thank you present for Dr. Suvit

Thank you present for Dr. Nitin

Thank you present for Dr. Charat

Alumni Party Group Photo

Forefront and Challenges of Geospatial Technologies for Environmental andForefront
and Challengesof Geospatial
Disaster Managementin Southeast
Asia Technologies for Environmental andDisaster Management in Southeast Asia

iii
iii

Overview of Space Technology Development inThailandDr. Suvit VibulsresthOVERVIEW OF SPACE TECHNOLOGYDEVELOPMENT IN THAILAND
SUVIT VIBULSRESTH
Former Executive Director, GISTDA
suvit@gistda.or.th
Space Technology in terms of remote sensing and geoinformation was
first introduced into Thailand with the NASA Earth Resources Technology
Satellite (ERTS) programme in 1972 when Thailand was accepted as one of
the Principal Investigators (PI). Thailand National Remote Sensing
Coordinating Committee was set up by the cabinet to liase with NASA andother international organizations under the leadership of Dr. Boon
Indrambarya, the first coordinator of the Thai Programme. The success ofthe various application of ERTS (later called Landsat) data led to theestablishment of Thailand Satellite Ground Receiving Station in 1981, firstof its kind in Southeast Asia. The assistance and support from Canada, USA
and Japan helped usher the Thai ground station into one of the top fivebiggest satellite data providers in the would during 1988 to mid 1990’s. At
the same period, most of the applications in agriculture, land use, forestry,
etc. reached quasi-operational status. Universities offered bachelor andmaster degree courses in remote sensing, GIS, and related subjects both in
Bangkok and in provincial universities. The active participation of Thailand
in ESCAP Regional Remote Sensing Programme (RRSP) and later inRegional Space Application Programme (RESAP) and in ASEAN
Committee on Science and Technology (COST), Subcommittee on Space
Application (SCOSA) culminated in the government decision to build
Thailand’s first earth observation satellite (TRSS) with Canada in 1996.
However, the economic crisis of 1997 compelled the cancellation of the
project. When Geoinformatics and Space Technology Development Agency(GISTDA) was established as a public organization replacing ThalandRemote Sensing Center (TRSC) of the National Research Council in 2000,
development of satellite project was revived, this time with France. The
satellite, named THEOS was signed in min 2004 and launched in 2008. At
present, THEOS is providing Thailand and other countries around the world
with 2.5 m panchromatic and 17.0 m multispectral data for various
applications ranging from urban planning, cartography, agriculture, forestry,land use planning, coastal erosion study and environmental monitoring. All
the way, the spirit of coordination and cooperation domestically andinternationally was the mainstay of Thai philosophy in space utilization.
This was elaborated in the presentation.

11

November 2010, Thailand
November 2010, Thailand

22

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

Monitoring, Modeling and Assessment of
Urban Sustainability
Prof. Yoshifumi Yasuoka

MONITORING, MODELING ANDASSESSMENT OF URBANSUSTAINABILITYYOSHIFUMI YASUOKA
Executive Director, National Institute of Environmental Studies, Japanyyasuoka@nies.go.jp

33

November 2010, Thailand
November 2010, Thailand

44

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Monitoring,
Monitoring, modelingmodelingand
andassessment
assessmentofofurban
urbansustainability
sustainability

55

November 2010, Thailand
November 2010, Thailand

66

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Monitoring,
Monitoring, modelingmodelingand
andassessment
assessmentofofurban
urbansustainability
sustainability

77

November 2010, Thailand
November 2010, Thailand

88

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Monitoring,
Monitoring, modelingmodelingand
andassessment
assessmentofofurban
urbansustainability
sustainability

99

November 2010, Thailand
November 2010, Thailand

10
10

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Monitoring,
Monitoring, modelingmodelingand
andassessment
assessmentofofurban
urbansustainability
sustainability

11
11

November 2010, Thailand
November 2010, Thailand

12
12

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Monitoring,
Monitoring, modelingmodelingand
andassessment
assessmentofofurban
urbansustainability
sustainability

13
13

November 2010, Thailand
November 2010, Thailand

14
14

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Monitoring,
Monitoring, modelingmodelingand
andassessment
assessmentofofurban
urbansustainability
sustainability

15
15

November 2010, Thailand
November 2010, Thailand

16
16

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

Community-based Climate Centers
Dr. Anond Snidvongs

COMMUNITY-BASED CLIMATECENTERSANOND SNIDVONGS
Director, Southeast Asia START Regional Center (SEA START RC),
Chulalongkorn University; and Acting Executive Director,
Geoinformatics and Space Technology Development Agency (GISTDA)
anond@start.or.th

Community-based Climate Centers

A Tool to Increase Resilience to Local Climate
Anond Snidvongs

Director, Southeast Asia START Regional Center
Chulalongkorn University

Major Climate Phenomena
Time scale (time periods where changes/differences may be realized)
Hours-day

Day/night (diurnal) temperature, land/sea
breezes, tides

Days-weeks

Spring/neap tidal cycle, storm events

Weeks-months

Madden-Julian Oscillation

Months-year

Winter/summer, monsoons, tropical storm
seasonEl Nino/La Nina events, Indian Ocean
DipoleYears-Decade
Decades-century

Pacific Decadal Oscillation, GHG driven
climate change

17
17

November 2010, Thailand
November 2010, Thailand

El Nino and La Nina Events

Rainfall Anomaly in Thailand from 1951 - 2006

%differ fromaverage

20.0
10.0
0.0

1

11

21

31

41

51

-10.0
-20.0

Year

Tropical Storms in the Gulf of Thailand(1953-2010)
PDO cycle??

No. per 5 y
6TyphoonTropical Storm
Tropical Depression

5

4

3

2

1

0
19531957

19581962

19631967

19681972

19731977

19781982

19831987

19881992

19931997

19982002

20032007

20082012

20132017

20182022

20232027

20282032

20332037

Khonkaen

B2

31
30
29
28
27
26
25
24
23
22
21
20
19
18
17
16
15
14

A2
B2

2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

A2

2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

Degree Celcius

44
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
28
27

Degree Celcius

Minimum temperature (3 months average) : comparison ECHAM4 A2 vs B2
Khonkaen-Thailand

Maxium temperature (3 months average) : comparison ECHAM4 A2 vs B2
Khonkaen-Thailand

Annual precipitation : comparison ECHAM4 A2 vs B2
Khonkaen-Thailand
2500

2000

mm

1500
A2
B2

1000

500

2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

0

18
18

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ENSO
Years

Community-based
Community-basedClimate
ClimateCenters
Centers

Time (y)

2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

mm

Degree Celcius
31

30

29
A2

B2

Century

DecadeDays/weeks

1

10
Degree Celcius

2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

mm

2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

Degree Celcius
42
41
40
39
38
37
36
35
34
33
32
31
30
29
28
27

28
26

27
25
2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
2052
2054
2056
2058
2060
2062
2064
2066
2068
2070
2072
2074
2076
2078
2080
2082
2084
2086
2088
2090
2092
2094
2096
2098

A2

B2

Degree Celcius

ICUS Report 48
ICUS Report 48

Don Muang

Maximum temperature (3 months average) : comparison ECHAM4 A2 vs B2
Donmueang-Thailand
Minimum temperature (3 months average) : comparison ECHAM4 A2 vs B2
Don muang-Thailand
30

29

28

27

Maximum temperature (3 months average) : comparison ECHAM4 A2 vs B2
Phuket-Thailand

33

32

100

26

25

24

23
A2

22

21

20

19

B2

18

17

Annual precipitation : comparison ECHAM4 A2 vs B2
Don Mueng -Thailand
3000

2500

2000

1500

1000

A2

500

B2

0

PhuketMinimum temperature (3 months average) : comparison ECHAM4 A2 vs B2
Phuket -Thailand
33

32

31

30

29
A2

28

27

B2

Annual precipitation : comparison ECHAM4 A2 vs B2
Phuket-Thailand

6000

5000

4000

3000

2000
A2

1000
B2

0

Matters of Scales

Climate Cycle

100

10

1

Months/season 0.1

0.01

Space (ha)

1000

10000

1000001000000

19
19

November 2010, Thailand
November 2010, Thailand

Need to know local climate to improve local weather
forecast
Weather:•State of the atmosphere at any location at a particular
time
Climate:•Overall description of weather regime of a location•Collections of weather over a long period•Represent by narrative description or quantitative
parameters

Many ways to do weather forecast
Local/Synoptic-based•Persistent•Trend•Climatology
Modeling-based•Many from both national and international sources

Components in Forecasting cycles
1. Centralized forecasting systems (synoptic network,
weather typing, trend analysis, NWP, etc)
2. Scaling
3. Interpretation in to local contexts

20
20

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

No single model can be good at any situations, models(with different physics, numerical schemes, resolutions,boundary and initial conditions, etc.) provide
uncertainties due to know scientific basis
Concept of ‘Ensemble’
Local climatology (reasonably long-term observation of
local weather) of the location are required to ‘calibrate’and continue to ‘evaluate’ if re-calibration of ensemble
may be needed

A medalist sharpshooter undera controlled condition

The same sharpshooter shooting
at the target in a dark room

May easily hit the bull eye

Will be very likely to miss the bull eye

Many shooters using various equipments from different angles aiming
at the target in a dark room

Will score theirs marks
unevenly on the target(and not necessary thatmodern Olympic medalists
will do better than Mr.
Robin Hood or Mr. Pancho
Villa!!)

Community-based
Community-basedClimate
ClimateCenters
Centers

But their distribution is
likely to cover the bull
eye

21
21

November 2010, Thailand
November 2010, Thailand

Third Common Misuses of Climate Models• Overemphasize on multi models precision

Accurate but notprecise22
22

Accurate andpreciseNot accurate but
preciseForefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia‘Sentinel Asia’, ‘SAFE’ and JAXA’s Earth
Observation Activities
Mr. Sinichi Mizumoto

‘SENTINEL ASIA’, ‘SAFE’ AND JAXA’SEARTH OBSERVATION ACTIVITIESSHINICHI MIZUMOTO
Director, Japan Aerospace Exploration Agency (JAXA), Bangkok Officemizumoto.shinichi@jaxa.jp

RNUS Seminar 2010

JAXA’s Role in Climate Change Adaptation
and APRSAF, Sentinel Asia and SAFE
November 2010

Shinichi Mizumoto
Director, Bangkok Office
Japan Aerospace Exploration Agency (JAXA)
1

Contents

� Outline of JAXA� JAXA’s Role in Climate Change
Adaptation
� Asia-Pacific Regional Space Agency
Forum (APRSAF)
� Initiatives of APRSAF / Sentinel Asia,
Space Applications for Environment(SAFE)
� Cooperation between JAXA and AIT

2

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November 2010, Thailand
November 2010, Thailand

History of Japan’s Space Activities
University

NAL ISAS University of Tokyo

1950s

1960s

1970s

1980s

2000s

1990s

2010

Start of SpaceRelated Research↓61 Kappa Rocket↓70 Lambda-Rocket↑Itokawa Rocket▲ 62 ISAS Establishment↓

Satellite Science Mission←70 1 st Japan Satellite▲54 NAL Establishment▲Solid/fluid Engine

Oct. 2003▲ JAXA Establishment

NASDA

Import of US
Technology,
Practical Application
Satellites ▲▲▲↓N-I#1 BS, CS, GMS
Transition to Independent
Development and Beginningof Diversification↓94 H-II Development.

Successes↑01 RTF of H-IIA▲05
New Era with
JAXA Vision

Technological Maturity, Diversification,
Internationalization←94 2tong satellite
ETS-VI※Other
Ministries

Ministry of Education (MEXT)▲69 NASDA Establishment▲08
Strategic HQ
New Space Law

3（※METI,MAFF,MLIT,Ministry of Environment）

JAXA Organization and Resources
President

Total Personnel
1,565
April 1, 2010

Policy Coordination

Space
Transporta tion
MissionDirectorate

FY 2010 Budget
180.0B yen (1.8B US$)

Executive
Directors

Space
Applications
MissionDirectorate

April 1, 2010

Admin. Management
Human
Space
Systems
and
Utilization
MissionDirectorate

Aerospace
R&D
Directorate

Technical Management

Aviation
ProgramGroup( Chofu )( Tsukuba )Inst. ofSpace &
Astro.
Science

Lunar &
Planetary
Exploration
ProgramGroup( Sagamihara )4

JAXA Field Centers
Liaison Offices

Kakuda Space Center

Noshiro Testing Center

Washington, DC, USA
Houston, TX, USA
Paris, France

Tsukuba Space Center(TKSC)
Earth Observation Center

Bangkok, Thailand

Usuda Deep Space Center

Katsuura T & C Station
JAXA Tokyo Office

Kagoshima Space Center
Chofu Aerospace Research Center

Sagamihara Campus

Okinawa T & C Station

Ogasawara Downrange Station

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ICUS Report 48
ICUS Report 48

Overview
Overview ofof thethe 2nd
2nd Mid-term
Mid-term Plan
Plan ofof JAXAJAXAContributions toward a Secure and Prosperous Society (R&D)

Environment

Precipitation

Moisture

GlobalPrecipitation
Measurement
Satellite/
Dual-frequency
Dual-fre�uency
Precipitation Radar(GPM/DPR)

Greenhouseeffect gases

Navigation Satellite

Greenhouse Gases
Observing
Satellite（GOSAT）

11st �uasi-Zenith
Quasi-Zenith
Satellite

Cloud Aerosol Radiation
Mission/Cloud Profiling Radar
(EarthCARE/CPR)

Global Change Observation
Mission-Water（GCOM-W）
Global Change
Observation MissionClimate（GCOM-C）GPS
Availability enhancement
・Performanceenhancement

Cloud/Aerosol

Expansion of Human �rontiers
Frontiers

International Space Station（ISS）

Space Explorer
Successor ofSE�enological
SELenological and
ENgineering
Explorer (SE�ENE(SELENE)

Space Science

ISS/�apanese Experiment
ISS/Japanese(�EM) Kibo
Module (JEM)

Venus Climate
Radio Astronomy
Orbiter
X-ray Astronomy Satellite （ASTRO- （PLANET-C)（P�ANET-C)
H-ⅡTransfer Vehicle
G）
Satellite（ASTRO（HTV）
H）

KAGUYA

Int’l Mercury
ExplorationPro�ect
Project（BepiColombo)

Successor ofAsteroid Explorer(HA�AB�SA)(HAYABUSA)

Development of Advanced Technologies

Aeronautics

Space Transportation

H-IIＢ
launch vehicle

Next Generation SSTMHITo Contribute toward Industry needs using fundamental tech�NG
LNG Propulsion System

6
6

JAXA’s Major
Earth Observation
Observation Activities
Activities
JAXA’sMajor Earth
GEOSS
implementation plan
GEOSS 10
10 years
years implementationplan①

Disasters
Disasters⑥
Weather
Weather
MTSAT(JMA)
MTSAT (JMA)①Disaster prevention
prevention andandmitigation
mitigation②
HealthHealthMonitoring
Monitoring flood,
flood, earthquake,
earthquake,crustaldeformation, forest,
crustal deformation,
forest,biomass,etc.
biomass, etc.

⑦
Eco-systems
Eco-systems③
EnergyEnergy⑧Agriculture
Agriculture②Greenhouse gas
gas andandcarbonflux
carbon flux④

ClimateClimate⑨
Bio-diversity
Bio-diversity③Climate changechange andand water
water
cycle
cycle

⑤

Water
Water

Precipitation, cloud,aerosol, SST,
Precipitation,
cloud, aerosol,
SST,
snow,
snow, ice,
ice, etc.
etc.

7
7

Long-Term
Long-Term Plan
Plan ofof Earth
Earth Observation
Observation
Targets
Targets

2006

2007

2008

2009

2011

2012

2013

2014

2015

2016

2017

2018

[Land and Disaster monitoring]

Disasters
Disasters&&

ALOS-2 SAR

Resources
Resources

ClimateClimateChangeChange
&
&
Water
Water

2010

ALOS

ALOS-3 Optical

JAXA-NASA
JAXA-NASA

JAXA-NASA
JAXA-NASA[Precipitation]

TR
TRMM

GPM/DPR
GCOM-W1/ AMSR2[Wind, SST , Water vapor]

AMSR-E on AQUA

Water
Water
Cycle
Cycle

JAXA-NASA
JAXA-NASA

GCOM-W2acloud, SST, ocean color][Vegetation, aerosol,

250m, multi-angle, polarization

ClimateClimateChangeChangeGreenGreenhouse
house
gases
gases

Mission status

GCOM-C2-C2GCOM-C1/ SGLI[Cloud and Aerosol 3D structure]

JAXA-ESAJAXA-ESAE arth C
A RE/C PR
Earth
CARE/CPR[CO2, Methane][CO2, Methane]

GOSAT-2

GOSAT

On orbit‘Sentinel
earth
observation
activities‘Sentinel Asia’,
Asia’,‘SAFE’‘SAFE’andandJAXA’s
JAXA’searth
observation
activities

Phase B~

Phase A

Pre-Phase A

Extension

8
8

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November 2010, Thailand
November 2010, Thailand

Advanced Land Observing Satellite(ALOS)© JAXA

ALOS

PRISM

• Disaster monitoring• Cartography• Regional observation• Resources surveying

Panchromatic Remotesensing Instrument for
Stereo Mapping© JAXA© JAXAAVNIR-2

PALSAR

Advanced Visible andNear Infrared Radiometer
type 2Phased Array type Lband Synthetic
Aperture Radar

ALOS Pansharpen (PRISM/AVNIR-2) image over Tokyo
observed on August 29, 2006

9

Monitoring Forest in Amazon(Deforestation)©JAXA,METI

1995 (JERS-1)

2007 (ALOS)• Within seven days after the data acquisitions, JAXA provides thequickly processed SAR images to IBAMA (Instituto Brasileiro do
Meio Ambiente e dos Recursos Naturais Renováveis).
• The data are being utilized for the illegal deforestation monitoring.
10

Disaster Monitoring (Flood in Myanmar)

Myanmar was heavily flooded from May 2 to May 3, 2008, due
to Cyclone “Nargis”. JAXA decided to activate the
ALOS/PALSAR to observe the area quickly, and succeeded toacquire image the area on May 6.
- Overlaying images with Apr. 24, 2008 ScanSAR (right)
Blue: inundation area
Yellow: expecting soil moisture increased

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Disaster Monitoring (Earthquake in China)

Many land slides
Dammed lake andrivers destroyed by land slides

3D view in south-west China using PRISM/DSM and pan-sharpened image by PRISM and AVNIR-2 on June 4, 2008
- PRISM can generate digital surface model (DSM)- Many land slides have been occurred

12

Glacial Lake Outburst Flood Monitoring in Bhutan

3D view of Lunana region, Bhutan by PRISM DSM and AVNIR-2
acquired on Dec. 26, 2007
Temporal change of area of glacial lake in Bhutan(ha)Bechung

Raphstreng Tso

Thorthormi

Lugge Tsho

1993.12.27

1

127

0

118

1994.11.9

4

130

41

96

2007.12.26

18

126

88

127

* This project is conducted in “Science and Technology Research Partnership for
Sustainable Development” sponsored by JST and JICA.

13

Tropical Rainfall Measuring Mission (TRMM)• Major characteristics– Focused on rainfall observation. First
instantaneous rainfall observation by
three different sensors (PR, TMI,
VIRS). PR, active sensor, can observe
3D structure of rainfall.
– Targeting tropical and subtropicalregion, and chose non-sunsynchronous orbit (inc. angle 35
degree) to observe diurnal variation.

• Major achievement in Japan– Demonstration of high quality and highreliability of a satellite onboard
precipitation radar– Improvement of MWR precipitation
retrieval by PR 3D observation– Pioneering precipitation system
climatology by PR observation– Operational use in NWP etc.
– New products including all-weather
SST, global soil moisture

US-Japan joint
missionJapan: PR, launcher
US: satellite, TMI,
VIRS, CERES, LIS,
operation

Launch28 Nov. 1997 (JST)

Altitude

About 350km (since 2001,
boosted to 402km to extend
mission operation）

Inc. angle

About 35 degree, non-sunsynchronous orbit

Design life

3-year and 2month (still
operating)Instruments

Precipitation Radar (PR)TRMM Microwave Imager(TMI) Visible Infrared Scanner(VIRS)
Lightning Imaging Sensor (LIS)
CERES (not in operation)
14‘Sentinel
earth
observation
activities‘Sentinel Asia’,
Asia’,‘SAFE’‘SAFE’andandJAXA’s
JAXA’searth
observation
activities

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Global Rainfall Map (GSMaP)•

GSMaP (Global Satellite Mapping for
Precipitation) is originally funded by JST/CREST
during 2002-2007, led by Prof. K. Okamoto.
– Development of reliable MWR algorithm consistent
with TRMM/PR and precipitation physical model
developed by using PR (Aonashi et al., 2009).
– Combination of microwave radiometer retrievalswith GEO IR by the moving vector (like CMORPH)
and new Kalman filtering method (Ushio et al.,2009).

•

Near Real Time Global Rainfall Map on
Web

JAXA/EORC began to provide near-real-timeversion data of GSMaP (GSMaP_NRT) about 4hour after observation via. password protected
ftp site since October 2008.
Hourly browse images, kmz files for GoogleEarth,and 24-hour movies are also available from Web
server.

•Cyclone "NARGIS" attacked Myanmar

Global Rainfall Map in near-real-time -- http://sharaku.eorc.jaxa.jp/GSMaP/
15

Monitoring Arctic Ice by AMSR-E

1979

2007

2009

• JAXA’s AMSR-E instrument on the NASA’s Aqua satellite monitors
Arctic ice.
• On September 24, 2007, the Arctic ice measured its smallest since1978, when satellite observation began.
16

Global Change Observation Mission(GCOM)
Main
Mission• Establish and demonstrate the global andlong-term Earth observing system (contribute to GEOSS)• Contribute to improving climate change prediction in concert withclimate model research institutions
GCOM-W

Orbit

GCOM-CType : Sun-synchronous orbit
Altitude : 798 km
Inclination : 98.6 degrees
Local sun time : 10:30±15min

Type : Sun-synchronous orbit
Altitude : 699.6 km
Inclination : 98.2 degrees
Local sun time : 13:30±15min

Satellite overview

Mission life

5 years

Launch vehicle

H2A launch vehicle

Mass

1991kg(AMSR follow-on 340 kg and Sea
Winds 240 kg included)

2093 kg(SGLI 460 kg included)

Instrument• AMSR 2• Global Imager follow-on instrument(SGLI)

Launch (target)

JFY 2011

JFY 2013
17

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Greenhouse Gases Observing Satellite (GOSAT)GOSAT enables global (with 56,000 points) and frequent (at every 3days) monitoring CO2 and CH4 column density. (Launched in Jan 2009)TANSO-CAI(Cloud andAerosol Imager)

TANSO-FTS(Fourier Transform
Spectrometer)

Current Ground-based Observation Points(320pts)
Provided by WMO WDCGG

Increase of Observation Points using
GOSAT (56,000pts)
18

CO2 Column Averaged Dry Air Mole Fraction(Collaboration with ACOS Team)

Processed by Dorit Hammerling
Anna Michalak (University of Michigan)

19

PLANET-C “AKATSUKI”

Venus Climate Orbiter•Observation of climatic phenomenon of Venus•Contribute to solve the origin of the earth and climate change
20‘Sentinel
earth
observation
activities‘Sentinel Asia’,
Asia’,‘SAFE’‘SAFE’andandJAXA’s
JAXA’searth
observation
activities

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Contents

� Outline of JAXA� JAXA’s Role in Climate Change
Adaptation
� Asia-Pacific Regional Space Agency
Forum (APRSAF)
� Initiatives of APRSAF / Sentinel Asia,
Space Applications for Environment(SAFE)
� Cooperation between JAXA and AIT

21

Asia-Pacific Regional Space Agency Forum◆Established in 1993 after the Asia-Pacific International Space Year Conference (APIC)
in 1992◆Enhance the development of space programs in the Asia-Pacific region and promote
regional cooperation in the field of space technology and its applications.
◆[Participation] Space agencies, related governments, regional and internationalorganizations, institutions responsible for applying space technology.
◆[Organizers] MEXT, JAXA and co-host organizations
Past co-organizers: Government entities of Mongolia, Malaysia, The Republic ofKorea, Thailand, Australia, Indonesia, India, Vietnam“Sentinel Asia”
Disaster Management
Support System

Working Groups

Earth
Observation
WG

Communication
Space
Satellite
Environment
Applications
Utilization
WG
WG

Space
Education
And
Awareness
WG“SAFE”Space Applications
for Environment
STAR“STAR”
Satellite Technology
for the Asia-PacificRegion Program
22

Sentinel Asia
Sentinel Asia is a voluntary initiative led by APRSAF tosupport disaster management activities in the Asia-Pacificregion by applying remote sensing and Web-GIS
technologies.
� Oct 2005: plan to initiate the pilot
project was approved at APRSAF12.
� Feb 2006: Joint Project Team
(JPT) was organized. As of
2010/11, JPT consists of 60
agencies from 24 countries and
10 inn's organizations.
� Step1 (2006-2007): pilot project(completed).

Websitehttps://sentinel.tksc.jaxa.jp/

� Step2 (2008-2012): in progress.
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Framework of Sentinel Asia
Disaster Management
Community

Space Community

APRSAF*
Data Provision

ADRC**
Member Countries

Promotion of Utilization

Sentinel
Asia
Joint Project Team (JPT)Capacity Building

Utilization (User)

Join Project Team consists of total 70
organizations including 60 organizations of 24
countries/region and 10 internationalorganizations as of September 2010

* Asian-PacificRegional
Space Agency Forum** Asian Disaster
Reduction Center

International Community

UN / ESCAP UN / OOSAASEAN AIT etc.
International Cooperation

24
JPT meeting in Manila,
Philippines,
in July 2010

24

Main Activities of Sentinel Asia

•Emergency Observation
accept emergency observation requestfrom JPT and ADRC members•Wildfire Monitoring•Flood Monitoring•Glacier Lake Outburst Flood
Monitoring•Capacity Building and Human
Resource Development

25

Flow of Emergency Observation
IDC

Requesting Organization (RO)ADRC Members
JPT Members

Emergency Observation
RequestEmergency Observation
RequestDisasterOccurrence

ADRC

Analyzed ProductsData Provider
Node (DPN)

Emergency Observation
RequestFeedback
Disaster Information

JAXA
ISRO
GISTDAKARI
NARL

SupportJAXA
Asia Branch(Bangkok)

Data Analysis
Node (DAN)

Sentinel Asia
Step 2 System

SupportDisaster Management Agencies
in Asia

AIT, ADRCCRISP, CAIAG
Own Data
LAPAN, SD/Sri Lanka
MONRE, ICIMOD,
Sri Lanka MoDM, CEA
26‘Sentinel
earth
observation
activities‘Sentinel Asia’,
Asia’,‘SAFE’‘SAFE’andandJAXA’s
JAXA’searth
observation
activities

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November 2010, Thailand
November 2010, Thailand

Satellites contributing to Emergency Observation
JAXA/Japan

PRISM: 2.5m Pan
AVNIR-1: 10m Multi
PALSAR: 10-100m L-Band

ISRO/India

International
Disaster Charter

GISTDA/Thailand
THEOS

ALOS

NARL/Taiwan
FORMOSAT

PAN: 2m
Multi: 15m

Sentinel Asia
Constellation

IRS

LISS-4: 5.8m Pan
LISS-3: 23.5m Multi
AWiFS: 56m Multi

PAN: 2m
MS: 8mKARI/Korea
KOMPSAT-1

EOC: 6.6m
OSMI: 1km
27

Regional Servers to be set up in 2010
(shown in red)
WINDS

28

Flood in Pakistan: ALOS Imagery on 5 Aug. 2010

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ICUS Report 48
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Flood Inundation Map by ICIMOD

30
30

Sentinel Asia Wildfire Monitoring by MODIS

University of Tokyo (Japan)

Satellite observation network
AIT/Univ. of Tokyo(Thailand)
W ildfire L ocation

C orps Location

B ase Location

Map

CRISP (Singapore)
Overlaid Image

Web-GIS
interface
CSIRO (Australia)

Hotspot map of
Asia

31

Bushfires in Victoria, Australia in Feb. 2009
MTSAT Hotspots

MODIS Hotspot

32‘Sentinel
earth
observation
activities‘Sentinel Asia’,
Asia’,‘SAFE’‘SAFE’andandJAXA’s
JAXA’searth
observation
activities

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November 2010, Thailand
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Sentinel Asia Flood Monitoring

33

Precipitation Data
GFAS (Global Flood Alert Sysytem)
Accumulated daily precipitation

GSMaP (Global Satellite Map ofPrecipitation)

Near real-time hourly precipitation
Cyclone ‘NARGIS’ attacked Myanmar in
May 2008
34

MTSAT(Meteorological Satellite) Imagery on GIS

Big Typhoon

35

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ICUS Report 48
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Capacity Building and Human Networking�The 5th Training by JAXA, hosted by MoDM
in Sri Lanka, in February 2010

Human Network
the most fundamental underpinning of the project
The 6th Training by JAXA, hosted by GISTDA
in Thailand, in July 2010

36

Sentinel Asia Success Story (SASS)
Cooperation with Philippines through Creating Hazard
Map using ALOS Data
LAHAR - Mt. Mayon(PHIVOLCS)
Flood - Antique Province(MGB)
Flood - Iloilo City(PAGASA)PCASTRD
DOST

OCD
NDCC

PHIVOLCSNAMRIAMGBPAGASA
37

SAFE (Space Applications for Environment)
Prototyping
DAICHI

TRMM/PR

MTSAT

Aqua/AMSR-E

Terra/MODIS

Vietnam:ForestManagement
Vietnam:
Water Resource
Management
Lao PDR:
ForestManagement
Cambodia:
Water Resource& Agriculture
Sri Lanka:
Risk ofSea Level Rise
Indonesia:
Potential Drought

Social Benefitsin
Asia-Pacific

Water

Weather

Ecosystems

Energ
y

ClimateHealthAgriculture Biodiversity

38‘Sentinel
earth
observation
activities‘Sentinel Asia’,
Asia’,‘SAFE’‘SAFE’andandJAXA’s
JAXA’searth
observation
activities

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November 2010, Thailand
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Framework of SAFE
● The SAFE activities are implemented by issuebased prototyping project teams consisting of
end users, technical supporters, and data andapplication providers.
Prototyping
Executor(user agencies)

Public agencies for the environment that havethe authority to carry out SAFE activities as
official.

Educational agencies can supportthe
prototyping executor regarding technicalaspects

Technical
Supporter

Data &
Application
CreatorSpace related agencies can create
satellite datasets and/or analyzing
tools to support environment
monitoring.

39

SAFE 2nd Workshop

SAFE #2 WS
Held in Sri Lanka on Jun, 2010
As co-host; Coastal Conservation Department
50 participants

4 new proposals were submitted, and 2 out ofthem were approved as SAFE new prototyping.
40

SAFE Prototyping Status
StatusCountry

Theme

SuccessStory

VIETNAM

Integrated water resource management

VIETNAM

Forest monitoring

On Going

CAMBODIA

Water Cycle and Agricultural Activities

New
Proposal

LAO PDR

Forest monitoring and management

INDONESIA

Potential Drought Monitoring

SRI LANKA

Risk of Sea Level Rise on Coastal Zone

PAKISTAN

Monitoring Water Cycle Variations & Assessing Climate
Change Impacts

SRI LANKA

Modeling ocean frontal zones using high resolution satellite
and float data to locate tune fish aggregations

More detailes : http://www.eorc.jaxa.jp/SAFE/index.html
41

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SAFE Prototyping
Integrated Water Resource Managementin Vietnam• Vietnamese National HYDORO-METEOLOGICAL
Service , Ministry of Natural Resources and Environment(NHMS/MONRE) responsible for flood management andMetrological Service in Vietnam. NHMS is trying tostrengthen the precipitation monitoring and reservoirs
management under the Asian Water Cycle Initiative incooperation with Univ. of Tokyo and JAXA.

42

SAFE Prototyping
Forest Management in Vietnam• Vietnamese Forest Protection Department of Ministry ofAgriculture and Rural Development (FPD/MARD)
responsible for Forest Management in Vietnam. FPD has
MODIS receiving station and provides wild fire Hotspots
information to its rural branches. The target of FPD is tostrengthen the forest management by using of MODIS.

43

Contents

� Outline of JAXA� JAXA’s Role in Climate Change
Adaptation
� Asia-Pacific Regional Space Agency
Forum (APRSAF)
� Initiatives of APRSAF / Sentinel Asia,
Space Applications for Environment(SAFE)
� Cooperation between JAXA and AIT‘Sentinel
earth
observation
activities‘Sentinel Asia’,
Asia’,‘SAFE’‘SAFE’andandJAXA’s
JAXA’searth
observation
activities

44

37
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November 2010, Thailand
November 2010, Thailand

Cooperation between JAXA and AIT� Dispatch of faculty members to SET (School ofEngineering and Technology) and GIC (GeoInformatics Center)� ‘Mini-Projects’ and other Capacity Building Programswith GIC� Sentinel Asia and International Disaster Charter withGIC
� WINDS Utilization Experiments (Tele-Education)with SET� QZS monitoring� Others (ADRC Projects etc.)

45

Cooperation with GIC-AIT in Capacity Building� For last 16 years starting from April 1995, JAXA has been
entrusting a responsibility to the Geo-Informatics Center,
Asian Institute of Technology (GIC-AIT) in Bangkok, tocarry out various training programs mainly focusing on RS
and GIS for the Asia-Pacific nations.
� The contents of the training programs were sometimes
changed by the needs of the times. For last several years,
JAXA and GIC-AIT concentrate on the Mini-Projects, aproblem-solving type of training program.
16 year history of JAXA’s
Capacity Building
activities in cooperation
with GIC-AIT

46

Flow of ‘Mini-Projects’Mini-Projects (Real-world problem solving projects)
Call for Proposal
21 proposals from 33
organizations of 12
Asian countries for2010.

Data Analysis
Basic RS/GIS
andApplication
Training

Image processing,modeling

Field Survey
Data collection,
Validation

Selection
Technical andRegional Demands
9 themes wereselected for 2010.

Proposalin
47 May – Aug.

38
38

Mapping, Reports
Open to publicMethodology
ALOS images order

Phase 1
at AIT
4 weeks in
Oct.

Field Survey

Phase 2at eachin Nov. – Dec.
Countries

at AIT
4 weeks in Jan. –Feb.

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

9 Mini-Projects selected for 201016 Participants of 16 Organizations from 9 Countries

1. Bhutan:
Landslide
2. Indonesia: Flood
3. Kyrgystan: Landslide
4. LaoPDR :Drought
5. Nepal: Japanese Encephalitis
6. Pakistan:
Habitat Evaluation of Western
Horned Tragopan
7. Sri Lanka: Flood and Landslide
8. Thailand:
Assessing Impact of Urbanization
48
9. Vietnam:
Coastal Erosion Management

Quasi-Zenith Satellite System (QZSS)QZSSEarth ObservationGPS

The Japanese firstExperimental Navigation
Satellite is scheduled
in Sept, 2010 by H-IIA F18

49

Conclusions
� JAXA aims to contribute to Climate Change Adaptation
and Disaster Management, employing its Earth
Observation Satellites.
� APRSAF is the largest framework for space cooperationin Asia and the Pacific region. APRSAF aims to strengthen
partnerships between space agencies and user agencies.
� APRSAF conducts concrete cooperative activities andinitiatives. The initiatives of APRSAF, such as Sentinel
Asia and SAFE contribute to addressing regional issues,
such as disaster risk reduction, environmental protection
and natural resources management.
� JAXA and AIT cooperate tightly in Capacity Building(Mini-Project etc.), APRSAF, Sentinel Asia and so on.
50‘Sentinel
earth
observation
activities‘Sentinel Asia’,
Asia’,‘SAFE’‘SAFE’andandJAXA’s
JAXA’searth
observation
activities

39
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November 2010, Thailand
November 2010, Thailand

Pleaseour web site !
マスタvisit
タイトルの書式設定

http://www.jaxa.jp/index_e.html
マスタ サブタイトルの書式設定

Thank you for your attention
51©JAXA/NHK©JAXA/NHK

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Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

Role of JSPS Bangkok office for Promoting
Research and Education in Southeast Asia
Assoc. Prof. Dr. Wataru Takeuchi

ROLE OF JSPS BANGKOK OFFICE FORPROMOTING RESEARCH AND
EDUCATION IN SOUTHEAST ASIA
WATARU TAKEUCHI
Director, JSPS Bangkok Office and IIS, The University of Tokyo
wataru@jsps-th.org

41
41

November 2010, Thailand
November 2010, Thailand

42
42

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Role
and
education
in Southeast
AsiaAsia
Role ofof JSPSJSPS Bangkok
Bangkokoffice
officefor
forpromoting
promotingresearchresearchandeducation
in Southeast

43
43

November 2010, Thailand
November 2010, Thailand

44
44

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Role
and
education
in Southeast
AsiaAsia
Role ofof JSPSJSPS Bangkok
Bangkokoffice
officefor
forpromoting
promotingresearchresearchandeducation
in Southeast

45
45

November
2010, Thailand
November 2010,
ThailandNovember 2010, Thailand

46
46

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

Geospatial Planning for Flood Water Retention
Sites to Mitigate Flood and Drought in
Chi River Basin, Thailand
Dr. Nitin Kumar Tripathi

GEOSPATIAL PLANNING FOR FLOOD
WATER RETENTION SITES TO
MITIGATE FLOOD AND DROUGHT IN
CHI RIVER BASIN, THAILAND
NITIN KUMAR TRIPATHI
Director, UNIGIS, Asian Institute of Technology (AIT)
nitinkt@ait.ac.th

Remote Sensing and GIS Based Sustainable Water
Management Modeling in Chi River Basin

Nitin Kumar Tripathi
Asian Institute of Technology
nitinkt@ait.asia

Rationale
Chi basin• Average annual rainfall 1,000-1,400 mm• Average temperature 25.7o - 27.2o• Average relative humidity 66.3-74.1%

Rainy season• May-June under the influence ofmonsoon• August-October under the influenceof typhoon and depression whichcause heavy rain and instantaneous
flooding• The most of devastating floods
occurred in 1978, 1995, 2000 and2001(RID, 2005).

47
47

November 2010, Thailand
November 2010, Thailand

Drainage area: 49,477 km2

Ubonrattana Dam
Lam Pao Dam

Relief map of Chi River basin

� Chi River Basin faces natural
disasters such as floods and droughts,
especially floods almost every year.

� The degree of devastation has
dramatically increased in parallel with the
expansion of affected areas during the past
2-3 years.
� Realizing the problem, Thai
Government has started many projects
such as the use of rubber weirs andconstruction of retention ponds to store
runoff water and floodwater.
Government focus would be on building rubber
weirs and construction of retention ponds tostore runoff water (Source: Bangkok Post,
September 16, 2005)

Objective
To develop a water budget model and plan water
retention infrastructures to reduce the impact of flooding
using integrated hydrological and hydrodynamic models,
remote sensing ,GIS, and Analytical Hierarchy Process
(AHP)

48
48

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Integration of RS, GIS, DEM, hydrologicaland hydrodynamic models for water
resources management

Sustainable water resources management• It is economically, socially, and ecologically sound andmeets the need of present without compromising theability of future generations to meet their own needs• Sustainability depends on economic, environmental,
ecological, social, and physical goals.

Sustainability and technology• Impacts of planning and management of water resources
can be aided by the use of modern processing technology.
• computer-based optimization and simulation models• exploring individual ideas, to test various assumptions,and to understand results of analyses• predict the impacts of possible alternatives• The resources and condition of future generations can beconsidered which depend on the actions today.

Geospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

49
49

November 2010, Thailand
November 2010, Thailand

Thailand’s national economic and social
development plan (NESDP) (2007-2011)• development under the 10th NESDP• follow “the self sufficiency philosophy”• self reliance, self immunity and development balance inall directions• economic, social, and natural resources and environment

Conceptual framework of water resources management for this study

Guidelines on water resources management• increasing water storage capacity• proper water distribution in the basins• water resources development at proper areas• wetland rehabilitation, water drainage improvement• flood prevention in both rural and urban areas

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Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Where to store floodwater?

To develop a model for locating water retention zones
using remote sensing, GIS and Analytical Hierarchy
Process (AHP)

Methodology
2

1

3

Why AHP?
Multicriteria decision making(MCDM) problems

Multiple objective decision making(MODM)
Multiple attribute decision making(MADM)

AHP• simple hierarchical structure• simplicity• sound mathematical basis• widespread usage• ability to measure inconsistency in judgments

Geospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

51
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November 2010, Thailand
November 2010, Thailand

Decision tree to determine the main and subcriteria for suitable water retention zones
Goal

Sub-criteria

Main-criteria

Three principles of AHP

2.Prioritisation• Humans are well capable of evaluating two elements at a time.
• For many criteria; human mind has certain difficulties in dealing.
• Pair-wise comparison approach has used to uncover the relative-importanceamong all decision elements in a multiple attribute• For example; A = 2B ; [B=(1/2)A]• Pair-wise comparison of relative-importance (assign scores by subjectivity)………………..1

aij = wi / wj
 1
w w
A= 2 1 : wn w1

w1 w2
1
:
wn w2

...
...
:::
...

w1 wn w2 wn 

: 

1 

………………..2

Main criteria
Geology

Slope

Soil
drain

Land
use

Relativeweights

Normalized
weights

G

1

1/2

1/4

1/6

1/2

0.062

1.00

S

2

1

1/3

1/4

2

0.127

2.05

SD

4

3

1

1/2

2

0.254

4.10

SC

6

4

2

1

5

0.456

7.36

L

2

1/2

1/2

1/5

1

0.100

1.62

λmax = 5.009; CI = 0.028;

52
52

Salt crust

CR = 0.025 (≤ 0.10)

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48
Three principles of AHP

3.Synthesis• Summation the score of each polygon: Weighted Linear

Combination method
Ri = ∑kwkrik• Normalized total score by the summation of weights of thematic maps
WHPI = (Gw1Gw2i + Sw1Sw2i + SDw1SDw2i + SCw1SCw2i + Lw1Lw2i)/∑W1
w1 = weights of main criteria
w2i = all weights of sub-criteria• Overlay all 5 thematic maps using ArcView; Union tool
• Classify suitability score classes

Results of Objective 1
1) Relative weights

2) AHP-Suitable water retention zones map
Suitability score classes(natural breaks method)
WHPI Ranges Suitability Classes
1.40 - 4.04
Poor
4.04 - 5.40
5.40 - 7.36
7.36 - 11.44

Moderate
Good
ExcellentGeospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

53
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November 2010, Thailand
November 2010, Thailand

Scale 1: 1,000,000(a) AHP-Suitable water retention zones map for two sub-basins(b) Kud Dok reservoir (proposed reservoir’s boundary)(c) Kud Jub reservoir (data from ROI6)

Field verification points of Kud Dok floodwater retention site

1
2

Kud Dokreservoir

3

4

Field verification
10/28/2006

01/04/2007(a)(b)(a) Flood inundation areas in October 2006 for Kud Dok site(b) Interviewing the villagers

Discussions (1) Expert who suggested the scores; and(2) Experts of Regional Office of Irrigation 6

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Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48• 57 existing reservoirs+ 2 reservoirs from
Kud Dok

Kud Jub

To improve the surface model by filling voids in DEM
and calibrating processes for water volume estimation
and analysis of flood inundation areas

Water volume estimation
� Approximation method:
surface area x average water depth� Elevation data from surveying instruments;
costly and take time� Elevation values from Space Shuttle Radar

Topographic Mission (SRTM); 90 m
� DEM data with a 30 m square grid from RTSD;
developed from SRTM and topographical data

Geospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

55
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November 2010, Thailand
November 2010, Thailand

RMSE was 4.257 m
Void patches and spike in 30 m DEM data

Water volume estimation using DEM

Intermediate DEM

Calibrated DEM• Water causes a specular reflection of radar signals.
• Water acts like a mirror with most of the radar signals
reflected away from sensors.
• Most water areas in raw SRTM are voids.

DEM data processing
1) Removal of voidsa)Original DEM
Process in ArcView GISb)Voids filling

Apply a 3x3 window

c)

56
56

Intermediate DEM

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48
Data processing2) Calibration
� Combine Intermediate DEM values with known elevation data at the same
locations� Comparisons of 54 ground referenced points to establish the relationship

Ground reference points with known elevation

� Apply the relationship equation to correct the vertical error

Elevation

Comparison of Field and DEM Elev
210
200
190
180
170
160
150
140
130
120
110
100

Field_Elev
DEM_Elev

0

5

10

15

20

25

30

35

40

45

50

55

60

Station and Referenced Points

Field Elev

Relationship of Field and DEM Elev
210
200
190
180
170
160
150
140
130
120
110
100
100

y = 1.0312x - 7.3137
2

R = 0.9783

110

120

130

140

150

160

170

180

190

200

210

DEM Elev

Calibrated DEM

RMSE was 3.094 m

Water volume estimation

Unit: meter

Unit: meter

Ele. 162 m :base ele.
(a) Field survey surface of Kud Jub

Water level (m)(b) Calibrated DEM surface of Kud Jub
Water volume (MCM)

Original DEM

Calibrated DEM

163.0

-

0.56

Field DEM
0.83

164.0

0.49

2.58

3.46

165.0

0.61

5.88

7.40

166.0

2.55

9.55

11.69

• Average 25% error

Geospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

57
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November 2010, Thailand
November 2010, Thailand

Water Volume
1)

Water level
(m)

Water
volume(MCM)

Surface area
( Mm2 )

140

2.70

1.74

141

4.50

1.80

142

6.31

1.82

143

8.13

1.83

Unit: meter

Kud Dok reservoir

Ele. 139 m :base ele.

------------------------------------------------------------------------------------2)

To simulate the reduction of water levels and floodinundation areas of temporarily storing floodwater in
retention reservoirs

Model selection
Modelforecasting• Purpose of the effort• Amount of data availability• Degree of accuracy� Rainfall-runoff; NAM model� 1-Dimensional unsteady flow, solved
by finite difference – implicit scheme; MIKE11 model� Flood inundation areas; MIKE-GIS model

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Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Hydrological model calibration(NAM model)

1) Hydrological model calibration with discharges•
E6C, E54•
Calibration 1990 – 1999•
Verification 2000 – 2001
2) Hydrological model calibration with water levels•
Year 2000

Results of calibrated parameter
Parameters

WL

E6C

WL

WL

WL

E54
Group 6

Group 1

Group 2

Group 3

Group 4

Group 5

Umax

10

17

20

19

19

20

Lmax

100

240

288

280

288

288

CQOF

0.350

0.350

0.100

0.100

0.100

0.505

CKIF

200

350

200

200

200

200

CK1,2

50

41

50

50

50

50

TOF

0.600

0.658

0.575

0.58

0.575

0.575

TIF

0.100

0.151

0.229

0.230

0.230

0.229

TG

0.01

0.632

0.881

0.881

0.881

0.881

CKBF

1000

1890

1000

1000

1000

1000

Group

Code of sub-basins

1

LF02, LF03, LF04, LF05, LF06

2

LF07, LF08, LF09, LF10, LF11,LF12

3

LF13, LF14, LF15

4

LF16, LF17, LF18, LF19

5

LF20, LF21, LF22, LF23, LF24, LF25

6

LF26, LF27, LF28, LF29

Hydrograph: Calibration (1991)
StationE6CinYear1991

550

ObservedRunoff
SimulatedRunoff

400
350

R2=0.715

Discharge(m^3/s)

Discharge(m^3/s)

500
450

300
250
200
150
100
50
0
Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Jan

Feb

StationE54inYear1991

550
500
450
400
350
300
250
200
150
100
50
0

Mar

ObservedRunoff
SimulatedRunoff

R2=0.819

Apr

Month

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Month

Hydrograph: Verification (2001)
StationE6CinYear2001

500

ObservedRunoff
SimulatedRunoff

450

400

400

350
300

Discharge (m^3/s)

Discharge(m^3/s)

StationE54inYear2001

500

ObservedRunoff
SimulatedRunoff

450

R2=0.714

250
200
150
100

350
300

R2=0.760

250
200
150
100

50

50

0

0
Apr

May

Jun

Jul

Aug

Sep

Oct

Month

Nov

Dec

Jan

Feb

Mar

Apr

May

Geospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

Jun

Jul

Aug

Sep

Oct

Month

Nov

Dec

Jan

Feb

Mar

59
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November 2010, Thailand
November 2010, Thailand

Input data
� Chi river network: x ,y coordinates� Cross sections; 614 cross sections(red = 323, green = 291)
� Discharge data and water level data (1996,2000,2001,2002)
� Lateral flow from NAM hydrological model

Boundary condition
� Upstream: discharges of station E21
� Downstream: water levels of station E20A
� ∆t = 60 seconds

Downstream

Upstream

Calibration
� Return period analysis
� Return Period of station E20A (Qmax)
� Log-Pearson type III distribution

60
60

Return period(year)

Calculated Qmax
(m3/s)

Standard deviation(m3/s)

Measured Qmax
(m3/s)

Year

25

2,922

516

2,706

2001

8

2,046

234

2,105

2002

5

1,724

169

1,756

2000

3

1,390

121

1,336

1996

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

� Calibration in year 2000
� Stages of station: E9, E16A, E1, E8A, E18,forinternal calibration

E16A
E1

E9

E8A

E18

614+000

0+000

Manning, n, Parameter
Station134

Km (from Upstream)
0+000 – 109+100

E9-E16A

109+100 – 183+800

0.038 – 0.035

E16A-E1

183+800 – 250+000

0.035 – 0.030

E1-E8A

250+000 – 293+200

0.030 – 0.033

E8A-E18

293+200 – 470+400

0.033 – 0.030

E18-E20A

470+400 – 614+000

0.025

0.039 – 0.038

Calibration; StationE18inYear 2000
Observed
Simulated

133
132
130

R2=0.824

129
128
127
126
125
124
123
21/5/2000

10/7/2000

29/8/2000

18/10/2000

Date

7/12/2000

26/1/2001

17/3/2001

Water Level (m)Water Level (m)131

1/4/2000

Manning’ n

E21-E9

136
135
134
133
132
131
130
129
128
127
126
125
124
123

Verification; StationE18inYear2001

4/1/2001

Observed
Simulated

R2=0.893

5/21/2001

7/10/2001

8/29/2001

10/18/2001

Date

12/7/2001

1/26/2002

3/17/2002

Results of flood inundation areas

1,724 km2

1,233 km2

Flooding areas from simulation of 15 September 2001 Flooding areas from Radarsat of 15 September 2001

• 491 km2 difference

Geospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

61
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November 2010, Thailand
November 2010, Thailand

Flood alleviation application

Km 305+700

Fifty nine flood
retention storage
reservoirs scenario• 57 existing reservoirs+ 2 reservoirs fromobjective 1

Kud Dok

Kud Jub• Water volume capacities
from calibrated DEM• Diverted discharges throughnatural channels•Total storage capacityof 540 MCM

Results of simulation
1,327 km2

1,272 km2

15/9/2001

Divert discharges 80% of
retention storage capacity(431 MCM)

62
62

15/9/2001

Divert discharges 60% of
retention storage capacity(323 MCM)

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48
Results of simulation (cont)1,545 km2

1,372 km2
15/9/2001

15/9/2001

Divert discharges 20% of
retention storage capacity(108 MCM)

Divert discharges 40% of
retention storage capacity(215 MCM)

Reduction of flood water levels at Km 596+510 (downstream)
Reduction of flood water level (m)Dateinitial storage
20%

initial storage
40%

initial storage
60%

initial storage80%

15/9/2001

0.23

0.18

0.12

0.06

18/9/2001

0.37

0.30

0.19

0.10

Station 596+510 km

Station 596+510 km
124.70124.70124.60

Diversion

124.50

Water level (m)Water level (m)No diversion

No diversion

124.60124.40124.30124.20124.10124.00124.40124.30124.20124.10124.00123.90123.9012/9/2001

13/9/2001

14/9/2001

15/9/2001

16/9/2001

17/9/2001

18/9/2001

19/9/2001

20/9/2001

12/9/2001 13/9/2001 14/9/2001 15/9/2001 16/9/2001 17/9/2001 18/9/2001 19/9/2001 20/9/2001
Date

Date

Divert discharges 80% of
retention storage capacity(431 MCM)

Divert discharges 60% of
retention storage capacity(323 MCM)

Station596+510km
124.70Station596+510km
124.70No diversion

124.60No diversion

124.60

Diversion

Diversion

124.50
Water level (m)124.50
Water level (m)Diversion

124.50124.40124.30124.20124.40124.30124.20124.10124.10124.00124.00123.90123.9012/9/2001 13/9/2001 14/9/2001 15/9/2001 16/9/2001 17/9/2001 18/9/2001 19/9/2001 20/9/2001
Date

12/9/2001 13/9/2001 14/9/2001 15/9/2001 16/9/2001 17/9/2001 18/9/2001 19/9/2001 20/9/2001

Divert discharges 40% of
retention storage capacity(215 MCM)

Geospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

Date

Divert discharges 60% of
retention storage capacity(323 MCM)

63
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November 2010, Thailand
November 2010, Thailand

Irrigable areas from SPOT5 images• Acquired in February 2006
• 2.5 m pixel size, FCC 421

1
2

Kud Dok
Reservoir:
8.13 MCM

Extraction of Irrigable areas

Total Irrigable areas = 4.92 million m2(3,073 Rai)

Kud Dokreservoir• Max. 500 m buffer zone

Scale 1:75,000

Water supply to irrigable areas

No scale64
64

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Conclusions
A model was developed to assess suitable water retention zones
by integrating five parameters such as salt crust, soil drainage,
slope, land use, and geological formation including AHP throughGIS.
The processes of filling voids and calibration in DEM facilitatedwater volume estimation.
The hydrological and hydrodynamic models could satisfactorily
simulate hydrological and hydrodynamic components of the Chi
basin, respectively.
Diverted discharges of 80% retention storage capacities (431
MCM) could reduce flood inundation areas to great extent.

Water is life.
nitinkt@ait.asia

Thank you

Geospatial planning for flood water retention sites to mitigate flood and drought inGeospatialplanning
for flood water retention sites to mitigate flood and drought in
Chi River Basin,
ThailandChi River Basin, Thailand

65
65

November 2010, Thailand

66

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

Development of Tsunami Disaster Mitigation
System Considering the Characteristics of the
Indian Ocean Region
Prof. Kimiro Meguro

ICUS Report 48

DEVELOPMENT OF TSUNAMIDISASTER MITIGATION SYSTEMCONSIDERING THE CHARACTERISTICS
OF THE INDIAN OCEAN REGIONKIMIRO MEGURO
Director, ICUS, IIS, The University of Tokyo
meguro@iis.u-tokyo.ac.jp

Development of Tsunami Disaster
Mitigation System
Considering the Characteristicsof the Indian Ocean Region
Kimiro MEGURO

ICUS

International Center for Urban Safety Engineering
Institute of Industrial Science
The University of Tokyo

What are the real issuesof disaster management？
• Lack of technology? Financial resources?
Adequate Policies? Organization? Education?
• In which order should we tackle them?
• Which could be the trigger for starting avirtuous cycle?

6767

November 2010, Thailand
November 2010, Thailand

What are the real issuesof disaster management？
• Lack of technology? Financial resources?
Adequate Policies? Organization? Education?
• In which order should we tackle them?
• Which could be the trigger for starting avirtuous cycle?

How to tackle future tsunami?

How about recovery and reconstruction
plan, and land use plan?
Following the plan, when people movefrom the beach to inlandby 100 to 200 m in Thailand and Sri-Lanka,
and 2 to 3 km in some parts of Indonesia,
is it possible to maintain their daily life ?
Especially, Fishermen andResort Hotel persons?

各調査相互の関係/Structure of the Study
構造^!"地震断&を
被`ab
対)*+,
津波/0
Damage Survey
シミュレーシ67
of Structures

被災地の
高NO測o

被災fgの
hアリ7k
ア7lートab
Questionnaire＆ Interview
SurveyElevation
SurveyTsunami
津波\]
Simulation
S
Estimation of Tsunami Load
高NOP高and Design of Structures
海9:;お=>海
QーR
津波避難EFの 津波高・AB
位置FJ
住Tの
DE Map
・構造FM
避難U
津波cd
動WX
シミュレーシ67
津波避難EF
Evacuation
Tsunami inundationの$%・位置Behavior
YZ深・AB
Strength and Locationof evacuation facility

!"利
用fの
'"(
)*+

多目rs測tuを用w,
リxートyz{|}TWSの~Proposal of
New TWS

津波 !
の}"#Possibility of Introductionof the Proposed System

津波避難シミュレーシ67

津波避難シミュレータ/Human Evaluation Simulator in Tsunami Disaster

68
68

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Damage Surveyof Structures to Discuss
the Impact due to Tsunami
構造物被害調査
安全な避難施設を実現するために
Structural damage/建物の被害

門柱基部
損傷

Kinniyai

Inundation
heightの計測

Kinniyai
高架水槽の被害
柱鉄筋の抜け出しで全体崩壊

Hambantota
レンガ造

Hambantota
レンガ造

Galle
RC造

逆対称曲げによる柱折損

Development of Tsunami Disaster Mitigation System considering the characteristics ofDevelopmentof Tsunami
the Indian Ocean
RegionDisaster Mitigation System considering the characteristics ofthe Indian Ocean Region

無損傷

69
69

November 2010, Thailand
November 2010, Thailand

屋外トイレの被害
Galle
レンガ造

Nilavelli
レンガ造

無損傷
開口：津波直交方向

転倒による倒壊
開口：津波方向
Kottagoda Belwatte
レンガ造

Hambantota
レンガ造

無損傷
開口：津波直交方向

無損傷
開口：津波直交方向

構造耐力と津波荷重の関係/
Relation between Structural Strength and Tsunami Impact• 割増係数 a と津波高さの実測値 η の関係• Relation between a and Real Tsunami Height η

η
a

10.0

10.0
無被害

損傷

傾斜・崩壊

壁部材

無被害

8.0

傾斜・崩壊

柱部材

8.0
23. 引波時に漂流物の衝突で損傷（ひび割れ）の可能性

Wall Type
6.0

4.0

57. η=9mを仮定

津波高さ η (m)

津波高さ η (m)1

2.0

Column Type57. η=5mを仮定

6.0

1. 15. 16. 漂流物が衝突したものは崩壊したがそれ以外は健全

4.0

2.0
8. 津波→コ

0.0

0.0
0.0

1.0

2.0

3.0

4.0

耐力相当時の津波高さ η '／津波高さ η

5.0

0.0

1.0

2.0

3.0

4.0

5.0

耐力相当時の津波高さ η '／津波高さ η

出典：東大・中埜/after Dr. Y. Nakano

Vulnerability Analysis
by Tsunami Simulation
潜在地震断層を対象とした
津波伝播シミュレーション対策の対象となる
将来の津波を知るために

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スンダ海溝沿いのシナリオ断層(１)～（４）Scenario Faults (1) to (4)
（１）

（２）

（３）
（４）
by Dr. Koshimura, DRI, Kobe

予想津波最大波高（シナリオ１～４
Estimated Maximum Wave Heightby the Scenario Eq. (1 - 4)
シナリオ①
Scenario①

シナリオ②
Scenario②

シナリオ③
Scenario③

シナリオ④
Scenario④[単位：千人, Unit:1000 person]0

死者・行方不明者数
インド洋地震・津波(Dec.26,’04)(Dec.26,’04)
Deaths/MissingsIndian
Ocean
Indian
Ocean
Tsunami

200

400

600

800

1,000

1,200

1,400

Time time event
300 thousands

同シナリオ①
Scenario①
同シナリオ②
Scenario②

Worst Scenario event
1.3 millions

同シナリオ③
Scenario③
同シナリオ④
Scenario④

標高30m以下の沿岸部において4.1m以上の波高に襲われると推定される人口
Estimated Coastal Population (living in the ground level
less than 30m) under wave height more than 4.1m

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the Indian Ocean
RegionDisaster Mitigation System considering the characteristics ofthe Indian Ocean Region

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November 2010, Thailand

Accurate Elevation Survey
for Tsunami Inundationand Human Evacuation
Simulation
被災地の高精度測量
津波浸水や避難行動
シミュレーションのために
Accurate Elevation Survey
リアルタイム・キネマチックGPSとレーザートータルステーションによる高精度測量結果の一例（Galle）

HambantotaとTrincomaleeでも実施
国連大学 ，スリランカ地質調査所，Peradeniya大学，AIT, etc. との協力

IKONOS data
Infrastructure data
and building damage
data from survey

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3次元イメージ/３-D Image
リアルタイム・キネマチックGPSとレーザートータルステーションによる高精度測量結果の一例（Galle）

Interview
and Questionnaire
Survey
被災者へのヒアリング・
アンケート調査
提案システムが受け入れられるか否か
関係者へのインタビュー/Interview Survey
インタビュー対象者
スリランカ/Sri Lanka
Sri Gemunu Beach Resort (PVT) LTD, GalleHotel
Hotel Club Oceanic, Trincomalee
Urban Development Agency, Trincomalee
Secretary of Government Agent, Trincomalee
Minister of Science and Technology
President of Tourist Board of Sri Lanka
タイ/Thailand
Vice Ｇｏｖｅｒｎｏｒ of Phuket
Ｇｏｖｅｒｎｏｒ of Phang-nga
Kamala Beach Hotel
Khao Lak Bay Front Resort
Phatong Merlin Hotel
President of Phuket Aministration Organization

提案に対する反応
反応が良かった関係者
TBS代表
被災していないホテルのマネージャー
反応が良くなかった関係者
プーケット県の副知事
パンガー県の知事（中央政府からの指示待ちの姿勢）
被災したホテルのマネージャー(金がない）

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the Indian Ocean
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November 2010, Thailand
November 2010, Thailand

How to tackle future tsunami?

How about recovery and reconstruction
plan, and land use plan?
Following the plan, when people movefrom the beach to inlandby several km in Indonesia,
100 to 200 m in Thailand and Sri-Lanka,
is it possible to maintain daily life ?
Especially, Fishermen
and Resort Hotel persons?

Proposal ofMulti-Purpose Observation Systemthat can also be used forTsunami Warning

多目的観測ブイを用いた
リゾートホテル主導TWSの提案(a) Concept of TWS
using Multi-Purpose Buoy(b) Networked Multi-Purpose
Buoy System

Newly Proposed TWS
using Multi-Purpose Buoy

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ICUS Report 48

Sample ofdeveloped system

In case that land use control is not feasible as aproper countermeasure against future tsunami,a reliable Tsunami Warning System (TWS) andproper evacuation facilities (EF), built at
appropriate places, considering population
distribution and enough resistance against
tsunami wave load, are indispensable.

Therefore,
1) Combining our proposed TWS and properly distributed
EFs, a new Tsunami Disaster Mitigation System is
proposed.
2) Multi-purpose oceanic observation buoys are used in
our proposed TWS.
3) Optimal location of EFs with enough strength andcapacity is discussed by Tsunami Simulation andEvacuation Simulation in Tsunami Disaster.

1) Combining our proposed TWS and properly distributed EFs,a new Tsunami Disaster Mitigation System is proposed.
2) Multi-purpose oceanic observation buoys are used in our
proposed TWS.
3) Optimal location of EFs with enough strength and capacity is
discussed by Tsunami Simulation and Evacuation Simulationin Tsunami Disaster.

Important characteristics of our proposed TWS are
simplicity,
economical efficiency, anddaily-usability
Without these characteristics, it is very difficult for Indian
Ocean Rim countries with limited resource of technologies,
researchers and experiences of tsunami disasters, comparedto Pacific Ocean Rim countries, to continuously monitor
tsunamis which occur at very low frequency but cause hugedamage.

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the Indian Ocean
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November 2010, Thailand

多目的ブイによる津波警報システム
Multi-purpose observation system
大船渡沖のGPS津波･測位計
日立造船（株）

Tsunami Warning System
Proposed
New TWS

Conventional
TWS

Sophisticated but Expensive and Complicated

Low Cost, Simple, and Daily Useable

Useful for earth-science

The minimum unit of the proposed system
would be one or two multi-purpose
observation buoys operated by one beachsociety, such as hotel resort society or its
network.
temperature, current velocity, wave
height, moisture, etc. on a daily basis

Redundant and easier/cheaper to sustain
Because of more and simpler stations

But, from disaster mitigation
purpose, frequency of use of
the system is very small.
Difficult to maintain the system

With daily usability,

Weather forecast, Safety information,
Break unscientific rumor
Prediction of catch of fish, Fish dude ranch, etc.

Long return period of Tsunami
Limited resources, researchers andbudgetPoor experiences of tsunami disaster
トライトンブイ（海洋観測ブイ）
独立行政法人海洋研究開発機構

Cost of the System/必要経費
10～20 million yen/system
assuming that

Tsunami Tax

・Life time of the system: 3 to 5 years
・ Ave. No. of rooms in each resort beach: 200 to 500
rooms （Pattaya beach：20,000 rooms)
・Ave. No. of days of use of room: 100 to 200 days/year
Cost needed to maintain the system (\yen/room/day)
Cost(mill. yen)Life time(years)100 days

200 days

100 days

200 days

3

167

83

67

33

5

100

50

40

20

3
5

333
200

167
100

133
80

67
40

10
20

Hindu temple

200 rooms/beach

500 rooms/beachBased on survey andtsunami simulation results,
EFs with enough strength
will be built at proper locations＋good maintenancein normal situation

During our field survey, we could observe that temples,churches and shrines are commonly located along thecoastal line. Therefore, we are proposing using similar
community centers as evacuation facilities. At first, weneed to assess the expected wave heights for different
tsunami scenarios and based on the topographicalinformation, choose the appropriate location for thesecenters.

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ICUS Report 48

Hindu temple

Based on survey andtsunami simulation results,
EFs with enough strength
will be built at proper locations＋good maintenancein normal situation

Using worship centers as evacuation centers has two
main advantages. Because they are permanently used by
the people, their location is well known so in case that anevacuation notice is released, everybody can easily
access them. Additionally, because the people feel strong
commitment with these facilities, they take active
participation in their building and maintenance.

Effects of
Various Countermeasuresby
Simulation of Human Evacuationin Tsunami Disaster
避難シミュレーションによる
津波災害対策の効果の評価
想定津波/Scenario Tsunami
中央防災会議想定の南海・東南海連動型地震(by Dr. S. Koshimura)

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the Indian Ocean
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November 2010, Thailand

研究対象地域(尾鷲市)

中領域（領域 B）

大領域（領域 A）

小領域（領域 C）

Study Area:
Owase-City

尾鷲市の津波浸水

Tsunami inundation Simulation (by S. Koshimura)

東南海地震（１９４４）での津波被害/
Past Tsunami Damage due to 1944 Eq.

No. of death/missing: 650
No. of collapsed/washed away: 6000

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ICUS Report 48

道路ネットワークと建物分布
Road Network and Distribution of Structuresin the Study City0

0.5

1.0 km

市内の詳細
Detail mapof the Study City

○広域避難場所: Evacuation Spaces: parks, community centers, and schools

野地町駅前児童公園

福祉保険センター

尾鷲小学校

野地町駅前児童公園

尾鷲市体育文化会館

中電天満荘広場

市立中央公民館

Development of Tsunami Disaster Mitigation System considering the characteristics ofDevelopmentof Tsunami
the Indian Ocean
RegionDisaster Mitigation System considering the characteristics ofthe Indian Ocean Region

中村山公園

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November 2010, Thailand
November 2010, Thailand○密集市街地 Crowded Area, Narrow Streets

予想津波浸水区域

浸水時の避難者速度低下式の導入/
Velocity of the People in Tsunami
水[/water depth（m）

0.7

歩行BOを0と+,0.5

Walking velocity=0

成人男性/male adult

0.3

AB/
water
velocity（m/@）

成人女性/female adult
子供・高齢者/child and elderly
1.5

2.0

2.5

0123水`時の56避難行V（水7歩行）に:;る実験>?

災害情報伝達モデルの導入
Modeling of Disaster Information Communication『災害情報/ Disaster Information』
行政や報道機関などから発信される、津波の来襲を伝える情報#$EF/Occurrence of
Event

気
象
台
・
県

JMA,
Government-.EF/Tsunami③MNOPQ/Speaker

A!TU②②KLCディア/④R!SMass Media/Patrol car
A!伝BCディア/Media for information transmission
ST/
People①#$のG(に>?-.
のHIを予測/Ground Motion80
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ICUS Report 48
ICUS Report 48◇情報伝達パラメータ一覧/ Parameters for Disaster Information Communication
伝達方法①地震の揺れ/Ground Motion②マスメディア
Mass Media③屋外拡声器
Speaker

伝達パラメータ/Parameters

情報取得率

３０ ％

情報放送タイミング

２分後/2mins.

情報放送回数

１ 回

情報取得率

３０ ％

３分後/3mins. 音声到達エリア
内にいる住民/１１ 基
people who
can hear
２００ ｍ

情報放送タイミング
配置数
音声情報到達範囲
情報取得率

④広報車/
Patrol Car

対象
対象空間内の全住民/ all thepeople in thearea
対象空間内の全住民/ all thepeople in thearea

１ 分後/1min.

情報発信タイミング
start time

３０ ％５分後/5mins. 音声到達エリア
内にいる住民/２ 台
people who
can hear
２０ ｋｍ/ｈｒ

発車タイミング
台数
移動速度
音声情報到達範囲

１００ ｍ

情報取得率
３０ ％
今回の解析で変化させたパラメータ/ Parameters used for Study◇屋外拡声器による情報伝達/
Information Dissemination by Speakers
対象者：音声到達エリア内の部分＝音声到達エリア
Area where people can get information

屋外拡声器/Speakerｄｄ：音声到達半径/ 200m◇広報車による情報伝達/

対象者：音声到達エリア内

Information Dissemination by Patrol Carsの部分＝音声到達エリア
Area people can get informationｔ = Ｔ+2 T

ｔ = Ｔ+ Tｄ’ｔ=Ｔｄ’ ：音声到達半径/
広報車/
Patrol Car

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the Indian Ocean
RegionDisaster Mitigation System considering the characteristics ofthe Indian Ocean Region

Radius/ 100 m

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November 2010, Thailand
November 2010, Thailand◇避難行動シミュレーション◇
Human Evacuation Simulation

避難行動シミュレーション
Human Evacuation Simulation

検討項目/ Discussion Points①情報伝達の遅れが避難安全性へ及ぼす影響の評価
Effect by Delay of Information Dissemination②津波避難ビルの効果の検証
Effects of Evacuation Buildings/Towers/Centers③道路閉塞が避難安全性へ及ぼす影響の評価
Effects of Road Blockage by Collapsed Structures

避難行動開始時刻の決定/ Starting Time of Evacuation
Time for getting info.

避難開始時刻 ＝ 情報取得時刻 ＋ 避難準備時間
Starting Time of Evacuation
Time for Evacuation Preparation

A!伝BCディiによりe`A!をTU+,4V
Case 1:
By Government / Mass Media→行政の(応により変Z;る

避D行Vの[\]定や避Dの際の準備4b
Case ２: By People

人
数
（
人
）

→STの(応により変Z;るcdeμ： ●（分9標準hiσ ： 1（分9のjk分布でnoる
cde

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ICUS Report 48①情報伝達の遅れが避難安全性へ及ぼす影響の評価○シミュレーションケースの概要
情報取得$→ 50% 30%

Case 1:

情報伝達開)*刻（分.
10%

広報9/PTC

上;</Max

1

3

5

7

15

1

5

10

15

20

1

10

15

20

25

/0/Eq

情 遅れ?し /No delay
報
少し遅れ /Small delay伝
達 大遅れ /large delay

マス34/M.M 拡67/Spk＊避難準備時間を0分、5分、10分、15分と変化させた

地震
発生

5分

10分

15分

遅(rし

20分

25分

(min)

全員が避難開始/All people start evacuation/No delay

少し遅れ

全員が避難開始/Small delay

大遅れ

全員が避難開始/large delay①シミュレーション結果（情報伝達の影響）
Effect by Delay ofInformation Dissemination
CD準a4間 １tg

A!伝達の遅(rし/No delay

避難場所

屋外拡声器

情報未取得者

音声到達エリア

情報取得者

広報車

避難中

広報車ルートA!伝達の少しの遅れ/Small delay①人的被害の推移（情報伝達の影響）
Effect by Delay of Information Dissemination
情報取得$D50％
Information Receiving ratio
人 1800的
被 1600害 1400者 1200数（ 1000人） 800

Government/
行政対応

600
400
200
0
People/1
住Tの対応 0S3
v遅(/L delay
S2
少しの遅(/S delay
2
5

3
10

S1
遅(rし/No delay4
15

CD準a4間（g9/ Time for Evacuation Preparation

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November 2010, Thailand
November 2010, Thailand①人的被害の推移（情報伝達の影響）
Effect by Delay of Information Dissemination!"得$：30％
Information Receiving ratio
人 1800的
被 1600害 1400者 1200数（ 1000人） 800

Government/
行政対応

600
400
200
0
People/

更にq(る
S3
vq(
/L delayS2
少しq(る少しGq(/S delay

1
住TG対応 0

2
5

3
10

S1
q(rし
q(rし/No delay4
15

CD`a4b（g9/ Time for Evacuation Preparation①人的被害の推移（情報伝達の影響）
Effect by Delay of Information Dissemination!"得$：10％
Information Receiving ratio
人 1800的
被 1600害 1400者 1200数（ 1000人） 800

Government/
行政対応

600
400
200
0
People/vq(/L delay
S3
S2
少しGq(/S delay

1
住TG対応 0

2
5

3
10

S1
q(rし/No delay4
15

CD`a4b（g9/ Time for Evacuation Preparation②津波避難ビルの効果の検証/Effect of Evacuation Buildings
津波避難ビル・・・緊急時にのみ一時避難場所として利用できるビル

xyz
1

2

低層住宅が密集しており、避難ビルとしての候補ビルが限定される

2

提案

2

・安価で経済的・密集地にも設置可能
・多方向から進入可能
避難ビルの選定

Case 1

避難ビルなし/No Eva. Buildg

Case 2

実際に利用されている避難ビル①を利用/Current

Case 3

新提案:一時避難場所②×3を利用/Our Proposal＊情報伝達に遅れなし．

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簡易的な一時避難場所のイメージ図

避難準備時間を変化させた．

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48②避難ビルの効果 /Effect of Evacuation Buildings
CD準a4間 １tg

避難場所

屋外拡声器

1分 3分 5分

情報未取得者

音声到達エリア7分→情報の遅れなし

Ｃａ@} 1 CDビルなし/No Eva. Buildg

情報取得者

広報車

避難中

広報車ルートＣａ@} 3 ~する3ヶ所を利用/Our Proposal②人的被害数の推移(避難ビルの効果)/Effect of Evacuation Buildings
人
的
被
害
者
数
（
人
）

900
800
700
600

人的_`"#$%とんど()できない
Less Effects

500
400
300

Government/行政対応

人的_`"#+()できる
Large Effects

200
100
0

People/住TG対応

S3Case 1 (No Builg)
S2
Case 2 (Curent)

01

52

3
10

S1
Case 3 (Our
Proposal)4

15

CD準a4間（g）/ Time for Evacuation Preparation→補助金助成制度などの新たな政策立案が考えられる③シミュレーション結果(耐震補強の効果)
CD準a4間 １tg

避難場所

屋外拡声器

1分 3分 5分

情報未取得者

音声到達エリア7分→情報の遅れなし

Ｃａ@} 4,-な$震./（4ヶ所./）

情報取得者

広報車

避難中

広報車ルートＣａ@} 501的な$震./（4ヶ所./）

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November 2010, Thailand③人的被害数の推移(耐震補強の効果)/Effect of Road Blockage
Nothing retrofitted

人
的 700
被 600
害
者 500
数
400
（
人
） 300

Effect of Selection ofRetrofitting Locations
All retrofitted

200

Government/
行政対応

100
0

S2
Case 3-1

1
10

82
63
23456-所）/
No. of Road Blockage

44

25

S1
Case 3-206→効果的な耐震化により人的被害軽減が期待できる

ICUS, IIS
Universityof TokyoThank you
Kimiro MEGURO
目黒 89

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Approaches to Identifying the Areas at Risk of
Flood and Drought Over Northeast Thailand
Assoc. Prof. Dr. Charat Mongkolsawat

APPROACHES TO IDENTIFYING THE
AREAS AT RISK OF FLOOD AND
DROUGHT OVER NORTHEASTTHAILANDCHARAT MONGKOLSAWAT
Khon Kaen University
charat@kku.ac.thApproaches to identifying theareas at risk of flood and drought
over Northeast Thailand
Charat Mongkolsawat
Khon Kaen University

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Background� Floods and droughts are annual events inNortheast Thailand yet they are among themost expensive disasters in Thailand.
� Information about the severity, timing andspatial patterns of floods and droughts causes
challenges in providing prevention, relief andrecovery to the disaster-stricken areas.
� Satellite data are alternatives to identify
floods and droughts.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

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November 2010, Thailand
November 2010, Thailand

Objectives
� To explore the recurrent areas of floods using

multi-temporal RADARSAT data and to present
the flood extent as related to sub-basincharacteristics, rainfall pattern and streamhydrology.
� To predict drought-related vegetation stressusing satellite-derived data.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand� Northeast Thailand

Area: 170,000 km2.
Rainfall: 1,000-2,000 mm./year
Forest: Deciduous and Evergreen forests
Topography: Gently undulating terrain
with small hills

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Landform

Mekong ,Chi ,Mun Sub-basins

Elevati on

W ater body and hydrological networks

Geo -i nf ormat ics C ent er fo r t he Dev elo pment o f N ort heast Thai lan d, Facult y o f Sci enc e, K hon K aen Uni versit y, K honK ae n40002 , Th ai la nd88
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� Land use/ Forest

Paddy field

Area
Km2
%
88,428.44
53.93

Field crop

5,939.15

3.54

Sugarcane

5,868.35

3.25

Cassava

8,468.98

5.04

Para rubber

1,711.50

1.07

Evergreen forest

6,233.46

2.96

Deciduous forest

42,616.61

24.46

Riparian forest

4,590.21

2.71

Bush and shrub

157.880.09

Water body

4,709.40

2.88

Sand bar

51.33

0.03

Other

50.03

0.03

Total

168,825.34

100.00Land use type

Source: SPOT (2007) and THEOS (2009)

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Mekong River Basin
Upper Mekong Basin (UMB)
� 18 % of total flow

(China 16% & Myanmar 2%)
Lower Mekong Basin (LMB)
625,000 km2
82 % total flows
� Cambodia – 18%
� Lao PDR– 35%
� Thailand – 18%
� Viet Nam – 11%Upper Mekong gives 18% of annual flow,of that 2% comes from China.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

� Mekong River Is one of the world’s great rivers. It rises in the
Tibetan Plateau flows through 6 countries in its journey over 4,500
km to the South China Sea.

Mekong River Basin• China• Myanmar• Laos• Thailand• Cambodia• Viet Nam

Upper
Basin
Lower
Basin

Discharge: 475 km3 / year
Area: 795,000 km2
Murray-Darling
Discharge: 12.6 km3 / year
Area: 1,073,000 km2

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand89
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November 2010, Thailand
November 2010, Thailand

MRB water resource
Description

China

Mya

Lao

Thai

Cam

V/N

Total

Catchment(Km2 )

165,000

24,000202,000

184,000

155,000

65,000795,000% of Basin

22%

3%

25%

23%

19%

8%

4%

97%

36%

86%

20%

% of country
Average Flow
(m3/s)

2,410

300

5,270

2,560

2,860

1,660

Percentage

16%

2%

35%

18%

18%

11%

15,060Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Variability of Rainfall

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand� Spatial variability of mean annual rainfall

1951-2008 (58 years).

mean annual rainfall(mm.)

and c.v. (%)(15.43)(9.12)(10.06)(9.28)(13.47)(10.91)(14.88)A pattern of increasing the mean rainfall from SW to NE isevident in all of the classes. C.V ranges from 9.1215.43%,although pockets of erratic rainfall is present.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

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� Spatial variability of mean of the first� Spatial variability of mean of the second half
rainy season.

half rainy season.

mean annual
rainfall (mm.)

The first half rainy reveals highvariability in rainfall values in SW
with widely-distributed pocket of
higher values.

The second half rainy season shows
less variability than that of the first.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

� Monthly rainfall variability.
Records of 58 years
370.00320.00270.00cv

220.00mean

170.00SD

120.0070.00
20.00-30.00

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

NOV

DEC

Monthly rainfall during the second peak period
from July to September is higher than the firstpeak period with lowest C.V. in rainy season.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Recurrent areas of flood over the Northeast

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand91
91November 2010, Thailand
November 2010, Thailand

Methodology
� The recurrent flood extent over the Northeast wasestablished, based on the flood events in 2001 2002, 2003,
2004, and 2007 as seen by RADARSAT.
� Based on the sub-basins, we identified the flood area as

related to rainfall, time of concentration, landform, discharge
and return period .

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Acquisition dates of RADARSAT data(C band W mode)

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood areas were interpreted scene by scene
and combined ,covering the entire NE

Flood areas over the sub basins

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

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ICUS Report 48

Geometric

Step 1 : Prepare thesatellite images

correction

RADARSAT data 2001,
2002, 2003, 2004, 2007

Rectified image 2001,
2002, 2003, 2004, 2007

Neural network Classification

Step 2 : Classify flood
extentResult : Flood area each year
Flooded area

Step 3 :Overlay

Overlay all flood area
Reclassification
Recurring flood

Result : Recurring flood
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Cumulative Rainfall� Calculation of the cumulative rainfalls summed

over the preceding 5, 10, 15, 25 and 30 days
prior to imaging Radar by which the acquired
flood extent was performed.
� Establishment of the cumulative rainfall overthe sub-basin areas was made.

�

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Time of concentration (Tc)
� Estimate of the Tc for the sub-basins was

based on:Tc = L1.15 / 7700H0.38
L = length of travel
H = slopeGeo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand93
93

November 2010, Thailand
November 2010, Thailand

Recurrent flood and landform� Overlay of landform map layer on therecurrent sub-basins area of flood was carriedout.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Return period• Gumbel distribution was used to calculate thereturn period(recurrence interval) in subbasins having gauging stations.
• We performed analysis on42 sub-basins,eachof which had 2-4 stations.

Result – The areas of inundation
� The inundation areas accounted for large and recurrent areas
over the downstreams and the confluences of main rivers andtributaries. The flood water stored during the peaks of cumulative
rain was discharged into downstream areas and over spilled thebank, overflowing into the vast extent of lowland and floodplain.

2003

2002

2001

2004

2007

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

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ICUS Report 48

2001

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

2001

In 2001 the large floods occurred in the lower Song
Khram sub basin and many sub basins in the Mekong
and the lower Chi.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

2002

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand95
95

November 2010, Thailand
November 2010, Thailand

2002

The 2002 flooded areas covered extensively inth NE, causing the most serious damages.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

2003

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

2003

The 2003 flood peak occurred over downstream of
the Chi , commonly found in all 5 years studied.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

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ICUS Report 48

2004

The2004 large floods were predominantly river floods,with the mostserious flooding occurring in downstream of Song Khram and Chi.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

2007

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand� Flood areas over the Northeast for 2001, 2002, 2003, 2004 and2007, the largest area of flood occurred in 2002 for the Mun andChi, in 2004 for the Mekong.

Year
2001
2002
2003
2004
2007

Flood area (km2)
4,790.37
8,854.68
3,148.28
4,175.83
4,147.25

Percent
2.84
5.24
1.86
2.47
2.46

Total area of the Northeast = 168,825.34 km2

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand97
97

November 2010, Thailand
November 2010, Thailand

Flood areas of the watershed in 2001-2004, 2007
Km2
9000
8000
3636.61

7000
6000
5000
4000
3000

Mun
1117.123345.87

1863.12907.87

2000
1000

1810.12 1872.2

0
2001

2002

1161.18 1508.73
1321.511323.11917.3
2003

1693.152004

1628.75

Chi
MekongWatershed% of flood
2001

2002

2003

2004

2007

Mekong

37.79

21.14

29.14

40.55

24.35

Chi

38.89

37.79

42.03

31.65

39.27

41.07

28.84

27.81

36.38

1009.77

Mun

23.32

2007

Total

100.00 100.00 100.00 100.00 100.00

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Result - The recurrent flood extent

� The recurrent flood areas for all 4 and 5 years were found at thedownstream and confluences of the main rivers and its tributaries.
� Of the total flooded areas, the recurrent areas accounted for 8.68,
7.46, 10.67, 20.75 and 52.44 % for 5,4,3,2 and 1 year respectively. Most
river floods resulted from rainfall events such as excessively prolonged
rainfall and were intensified
by basin area,shape,slope,
altitude, landuse anddrainage network.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Result - The recurrent flood extent (Cont.)

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

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Result - The recurrent flood extent (Cont.)� The affected villages accounted for 3,820, 1,576, 815, 619 and839 villages for 1 year, 2 year, 3 year, 4 year and 5 years flood
respectively.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Cumulative rainfall and flooded areas
� The mean cumulative rainfall summed over thepreceding imaging exceeding 200 mm is likely tobring about the floods.
� The amount of flood-producing rainfalls reaching
200 mm varied from 15 days to 30 days.
� The prolonged period of rainfall as a result.
� of tropical cyclone/depression usually 2-3 storms
occurring periodically, could intensify theseverity of flood.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Cumulative rainfall of 30 days prior to flood
Increasing rainfall from SE to NE is evident, producing
large floods in the Mekong and Chi.
Flood 2001

July 27, - August 26,

August 3, - September 2,

August 6, - September 5,

August 10, - September 9,

MillimeterAugust 13, - September 12, September 13, - October 13, September 14, - October 14, September 20, - October 20,

0-100
100-200
200-300
300-400
400-500
500-600
600-700
700-800
800-900
900-1000
1000-1100
1100-1200

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand99
99

November 2010, Thailand
November 2010, Thailand

Cumulative rainfall of 30 days prior to flooding
Flood-producing rainfalls are exceptional ,resulting in large flood
over the entire NE
Millimeter

Flood 2002

September 6, - October 6,

September 8, - October 8,

September 23, - October 23,

September 30, - October 30,

September 9, - October 9,

October 3, - November 2,0-100
100-200
200-300
300-400
400-500
500-600
600-700
700-800
800-900
900-1000
1000-1100
1100-1200

September 18, - October 18,

October 9, - November 8,

October 12, - November 11,

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Cumulative rainfall of 30 days prior to flood
Millimeter

Flood 2003

August 3, - September 2,

September 3, - October 3,

September 10, - October 10,

September 20, - October 20, September 25, - October 25, September 27, - October 27,

0-100
100-200
200-300
300-400
400-500
500-600
600-700
700-800
800-900
900-1000
1000-1100
1100-1200

September 13, - October 13,

October 2, - November 1,

October 4, - November 3,

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Cumulative rainfall of 30 days prior to flood
Large floods occurred during the period of Sept 10-20
Flood 2004

August 11, - September 10,

August 12, - September 11,

August 19, - September 18,

August 21, - September 20,

Millimeter

September 12, - October 12,

September 19, - October 19,

September 26, - October 26,

0-100
100-200
200-300
300-400
400-500
500-600
600-700
700-800
800-900
900-1000
1000-1100
1100-1200

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

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Mean of cumulative rain of 30 days before flood
Millimeter

332.08350

Cumulative Rain

300
250

231.95237.93228.25

2003

2004

200
150
100
50
0
2001

2002

The magnitude of the 2002 rainfall exceeded
those of the 2001,2003 and 2004,causing themost serious floods.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Landform and recurrent flood areas� About 75% of the Flood areas occurred over the flood plain and low

terrace. The rest was found over the low lying areas of the middle. terrace.
Flood plain
Low terrace
Middle terrace
High terrace
Dissected erosion surface
Mountain
Water
Recurrent flood 1 year
Recurrent flood 2 year
Recurrent flood 3 year
Recurrent flood 4 year
Recurrent flood 5 year

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Time of Concentration (TC-day)Sub-basins in Northeast Thailand

Mekong

0-1
1-2
2-3
3-4
4-5
5-8
>8

Water bodyTime of Concentration(TC-day)
0-1
1-2
2-3
3-4
4-5
5-8
>8

Of the total sub-basins, the sub-basins with highTc in the Mekong,Chi and Mun were identified.

TC(day)Chi

TC(day)
0-1
1-2
2-3
3-4
4-5
5-8
>8

Mun

TC(day)
0-1
1-2
2-3
3-4
4-5
5-8
>8

No. of
Percent
watershed
9
32.14
13
46.43
1
3.57
0
0.00
2
7.14
1
3.57
2
7.14
No. of
Percent
watershed
11
55.00
6
30.00
1
5.00
0
0.00
1
5.00
1
5.00
0
0.00
No. of
Percent
watershed
7
22.58
17
54.84
3
9.68
2
6.45
0
0.00
1
3.23
1
3.22

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand101
101

November 2010, Thailand
November 2010, Thailandหัวเรื่ องเพิ่มเติมเนื ้ อหา

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

The recurrent sub-basins of floods in all years
Discharge and return period
Sub basin

StationMekongHuai luang

2001
(1)
(2)

2002
(1)
(2)

2003
(1)
(2)

2004
(1)
(2)

Kh.53

21.80

1

151.90

35

12.00

1

4.00

1

Upper part of songkhram river

Kh.74
Kh.93

245.60130.002
1467.00177.907
2

326.60122.303
1287.0074.40

2
1

Lower part of songkhram river

Kh.28A
Kh.58A
Kh.77A
Kh.78

398.20666.60
26.8
0.00

2
3
1
-

250.40683.70
33.70
-

2
3
1
1

356.30
24.20
32.60

2
1
1

-

-

Fourth part of chi river

E.1
E.18
E.8A

649.601,890.00
519.1031031,340.00
1,512.00
1,330.00

20
6
35

809.20924.00746.105
3-398.901,126.20-

2
4-

Yang river

E.54
E.57
E..70

186.4030.10
300.801
1
1410.0038.30
603.904
1
6

228.4016.00
503.201
1
3276.8014.08
365.84

2
1
1
4

Chi

Chi
Pa SakMun
MekongLower part of chi river
Mun
Second part of mun river

E.20A

2,690.00

14

2,009.00

6

1,493.10

3

1,717.50

M.104

141.802

408.20

4

-

-

-

-

Third part of mun river

M.5
M.7

857.004,692.00272,005.00
5,500.00

6
12

897.502,770.00

4
3

1,162.00
2,813.00

3

Lam sa bai

M.155
M.179

56.50
-

1
-

30.80
975.001
4

33.60
632.201
2

28.70
396.20

1
1

1 = Discharge ()2 = Return period (year)
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Discharge and return period

Chi
Pa SakMun
MekongStationEquation

R2

Kh.28Ay = 356.7ln(x) + 95.04

R² = 0.939

Return period
2

5

10

25

50

342.29669.13916.371,243.21

1,490.46

Kh.53

y = 39.47ln(x) + 12.10

R² = 0.958

39.46

75.62

102.98139.15

166.51

Kh.58Ay = 421.4ln(x) + 173.0

R² = 0.913

465.09851.22

1,143.31

1,529.43

1,821.53

Kh.74

y = 164.1ln(x) + 154.9

R² = 0.966

268.65419.01532.75683.12796.86

Kh.77Ay = 83.76ln(x) + 47.44

R² = 0.807

105.50182.25240.30317.05375.11

Kh.78

y = 60.77ln(x) + 8.617

R² = 0.943

50.74

106.42148.55204.23

246.35Kh.92

y = 241.6ln(x) + 214.4

R² = 0.862

381.86603.24770.70992.08

1,159.54

Kh.93

y = 178.7ln(x) + 62.12

R² = 0.946

185.99349.73473.59637.33761.20E.1

y = 382.1ln(x) + 205.4

R² = 0.975

470.25820.37

1,085.22

1,435.33

1,700.18

E.8A

y = 308.2ln(x) + 232.7

R² = 0.969

446.33728.73

942.36

1,224.76

1,438.39

E.18

y = 726.7ln(x) + 184.2

R² = 0.871

687.91

1,353.78

1,857.49

2,523.36

3,027.07

E.54

y = 188.6ln(x) + 165.2

R² = 0.774

295.93468.74599.47772.28903.01

E.57

y = 58.34ln(x) + 28.78

R² = 0.984

69.22

122.67163.11216.57257.01E.70

y = 155.2ln(x) + 322.5

R² = 0.897

430.08572.28679.86822.07929.65

E.20A

y = 835.8ln(x) + 490.2

R² = 0.967

1,069.53

1,835.37

2,414.70

3,180.54

3,759.87

M.104

y = 276.8ln(x) + 5.21

R² = 0.921

197.07450.70642.57896.191,088.06

R² = 0.969

976.35

1,831.71

2,478.76

3,334.12

3,981.17

M.7

y = 1812.ln(x) + 1066.

R² = 0.884

2,321.98

3,982.30

5,238.28

6,898.60

8,154.59

M.155

M.5

y = 81.15ln(x) + 42.95

y = 933.5ln(x) + 329.3

R² = 0.918

99.20

173.56229.80304.16360.41

M.179

y = 592.7ln(x) + 159.5

R² = 0.953

570.33

1,113.41

1,524.24

2,067.33

2,478.16

Y=discharge, x=return period

102
102

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Recent�flood�in�NE�Thailand

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

04Sept201009Sept 2010
12Sept 2010
19Sept 2010
21Sept 2010
26 Sept2010
28Sept 2010
29Sept 201003Oct201006Oct201007Oct201016Oct201020Oct2010
22Oct2010
23Oct2010
26Oct201027Oct2010

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood�plain�NE�Thailand

Flood�plain�River

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches toanddrought
overNortheast
ThailandApproaches
toidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand103
103

November 2010, Thailand
November 2010, Thailand

Flood plain + Flood area 2010

Flood plain
Flood area 2010
River
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood plain + Low Terrace

Flood plain
Low TerraceRiver
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood plain + Low Terrace + Flood area 2010

Flood plain
Flood area 2010
Low TerraceRiver
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

104
104

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Flood plain + Low Terrace + Flood area 2010 + Villages

Flood plain
Flood area 2010
Low Terrace
point survey floodRiver
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood plain NE Thailand

Flood plainRiver

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Nakhonratchasima province

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand105
105

November 2010, Thailand
November 2010, Thailand

Flood plain

Flood plainRiver

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood plain + Flood area 2010

Flood plain
Flood area 2010
River
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood plain + Low terrace

Flood plain
Low TerraceRiver
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

106
106

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Flood plain + Low terrace + Flood area 2010

Flood plain
Flood area 2010
Low TerraceRiver
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood area 2010 and landform

Flood plain
Flood area 2010
Low Terrace
point survey floodRiver
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood plain + Low terrace + Flood area 2010 + point survey flood

1
2
3

4

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand107107

November 2010, Thailand
November 2010, Thailand

Example of point survey flood
Point survey
Pictures1

48 Q 257571 1698497
Ban Tang Yang, Moo 11, Tambon Chum Phuang, Amphoe Chum Phuang

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Example of point survey flood (Cont.)
Point survey
Pictures2

48 Q 218107 1677667
Amphoe Phimai

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Example of point survey flood (Cont.)
Point survey
Pictures3

48 Q 192229 1621505
Ban Bueng Thai, Moo 8, Tambon Ta Lad Kaow, Amphoe Chok Chai

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

108
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Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Example of point survey flood (Cont.)
Point survey
Pictures

4

48 Q 137529 1646131
Ban Non Na, Moo 8, Tambon Lad Bua Kaow, Amphoe Sikhio

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Drought NE Thailand

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

MethodData source:� Rainfall data over 70 stations in Northeast Thailandof 8 years (2001-2008).
� Multitemporal Terra-Modis data of the 16 daycomposite image data at 250 m resolution during theperiod 2001-2008 and 2010 available from
WIST (https://wist.echo.nasa.gov)

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand109
109

November 2010, Thailand
November 2010, Thailand

Method (Cont.)
Rainfall Analysis:
� Mean annual rainfall, mean 16 days rainfall and theirstandard deviations for 8 years record were analyzed at
the entire stations.
� The cumulative rainfalls summed over the preceding
months and its slope gradient for each year.
� Spatial interpolation of mean annual rainfall for 8

years performed using Inverse Distance Weighted
method.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Method (Cont.)

� Based on relationship between rainfall and satellite

derived-indices.
� Satellite-derived indices
NDVI, NDWI and NDDI
� Comparison of the changes in NDVI and NDWI
values of pairs of images for different dates.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Method (Cont.)
Satellite derived indices:
The Normalized Difference Vegetation Index

NDVI = (ρNIR - ρRed) / (ρNIR + ρRed)
Where ρNIR and ρRed are the reflectance values at 0.857 μm and 0.645 μm, respectively

The Normalized Difference Water Index

NDWI = (ρNIR - ρSWIR) / (ρNIR + ρSWIR)
Where ρNIR and ρSWIR are the reflectance values at 0.857 μm and 1.65 μm, respectively

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

110
110

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48

Method (Cont.)
Satellite derived indices:
The Normalized Difference Drought Index

NDDI = (NDVI - NDWI) / (NDVI + NDWI)Where NDVI = The Normalized Difference Vegetation Index
NDWI = The Normalized Difference Water Index(Proposed by Gu et al 2007)

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Method (Cont.)
� Comparison of the changes in NDVI and NDWI
values of pairs of images for different dates. Phenology
of vegetation provides information on the spatiotemporal pattern of drought.
� dNDVI = NDVI1 - NDVI2
� dNDWI = NDWI1 - NDWI2
� The step of SD from the mean dNDVI or dNDWI
determines the magnitude of the change.
� -1SD to 1SD = no change� The severity of drought can be derived from the SD
step, the greater SD step the higher change.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Spatial Variability of Rainfall:
-3SD

-2SD

Results

X = 1,442.09
SD = 428.27
-1SD

+1SD

+2SD

+3SD

2001

2002

2003

2004

2005

2006

2007

2008

2001-2008

� The difference in spatial rainfall is shown by thestep of standard deviation.
� A board pattern of increasing rainfall fromsouthwest to northeast is evident.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand111
111

November
2010, Thailand
November 2010,
ThailandNovember 2010, Thailand

Results
Results (Cont.)(Cont.)
Temporal
Variability:
Temporal Variability:Show relationshiprelationship� Show
betweencumulative
between cumulative
rainfalland NDVI
rainfall and
NDVI
NDWI andand NDDI
NDDI
NDWI
values cover.
cover.
valuesGeo-informatics
Center forfor thethe Development
Development ofof Northeast
Northeast Thailand,
Thailand, Faculty
40002, Thailand
Geo-informatics Center
Faculty ofof Science,
Science, Khon
Khon Kaen
Kaen University,
University, Khon
Khon Kaen
Kaen 40002,
ThailandResults
Results (Cont.)(Cont.)
0.80

2001-2008
0.70
0.60

NDVI
NDWI
NDDI
SD

0.50
0.40
0.30
0.20
0.10

116
17 J
J -1
F
217
18 F
F5M
621
22 M
M
-7
A
72
23 2A
A9M 8M
-2
4M
25
M
-9
10 J
-2
26 5J
J11
12 J
-2
2 8 7J
J -1
2
13 A
-2
2 9 8A
A13
14 S
-2
30 9S
S15
16 O
-3
1O
11
1 7 6N
N2D
318
19 D
-3
1D

0.00


high NDVINDVI andand NDWINDWI values
values areare strongly
strongly
� The
The high
correlatedwith thegreenness ofof thethe areas
areas inin contrary
contrarycorrelated withthe greenness
to
NDDI value.
value.
to thethe NDDI
of NDDI
NDDI values
values occurs
occurs during
during thethe dry
dry period.
period.
� Increase
Increase of
Geo-informatics
Center forfor thethe Development
Development ofof Northeast
Northeast Thailand,
Thailand, Faculty
40002, Thailand
Geo-informatics Center
Faculty ofof Science,
Science, Khon
Khon Kaen
Kaen University,
University, Khon
Khon Kaen
Kaen 40002,
ThailandResults(Cont.)
Results (Cont.)
Drought
Drought
identification
identificationforthe dry
for thedry
periodof 20102010
period ofthe meanmean values
values ofof NDVI,
NDVI, NDWINDWI andand NDDI
NDDI thethe� WithWith thedrought severity
drought
severity forfor thethe yearyear 20102010 cancan bebe identified.
identified.
� No
No distinction
distinction ofof NDVINDVI values
values with
with increasing
increasing orordecreasing water
decreasingwater content
content can
can bebe observed.
observed.
� Greater
Greater response
response toto drought
drought isis remarkably
remarkably identified
identified byby
NDWI andand NDDI
NDDI values.
values.
NDWI� NDDI
NDDI values
values areare moremore sensitive
sensitive andand evident
evident forfor drought
drought
identification as
identification
as aa result
result ofof greenness
greenness andand waterwater content.
content.
Geo-informatics
Center forfor thethe Development
Development ofof Northeast
Northeast Thailand,
Thailand, Faculty
Faculty ofof Science,
Science, Khon
Khon Kaen
Kaen University,
University, Khon
Khon Kaen
Kaen 40002,
40002, Thailand
ThailandGeo-informatics Center

112
112

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48
Spatial NDVI over the Northeast� The onset of greenness increases with increasing NDVI value
occuring in May.
� The NDVI value response to rainfall is remarkably identified
by the slope and reaches maximum in October.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Spatial NDWI over the Northeast� The NDWI value response to rainfall is similar to the NDVI but

the NDWI is more sensitive to water content than the NDVI.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Spatial NDDI over the Northeast� When the area is dried out the NDDI value is increased. The
NDDI value is more sensitive than the NDVI-NDWI difference.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand113
113

November 2010, Thailand
November 2010, Thailand
NDVI

Spatial NDVI over the Northeast

Spatio-temporal NDVI for the years 2001-2008 and 2010
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

NDWI

Spatial NDWI over the Northeast

Spatio-temporal NDWI for the years 2001-2008 and 2010
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Spatial NDDI over the Northeast

Spatio-temporal NDDI for the years 2001-2008 and 2010
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

114
114

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

ICUS Report 48
ICUS Report 48
NDVI/ NDWI images differencing and their associated histograms of the changes

� The NDVI value is substantially sensitive to vegetation cover
but the NDWI is sensitive to both vegetation cover and watercontent.
� The severity of the change can be derived from the SD steps,
the greater step the higher changes.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

NDVI/ NDWI images differencing and their associated histograms of the changes
NDVI

NDWI

Comparison of pairs of NDVI/ NDWI images differencing and the histograms of thechanges in 2010 and the previous years.

Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Flood

Conclusion

� Flood events in the past over the Northeast were

geographically confined to the lower parts of the Mun, the Chi
and the Mekong as viewed with the Radarsat images of 2001,
2002, 2003, 2004 and 2007.
� The flood in 2010 were exceptional flood which was confinedto the reach upstream of the Mun.
� The study provided insights into cumulative rain-inducing
flood, discharge and return period and the time concentration.
Drought
� Changes in phenological state of different vegetation covers
identify the spatio-temporal pattern of drought.
� With availability and rapid access to satellite data and difficultyin gathering the continuous spatial coverage of climatic data, thesatellite derived indices can be used to monitor the drought
condition for the vast extent.
Geo-informatics Center for the Development of Northeast Thailand, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Approaches
anddrought
overNortheast
ThailandApproaches totoidentifying
identifyingthe
theareas
areasatatrisk
riskofofflood
flood
and
drought
overNortheast
Thailand115
115

November 2010, Thailand
November 2010, Thailand

116
116

Forefront and Challenges of Geospatial Technologies for Environmental andDisaster Management in Southeast Asia

APPENDIX I: BROCHURE

ICUS Report 48

13:00 – 17:30, Saturday, 27th November, 2010
Venue: Jamjuree Ballroom A, Phatumwan Princess Hotel, Bangkok
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Appendix

117

APPENDIX II: SYMPOSIUM PROGRAM

ICUS Report 48

PROGRAM OVERVIEW“Forefront and Challenges of Geospatial Technologies for Environmental
and Disaster Management in Southeast Asia”
Venue:
Date:
13:05-13:10
13:10-13:25
13:20-13:45
13:45 14:15

14:15-14:45
14:45-15:10
15:10-15:30
15:30-16:00

16:00-16:25

16:25-16:55

16:55-17:20

Appendix

Phatumwan Princess Hotel (Jamjuree Ballroom A)
27 November 2010

MC: Akiyuki Kawasaki, Visiting Faculty of AIT and Project Assoc. Prof. of ICUS, IIT, Univ. of Tokyo.
Opening
Overview of space technology development in Thailand
Prof. Dr. Suvit Vibulsresth(National Research Council of Thailand, and member of IAA)
Monitoring, modeling and assessment of urban sustainability
Prof. Yoshifumi Yasuoka(Executive Director, National Institute of Environmental Studies, Japan)
Community-based Climate Centers
Dr. Anond Snidvongs(Director, Southeast Asia START Regional Center (SEA START RC), Chulalongkorn University;
and Acting Executive Director, Geoinformatics and Space Technology Development Agency(GISTDA))'Sentinel Asia', 'SAFE' and JAXA's Earth Observation Activities
Mr. Shinichi Mizumoto(Director, Japan Aerospace Exploration Agency (JAXA), Bangkok office)Role of JSPS Bangkok office for promoting research and education in Southeast Asia
Assoc. Prof. Dr. Wataru Takeuchi(Director, JSPS Bangkok office and IIS, The University of Tokyo)
Coffee Break
Poster display by JAXA, JSPS, ICUS, RNUS
Geospatial planning for flood water retention sites to mitigate flood and drought in Chi River
Basin, Thailand
Dr. Nitin Kumar Tripathi(Director, UNIGIS, Asian Institute of Technology (AIT))Development of Tsunami Disaster Mitigation System considering the characteristics of the
Indian Ocean Region
Prof. Kimiro Meguro(Director, ICUS, IIS, The University of Tokyo)
Approaches to identifying areas at risk of drought and flood over Northeast Thailand
Assoc. Prof. Dr. Charat Mongkolsawat(President, Remote Sensing and GIS Association of Thailand (RESGAT) ,Faculty of Science, Khon Kaen University)
Natural environments in the Mekong River Basin
Prof. Haruo Sawada(ICUS, IIS, The University of Tokyo)

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Suvit Vibulsresth, Dr. Eng.
Affiliation:
Member, National Research Council of Thailand (NRCT)
Brief Career:
Director, Remote Sensing Division, NECT
Secretary-General, NRCT
Deputy Permanent Secretary, Ministry of Science & Technology
Executive Director, GISTDA
Executive Board, GISTDA
Visiting Professor, University of Tokyo
International Contribution:
First Vice Chairman, Committee on the Peaceful Uses of Outer Space, UN
Motto: “Remote Sensing for Mankind”-----------------------------------------------------------------Dr. Suvit graduated Osaka University, and received his Ph.D from the University of Tokyo.

He was a director of

the Department of Remote Sensing on the National Research Council of Thailand, and became the first Director
GISTDA.
Last year, he received the honor of the order of the Rising Sun from the Japanese Government. This honor is theresult of his continuous contribution to establishing friendship and scientific cooperation between Japan and
Thailand, particularly in the field of remote sensing.

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Biography
Dr. Yoshifumi YASUOKA
Executive Director, National Institute for Environmental Studies(Professor Emeritus of the University of Tokyo)
He received the B. Eng., M. Eng. and Ph. D degree in applied physics and mathematics from theUniv. of Tokyo, Japan in 1970, 1972 and 1975 respectively. He was with the National Institute forEnvironmental Studies from 1975 to 1998, serving as researcher, senior researcher and section headin Environmental Information Division. At the NIES last two years he served as a director of theCenter for Global Environmental Research. In 1998 he moved to the University of Tokyo as a
Professor at the Institute of Industrial Science and at the Faculty of Engineering. In 2007 he moved
to the National Institute for Environmental Studies as an Executive Director. He is also a Professor
Emeritus of the University of Tokyo. His major research field is remote sensing, GIS and spatial data
analysis for environment and disaster assessment. He was a president of Japan Remote Sensing
Society since 2002 to 2004.

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Anond Snidvongs, PhD
Affiliation:
AIMES Scientific Steering Committee (Member), START Scientific Steering
Committee (Ex-officio)
Thailand (Member)Research interests:•

Chemical Oceanography , Physical Oceanography , Climatology, Meteorology , Pollution , Limnology ,Chemical Oceanography , Physical Oceanography , Climatology, Meteorology , Pollution , Limnology•

Descriptive oceanography, material transport across continental shelf, material transport and inputs fromdrainage basins, global changes•

Southeast Asia, Gulf of Thailand, South China Sea, Andaman Sea, Northeastern Ind

Academic Societies & Scientific Organizations:
Member, GISTDA Executive Board
Acting Executive Director
Geo-Informatics and Space Technology Development Agency

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Mr. Shinichi Mizumoto
Director of Bangkok Office
Japan Aerospace Exploration Agency (JAXA)
Mr. Shinichi Mizumoto is the Director of Japan Aerospace Exploration Agency(JAXA) Bangkok Office. He promotes international cooperation in space applications
and space technology between JAXA and space or space-related agencies of Asian countries. He also facilitates the
Asia-Pacific Regional Space Agency Forum (APRSAF), the framework for space cooperation in the region andinitiatives of APRSAF such as Sentinel Asia, Space Applications for Environment (SAFE) and STAR Program.
Before the appointment of the Director of JAXA Bangkok Office, Mr. Mizumoto worked for the Ministry of
Education, Culture, Sports, Science and Technology (MEXT) of Japanese Government and promoted Research andDevelopment of Nanotechnology and Material Sciences, Ocean Science and Technology and so on.
Mr. Mizumoto also worked for the Ministry of Economy, Trade and Industry (METI) of Japanese Government andwas in charge of international nuclear energy cooperation and nuclear safety regulations.
Mr. Mizumoto received a Master of Engineering degree in Nuclear Engineering from Kyushu University in 1991.

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Wataru Takeuchi, Ph. D. (Japanese)
Affiliation:
Director, Japan Society for the Promotion of Science (JSPS), Bangkok office
Associate Professor, Institute of Industrial Sciences (IIS), The University of Tokyo
Brief Career:
2004- Postdoctoral fellow, IIS, The University of Tokyo
2005- Research Associate, IIS, The University of Tokyo
2007- Assistant Professor, IIS, The University of Tokyo
2007- 2009 Visiting Assistant Professor, Asian Institute of Technology (AIT), Thailand
2010- Associate Professor, IIS, The University of Tokyo
2010- 2012 Director, JSPS Bangkok office
Research interests:• Remote sensing of environment and disaster• Sensor web• Satellite observation network over Asia
Academic Societies & Scientific Organizations:• American Geophysical Union (AGU)• Remote Sensing Society of Japan (RSSJ)• Japan Society of Photogrammetry and Remote Sensing (JSPRS)Appendix125

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Nitin Kumar Tripathi, PhD
Affiliation:
Coordinator, Remote Sensing and GIS FoS
Director, UNIGIS@AIT Centre
School of Engineering and Technology, Asian Institute of Technology
Brief Career:
1988-1989 Lecturer, MNNIT, Allahabad, India
1989-1999 Asst. Professor, Indian Institute of Technology, Kanpur, India
1999 onwards Assoc. Professor, Asian Institute of Technology
2005 Onwards President, Association of Geoinformation Technology (AgIT)
Research interests:• Disaster Monitoring and Management• Positioning Systems (GNSS, IPS)
• Coastal Zone Planning and Management• HealthGIS
Editor:
Editor-in-Chief, International J. of Geoinformatics (2005 Onwards)
Editor, Chemistry and Environment

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Kimiro Meguro, Dr. Eng.
Affiliation:
Director and Professor, International Center for Urban Safety Engineering (ICUS)
Institute of Industrial Sciences (IIS), The University of Tokyo (UT)
Brief Career:
After receiving his Ph D degree from UT in 1991, Dr. Meguro joined UT’s INCEDE (International Center for
Disaster-Mitigation Engineering) as one of the founding members. Dr. Meguro joined ICUS as an Associate
Professor in 2001 and has become Professor and Director in 2004 and 2007, respectively. From 2010, besides ICUS
Director, he has also become Professor of the Center for Integrated Disaster Information Research (CIDIR) at theInterfaculty Initiative in Information Studies, the University of Tokyo.
Research interests:
Dr. Meguro has wide range of research field in disaster reduction from structural to non-structural measures. As a
specialist of numerical simulation, he has developed several new models by which total behavior of structures
and/or materials from a sound state to a complete discrete state can be simulated. Applying these models, he has
been studying dynamic failure behavior that is highly nonlinear. While in the other field, or as a specialist of
non-structural measures and policy making, he has proposed some important social systems and policies. He has
been working on the human evacuation problems during disaster and he has come out with the idea of a new modelin which large number of people having different characteristics and changes of circumstances of the evacuation
field in case of disaster can be simulated. He is also studying the application of new technologies, like virtual reality,
information technology and/ or GIS/ RS to disaster mitigation issues, for example: Evacuation, Fire-fighting drill,
Risk assessment, Education on disaster, Disaster management manual, etc.

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CHARAT MONGKOLSAWAT DR. Eng
Affiliation‐ Associate Professor
Dept. of Computer Science
Fac. of Science
Khon Kean University (KKU)
Khon Kean, Thailand‐ President
Remote Sensing and GIS Association of Thailand

Brief Career:
1998‐2006, Director, Computer Center, KKU
2001‐2008, Director, Regional Center for Space Technology and Geoinformatics, NE. KKU
2000‐2007, Director, Geoinformatics Center for Development of Northeast Thailand ,KKU
2000‐2004, Member of, Executive board GISTDA

Research Interests:‐ Remote Sensing and GIS for Disaster Management, Land Suitability for Crops.
‐ The Mekong Basin, Northeast Thailand.
‐ Agroecosystem and Ecosystem Diversity.

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Akiyuki Kawasaki, Dr. (Eng.)
Affiliation:- Project Associate Professor, International Center for Urban Safety Engineering (ICUS),
Institute of Industrial Sciences (IIS), The University of Tokyo (UT)
- Visiting Faculty, Water Engineering Management, and Coordinator, Regional
Network Office for Urban Safety, School of Engineering and Technology,
Asian Institute of Technology
Brief Career:
After getting his doctoral degree and working at Yokohama National University, Dr. Kawasaki conducted researchat UT, United Nations University, and at Harvard University.
Dr. Kawasaki has over 13 years of experience utilizing GIS for multidisciplinary environmental research whiledeveloping systematic approaches for integrating a wide range of data models, data formats, and researchmethodologies into a common GIS computing environment. Using GIS as the main tool, he has been conducting
research on both disaster management, such as landslide and earthquake response, and environmental management,such as an integrated approach to evaluate the potential impact of precipitation and land-use change on stream flow.
His current main study area is the Mekong River basin.

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