International Journal for Infonomics (IJI), Volume 5, Issue 3/4, September/December 2012

Proposing Effective Method to Develop Common Operational Picture in
Disaster Response Utilizing Cloud-based Geospatial Infrastructure
Munenari Inoguchi
Research Institute for Natural Hazard &Disaster Recovery, Niigata University, JAPANKeiko Tamura
Risk Management Office,Niigata University, JAPANReo Kimura
School of Human Science and Environment,
University of Hyogo, JAPANHaruo Hayashi
Disaster Prevention Research Institute,
Kyoto University, JAPAN

Abstract

when IT technology application is discussed. Herein,
we explore the issues surrounding the way people
use IT technologies through the activities of theEmergency Mapping Team (EMT), which isdesigned to realize a common operational pictureduring the field disaster response for the 2011 Great
East Japan Earthquake. The challenges and solutionsin information processing are considered in order todevelop an effective disaster response.

The concept of Mashup, which refers to forming a
new service by combining technologies and contentsfrom multiple sources, already exists after Web2.0 in
the field of software development; however, itsconcept was not converted well to social service yet.
After Tohoku Earthquake ministries and agencies inJapan found it necessary to organize the pieces of
information in a geospatial manner in order to takea comprehensive, panoramic view of situations at thesite. We organized the Emergency Mapping Team
(EMT) as to be able to gather and analyze theinformation in the cooperative relationship withgovernment. For example under the serious situationof Fukushima Nuclear accident the EMT organized
the layers of the impacted area including theinformation about indicating the locations ofbuildings, the evacuation situations in areas under
directives to evacuate. Using those layers disaster
responders simulated the necessity of human andmaterial resources to support the evacuation
operation. In this activity, we have stored theoutcomes as spatial layers into the Cloud-based
Spatial Data Infrastructure. After this activity at the
Cabinet Office, we moved our focus to Iwate
Prefecture affected by huge tsunami. Utilizing thisinfrastructure, the responders at Iwate just added thedetail of data which only they gathered through theirdisaster response, and they could develop the COP
in their own view points. In this paper, we discuss
the effective method to develop COP utilizing the
Cloud-based Spatial Data Infrastructure from theview point of all-Japan to the one of limited affectedarea.

1. Introduction
Recent advances in IT technologies, inconjunction with cloud technology, are establishing afoundation for information sharing and information
processing. In spite of this, there is almost no
mention of the way people use these IT technologies

Copyright © 2012, Infonomics Society

2. Activities to Obtain a Common
Operational Picture
2.1. Setting up an Emergency Mapping Team
It is imperative that we share a common
operational picture in order to effectively respond toa disaster. A common operational picture means that
we collect, organize, and analyze information fromvarious organizations to draw a whole picture of"what is happening now" and to share that picturewith stakeholders. Following the 2007 Niigataken
Chuetsu-oki Earthquake, the disaster response
headquarters of municipalities of the Niigata
Prefecture and the City of Kashiwazaki set up an
EMT that uses maps to share a common operational
picture among disaster response workers.
The Great East Japan Earthquake on March 11,
2011, was a widespread disaster spanning many
prefectures that resulted in about 20,000 deaths andmissing people and about 370,000 totally or partiallydestroyed houses and buildings. The government ofJapan faced the task of collecting, organizing, andanalyzing information from various organizations todraw a whole picture of "what is happening now."
This required the consolidation of fragmented pieces
of information obtained through inquiry to variousorganizations, including tables and data formats, into
one dataset. Moreover, each time a piece of criticalinformation that was needed to respond to thedisaster was found to be missing, the government
had to ask the responding organization. In thisinstance, the efforts of the government alone were663

International Journal for Infonomics (IJI), Volume 5, Issue 3/4, September/December 2012

not enough to establish a common operational
picture. It was necessary to have knowledge andtechnology from outside of the government. The
EMT was set up mainly by researchers, private
corporations, and NGOs in response to a requestfrom the Cabinet Office (Disaster Response) on
March 12th (the day after the Great East Japan
Earthquake). The Emergency Mapping Center(EMC) was set up at the Cabinet Office, and it
operated for 48 days until April 28th; it eventually
expanded to include 39 organizations.

2.2. Making a Map by Mashup
Huge amounts of information were collected fromthe afflicted areas. Therefore, it was essential toconsolidate the collected information, sort it
according to its purposes, and convert it into spatial
information. In reality, however, these huge amountsof data were not really organized using a standard
format, since it required each piece of information tobe "organized" during a process from informationcollection to consolidation. It should be noted thatthe activities of the EMT were carried out under theconcept of Mashup. Mashup refers to forming a newservice by combining technologies and contents frommultiple sources. This is a feature that functions as if
it were a single web service and is formed by
combining multiple Application Program Interfaces(API). The EMT collected and organized related
information from the Internet, made the maps neededfor disaster response in GIS, consolidated them into
dynamic maps using the mashup technology over a
cloud application, and then made as many uniquelayers as possible available over the world-wide(Figure 1). Figure 2 shows the top page of the EMT
website. This page is composed of static maps anddynamic maps. The selection of a dynamic map,
which navigates you to a mashup portal site thatallows you to superimpose various information.
Using a dynamic map, you can freely superimpose
information distributed via domestic and foreignsources, in addition to a layer generated by the EMT,
onto one map (Figure 3). Another feature of thiswebsite is that it makes it possible to combine
information collected before and after the disaster.
Emergency Mapping Team

Public informationon the internet

Office of the
Prime
Minister

7
Cabinet Office
Mapping Team

RealityWeb

MashUp1

Utilitycompanies
Mass media

WebsiteSocial media

Service

Preparation

Ministries andlocal
municipalities

・・・

Unpublished informationfrom own organization
1

Recipients of information

Micro
Media

Automotive
navigation
systemCellularphonesFigure 1. The use of mashup by EMT

Copyright © 2012, Infonomics Society

Organizations/People inDisaster impacted Areas

100

Collecting
andarchiving

PDF

Figure2. The EMT website was composed of static
maps and dynamic maps.

Figure 3. Generating a dynamic map based on amashed-up portal. The information gap is filled in bymashing-up spatial information from variousorganizations.

The EMT generated 500 static maps as seen in
Table 1. Each map is a realization of a series ofprocesses from spatial analyses using various
information gathered from maps requested bygovernment
staff.
This
information
wassuperimposed in a process called mashup. Figure 4
depicts a representative map that was generated 11days after the disaster. It shows transportation
centers and evacuation situations in areas under
directives to evacuate or to stay indoors. This map isbased on a hazard scenario of "radioactive
substances have leaked from the Fukushima Nuclear
Plant." Concentric circles are drawn in areas underevacuation advisory and directive, centering on the
XY coordinate of the Fukushima Nuclear Plant. In
addition, point data for companies were used toindicate the locations of their buildings. The actual
number of buildings was calculated bysuperimposing this data using a spatial statisticalmethod. Locations of evacuation centers as well as
the number of evacuees at each center (indicated bynumbers next to circles "○ ") were superimposedwith transportation centers, such as airports andharbors, to aid in the decision-making process

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International Journal for Infonomics (IJI), Volume 5, Issue 3/4, September/December 2012

regarding whether it was necessary to close or moveexisting evacuation centers, or whether to set up new
evacuation centers where goods could be transported.

Table 1. Five hundred maps generated by the EMT
Purpose of map
Hazard observation
information

Number

Total

Observation of radioactivity

63

63

Areas under nuclear plant evacuation advisory and directive

8

Classification of map by visualized contents

Hazard scenario

Estimated damage

Actual damage

Planned power outage by Tokyo Electric Power Company

5

Seismic intensity distribution for each building

1

Building distribution within areas under evacuation advisoryand directive

5

Building distribution in low-altitude areas

33

Isolated people

31

Missing people

38

Injured people

40

Building damage

23

Fires

13

Population and number of households in each municipality

2

Distribution of population age 65 and over8

Facilities that can accept people who require assistance7

Satellite images of disaster areas

2

Relationship between transportation centers andtransportation capability

54

13

At this time, we just thought that we had to sharethose layers with all kinds of responders, and westored the 500 maps into the Cloud-based Spatial
Data Infrastructure. After this activity, the users,
registered to these services as the limited member touse maps and layers, could examine their responsebrowsing the maps and do Mash-up other mapservice or other layers developed by other responders
or other agencies in order to develop the COP atlatest situation.

39

145

Social infrastructure

Resources to consider for long-term evacuation designation
Response policy

Disaster response
results

Resources to consider for specific disaster-afflicted area
designation
Resources to consider for specific disaster-afflicted local
public organizations

1
1
5

Evacuation center provisions

8

Personal safety confirmation

1

Application of rescue methods

9

Application of rescue methods and assistance methods

3

Goods procurement

1

Temporary assistance staff dispatch

25

Utility damage recovery

88

Empty maps to record disaster response results

18

Visualization of the recognition of disasters to the society bytrend leaders
Total

19

61

7

160

500

500

3. Storing Outcomes into Cloud-based
Spatial Data Infrastructure
In order to cut the cost off to collect or to create
the data which are necessary to develop other COPs,
we decided to use the Cloud-based Spatial
Infrastructure as the platform to store the outcomesof EMT at the Cabinet Office. This infrastructure
was composed of three cloud services. First service
is Catalog Service, which enables users to search andselect maps or geo-processing tools from cloudstorage. (Middle of Figure5) Second service is Map
Service, which enables users to obtain the maps andlayers selected by Catalog Service. (Left-side of
Figure5) Third service is Tool Service, whichenables users to execute the geo-processing tools
selected by Catalog services. (Right-side of Figure5)

Copyright © 2012, Infonomics Society

Figure 4. Transportation centers and evacuation
situation in the areas near the Fukushima Nuclear
Power Plant under directives to evacuate or to stayindoors (Enlarged)• Web Browser (Web Application)• Desktop Application• Server• Mobile Application• Smart-phone• Tablet PC④Mash-up③ Obtain Maps

① Request②Obtain Tools

Distributed
Map Serviceson the web
Register

ArcGIS Server

Registeron Amazon EC2
Map Service
Catalog Service
on Amazon Cloudon Esri Cloud（www.amazon.com）（www.arcgis.com）

ArcGIS Explorer Online

Geo-processing Tool Service
on Esri Cloud（explorer.esri.com）

Figure 5. Composition of Cloud-based Spatial Data
Infrastructure665

International Journal for Infonomics (IJI), Volume 5, Issue 3/4, September/December 2012

4. Expanding EMT to Iwate Prefecture
After the activity of EMT at Cabinet Office for
one and half months, we decided to move the activity
post to Iwate Prefecture on June 1st, 2011. Iwate
Prefecture is placed on the northeast area in Japan,
and has the long and zigzag shoreline against Pacific
Ocean, called “Sanriku shoreline”. At the 2011 Great
East Japan Earthquake, this prefecture was attacked
by huge tsunami. By this tsunami, 19,199 buildings
were totally collapsed, 5,013 buildings were halfcollapsed, 4,976 persons were dead, and 1,205
persons were disappeared as of September 28th, 2012.
Local governments under Iwate Prefecture should
respond to those damages soon after huge tsunami
attack. When we established EMT at Iwate
Prefecture, it had passed about two months fromdisaster occurrence, so Iwate Prefecture faced on theissues relevant to the recovery and reconstruction
process. Against this situation, we decided to support
their response by developing COPs. At this time,
fortunately, we had already stored the outcomes into
the Cloud-based Spatial Infrastructure as spatial
layers, and we decided to utilize the stored layers fordeveloping COPs at Iwate Prefecture.

5. Developing COPs at Iwate Prefecture
5.1. Summary of the activity of EMT at Iwate
As described above, the response phase in Iwate
Prefecture had already entered the recovery andreconstruction phase. In this phase, one of mostcritical issue was how to support the residents inemergency temporary houses. Through the activityof EMT at Cabinet Office, we created the base data
about the location and housing-number of emergency
temporary houses collected from the web-site of the
Ministry of Land, Infrastructure, Transport andTourism.
At beginning of the activity of EMT at Iwate
Prefecture, we refine the data of emergency
temporary housings adding the detail data collectedfrom responders in the prefectural government. Then,
we registered this data into the Cloud-based Spatial
Infrastructure as the spatial layer.
After developing the basic data which isnecessary to develop COPs for the responders, wedeveloped 381 types of maps as dynamic maps by
doing Mash-up collected data at the prefecture on thebasic data (Table 2). 156 maps show the efficiency
level of medical services for residents in emergency
temporary housings. 90 maps show the risk oflandslide to emergency temporary houses. 65 maps
shows the efficiency level of welfare and elderly
nursing care services for residents with special needs
in temporary houses. These three categories occupy

Copyright © 2012, Infonomics Society

the majority of COP maps. In the following section,
we describe the detail of those major maps.
Table 2. 381maps were developed by EMT at Iwate
Number ofdeveloped maps

Major category
Medical service

156

Landslide forecast

90

Welfare and elderly nursing care service

65

Social statistics

34

Human and property damage

13

Temporary emergency house11

Evacuation center

11

Background figure

1

Total

381

5.2. Map of Relationship between Emergency
Temporary Houses and Hospitals/Clinics
After the occurrence of big disaster, publicagencies build emerge temporary houses for thevictims who lose their houses by the disaster. Those
temporary houses usually build in the open space
which public agencies own. Most of these open
spaces are stood out of downtown area. After the2011 Great East Japan Earthquake, almost of
emergency temporary houses were also built out ofdowntown area.
Health, Medical Care and Welfare Department of
Iwate Prefecture wanted to examine the sufficiency
level of health, medical care and welfare services forvictims who lived in emergency temporary houses.
As this request, we developed the maps ofrelationship between the emergency temporary
houses and hospitals/clinics as shown Figure 6.
Especially, some of hospitals/clinics were affectedby tsunami and they could not operate. To develop
this map, we had to survey the situation of theiroperation, and to create the data as spatial layers.
Then, by doing Mash-up the situation of
hospitals/clinics services operation with the layer of
emergency temporary houses, we developed this map
to establish COP about the sufficiency level of thoseservices.
Unosumai Area in Kamaishi City

Emergency Temporary Houses(Location and number of residents)

Hospitals / Clinics(Location, Name and Service Type)

Figure 6. Map of Relationship between Emergency
Temporary Houses and Hospitals/Clinics

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International Journal for Infonomics (IJI), Volume 5, Issue 3/4, September/December 2012

6. Discussion
5.3. Map of Relationship between Emergency
Temporary Houses and Landslide Risk
The 2011 Great East Japan Earthquake caused not
only huge tsunami and also ground sinking
liquefaction. So, most emergency temporary houses
were built in mountain area avoiding affected area
along shoreline area. This means those houses face tothe risk of landslide because most slope of mountainarea is steep in Iwate Prefecture.
Against this issue, we developed the maps about
relationship between emergency temporary houses
and high-risk area of landslide (Figure 7). In figure 7,
blue points represent the location and number ofhouseholds in temporary houses, and red polygons
represent the area of steep sloping land. Responders
in the prefectural level estimated the landslide risk toresidents in emergency temporary housings.
However, this map was too severe to be released toresidents despite our suggestion.

Temporary housings
Risk of Steep Sloping Land

Figure 7. Map of Relationship between Emergency
Temporary Houses and Landslide Risk
Because of terrible rainfall on May 4th, 2012,
some of emergency temporary houses were collapsed.
Finally, residents in those collapsed houses had to be
moved for evacuation again. If they had estimatedthe risk of landslide to emergency temporary houses
before they were built, this rainfall disaster should be
avoided. This activity indicated that it wasinsufficient only to develop the maps about theactual situation in order to support victims’ life
reconstruction. Lessons learned from this activity isthat we should develop the maps about the estimatedsituation to avoid new risk in all phase of disastermanagement.

Copyright © 2012, Infonomics Society

In this research, we aimed at establishing theeffective method to develop COP at huge catastrophe
through a case study of 2011 Great East Japan
Earthquake. On the next day of disaster occurrence,
we established Emergency Mapping Team (EMT) at
Cabinet Office in order to support for developing
Common Operational Picture (COP), which isnecessary for responders to make rational decisions
in disaster response.
Because of the features of 2011 Great East Japan
Earthquake,
which
are
“wide-area”
and“complicated”, we had to collect and manage themany kinds of data from many kinds of agencies,
and to develop many kinds of maps. Against thisissue, we decided to develop COPs in two ways; one
is “Static Maps”, second is “Dynamic Maps”.
Especially, dynamic map enables us to do mash-up
flexibly on the web with spatial layers which are
created by EMT and other agencies. Through theactivity of EMT at Cabinet Office, we developed 500
maps for one and half months, and stored outcomesand spatial layers, which maps were composed of,into the Cloud-based Spatial Infrastructure in orderto share those maps and layers with other agencies.
After closing the activity of EMT at Cabinet
Office, we moved our focus to Iwate Prefecture
which is one of affected area by 2011 Great East
Japan Earthquake, and we established the activity
post of EMT at Iwate Prefecture. At this time, their
response phase have already entered recovery andreconstruction phase. Major issue was how to
support the residents in emergency temporary houses.
Against this issue, we developed 381 maps as COP
using layers stored in the Cloud-based Spatial
Infrastructure, and layers owned by local responders.
Usually emergency temporary houses are built in
the public open space where are out of downtown, so
local responders should survey the efficiency level ofservices which are necessary for victims to live their
daily lives. Therefore, we revealed the relationshipbetween the necessary services and thelocation/number of temporary houses visualizing on
the maps. Furthermore, those houses were built inmountain area avoiding affected area in Iwate
Prefecture. However, in mountain area, there wasmuch risk of landslide because of steep land slope. In
order to estimate the possibility of landslide risk toemergency temporary houses, we revealed therelationship between the area of steep land slope andthe location/number of emergency temporary houses.
Unfortunately, about one year after disasteroccurrence, terrible rainfall attacked the area where
emergency temporary houses were built, and some ofthose houses were collapsed by landslide.
Through our case study at 2011 Great East Japan
Earthquake, we proved three issues. One is that it isinsufficient only to develop the maps as Static Maps

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International Journal for Infonomics (IJI), Volume 5, Issue 3/4, September/December 2012

for establishing COPs, and so we should also
develop the maps as Dynamic Maps for establishing
COPs at huge catastrophe. Second is that it iseffective way to use the Cloud-based Spatial Data
Infrastructure in order to store and share maps andlayers among central governments and local
governments. Third is that that it is insufficient only
to visualize the actual situation on maps, and weshould also visualize the estimated situation on maps
in order to support for rational decision makings in
the response to huge catastrophe.
The result of this research is just one case study athuge catastrophe. Therefore, we have not establishedthe standardized effective method to develop COPs
visualizing the situation on maps yet. Against thisissue, we have to analyze the work-flow of
information process in continuing the activity of
EMT. Furthermore, in this research, we have notestablished effective way to manage the spatial
information on cloud-based infrastructure in order tosearch and retrieve critical or effective information
flexibly. We are also planning to continue ourresearch to solve this issue in near future.

[4] Research Center for Natural Hazard & Disaster
Recovery of Niigata University, and Disaster
Prevention Research Institute of Kyoto University,“Emergency Mapping Center in Kashiwazaki
REPORT,” ISBN:978-4-901768-19-1, pp.96, March
2009.
[5] Disaster Prevention Research Institute of Kyoto
University, and Research Center for Natural Hazard &Disaster Recovery of Niigata University, “Emergency
Mapping Center REPORT,” ISBN:978-4-901768-14-6,
pp.130, March 2008.
[6] T. Furuya, R. Kimura, M. Inoguchi, K. Tamura, H.
Hayashi, “Geospatial Information Improves theDecision-Making Process during the Disaster
Response: The Experience of the Emergency Mapping
Team in the 2011 off the Pacific Coast of Tohoku
Earthquake,” Proceedings of 15th World Conference on
Earthquake Engineering, pp.8 (Online), September
2012.

8. Acknowledgements
Authors would like to thank the following fortheir support: (1) Ministry of Education, Culture,
Sports, Science and Technology, Metropolitan
Epicentral Earthquake Disaster Prevention andDisaster Reduction Project, "3. Building System for
Wide-Area Risk Management and Disaster
Reduction (Principal investigator: Haruo Hayashi,
Kyoto University), (2) JST Sakigake "Informationand Environment" field "Establishment ofInformation Consolidation Technology for Prompt
Disaster Response Using a Space (Principal
investigator:
Munenari
Inoguchi,
Niigata
University)," (3) Grant-in-Aid for Young Scientists(Start-up) #22710161, JSPS (Principal investigator:
Munenari Inoguchi, Niigata University).

7. References[1] M. Inoguchi , K. Tamura , T. Furuya ,R. Kimura and H.
Hayashi, “Proposal of Effective On-Demand MashUp
among Spatial Information from the activity ofEmergency Mapping Team - A Case Study of the 2011
off the Pacific Coast of Tohoku Earthquake -,” Journalof Social Safety Science, No. 15, November 2011.
[2] K. Tamura, G. Urakawa, and H. Hayashi, “2007Emergency Mapping Center Constructing Common
Operational Pictures with GIS,” Journal of Disaster
Research, vol. 5, No. 1, pp. 5–11, February 2010.
[3] M. Inoguchi, K. Tamura, S. Tatsuki, and H. Hayashi,“Realization of Effective Disaster Victim Support
through Information Integration and Visualization
using GIS,” Third International Conference on Health
Informatics, pp.381- 387, January 2010.

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