International Journal for Infonomics (IJI), Special Issue Volume 1, Issue 1, 2013

Implementation and Operation of a Cloud-Based Participatory Damage
Recognition System to Obtain a Common Operational Picture that
Supports a Quick Disaster Response
1

Reo Kimura, 2Munenari Inoguchi, 2Keiko Tamura, 3Yuji Nawa, 4Haruo Hayashi
1
University of Hyogo, 2Niigata University, 3ESRI, 4Kyoto University

Abstract
A cloud-based participatory damage recognition
survey system using WEB-GIS was implemented andoperated to collect comprehensive and fundamental
information that could be utilized to generate acommon operational picture, which are essential forthe recovery and reconstruction efforts during
widearea, complex disaster responses. The extent ofdamages due to buildings that were washed away by
the tsunami that occurred during the Great East
Japan (Tohoku) Earthquake of 2011 was captured
using aerial views. The objective of this research was
to develop the cloud-based participatory WEB-GIS
system constructing the common operational picture
in order to facilitate the decision-making process of
disaster response. The team set the research aim tocreate the web service of certifying property damage
due to Tsunami. Using developed service the teamconducted the demonstration experiment to survey toidentify buildings that were washed away in the threeafflicted prefectures of Iwate, Miyagi, andFukushima by Tohoku Earthquake.

1. Introduction

many as 73,500 people were evacuated from thedamaged prefectures (Table 1). Japan defined the
responsibilities of the national and regional
governments during disaster responses in theFundamental Disaster Relief Act, which was
implemented in 1961. The Tohoku Earthquake was ahuge disaster that shook the entire nation (Figure 2).
This disaster inflicted severe human and property

Figure 1. The 2011 Great East Japan (Tohoku) Earthquake
and Tsunami (Mw=9.0)
Noda village, Iwate prefecture, Japan

Table 1. Summary of the impact at the Great East Japan
Earthquake in 2011

High-quality disaster responses cannot beprovided without constructing a common operational
picture (COP) and organic collaboration among
stakeholders. To this end, it is effective to visualize
damages and responses using a Geographic
Information System (GIS), which facilitatesdecision-making based on visualized data. In reality,
however, during the chaotic days immediately
following a disaster, the collection and consolidationof data for visualization is insufficient. The absenceof data to be visualized hinders our efforts toconstruct a common operational picture.

2. 2011 Great East Japan Earthquake
The Great East Japan (Tohoku) Earthquake on
March 11, 2011 generated massive tsunamis thatwashed away many buildings (Figure 1).
Approximately 20,000 people died or went missing,approximately 130,000 buildings were severely
damaged or washed away, and approximately
255,000 buildings sustained somedamages. The amount of direct damages wasestimated to be between 16 and 25 trillion yen andthe amount of debris exceeded 26.7 million tons. As

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Figure 2. Japanese Disaster Management System since
1961

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International Journal for Infonomics (IJI), Special Issue Volume 1, Issue 1, 2013

damages to 3 out of 47 prefectures and 22 prefectures
established disaster response centers.

3. Efficient methods of earthquake andtsunami damage estimation
Our research team initially organized building
point data according to altitude in a geographic space
to create a big picture of damages. We thenestimated the number of damaged buildings in eachregion alongside the height of the tsunamis in theseregions (as reported by the Japan Meteorological
Agency). The results indicated that 270,000
buildings were damaged in three prefectures of
Iwate, Miyagi, and Fukushima. Figure 3 shows theresults of our information analyses, which wereshared with the disaster response workers. Under
ideal circumstances we would have conducted a fieldsurvey to verify the results of our estimate. However,immediately after the earthquake, access to thedisaster area was limited and the survey would havetaken a very long time. These conditions necessitatedthe development of an efficient survey method that
did not require visits to the fields.

number for each survey area (Figure 6). The 13-digit
ID number was composed of a city, ward, or "cho"district code (5 digits), flood area code (4 digits), andsurvey area code for city, ward, and "cho" (4 digits).
This made it easy to visually identify survey areas,
and tally the results according to governmental
jurisdictions.

4.2. Fundamental concepts of design
The following three points were established as
the fundamental concepts of design. These concepts
were determined based on discussions among
information technology and psychology researchers.
The discussions were centered on how to establish amechanism that allowed investigators to intuitively
conduct a survey without being stressed out in acloud-based environment and how to motivate
investigators in physically remote locations byproviding visibility to other workers' progress.

4.1. Aim of the system

4.3.1. Judgment patterns for washed-awaybuildings. Two categories were created for buildingsthat were washed away, either completely washedaway or partially washed away. The purpose of thiswas to make it easy for an investigator to intuitively
make a judgment (Figure 5). Despite our initialdecision to include the unable to determine category
during the development phase of this survey wedecided against this. We were concerned that someinvestigators would categorize ambiguous cases tothe unable to determine category if there was adiscrepancy between the buildings being completely
washed away or partially washed away. The purposeof this survey was to rapidly grasp the big picture ofa wide-area disaster by spending only the minimum
amount of time needed to assess building damage,instead of spending a large amount of time toprecisely evaluate the degree of damage on eachbuilding. For this reason, the survey required
investigators to always categorize all buildings into
the categories of completely washed away orpartially washed away.

The aim was to build a system to enable
participation from anywhere in Japan. This requires agood network environment in order to secure a stablesupply of human resources for the quick and efficient
execution of the survey. Specifically, we designed asystem to determine whether a building was washedaway or not using the WEB-GIS by superimposing
building data before the earthquake (building data)
and aerial views after the earthquake (Figure 4).

4.3.2. Survey areas by roads. We intersected areas
by roads, and each area was assigned a 13-digit ID
number for each survey area (Figure 6). The 13-digit
ID number was composed of a city, ward, or "cho"district code (5 digits), flood area code (4 digits), andsurvey area code for city, ward, and "cho" (4 digits).
This made it easy to visually identify survey areas,
and tally the results according to governmental
jurisdictions.

Figure 3. Estimated number of buildings damaged by
the tsunamis

4. System design

4.3.2. Survey areas by roads. We intersected areas byroads, and each area was assigned a 13-digit ID

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International Journal for Infonomics (IJI), Special Issue Volume 1, Issue 1, 2013

Figure 4. Screen design concept for the washed-away building judgment system using a Web-GIS

Figure 5. Judgment selection for building damage only by clicking

Figure 6. Code system for surveyed areas

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836International Journal for Infonomics (IJI), Special Issue Volume 1, Issue 1, 2013

4.3.3. Progress of the survey to be viewed.
Multiple investigators simultaneously conducted asurvey using the WEB-GIS. We installed a feature tovisualize the overall progress of the survey, which
we hoped would motivate the investigators to
conduct the survey (Figure 7).

5. System configuration

personal computers. This serves as the operating
environment for the personal computer, network
environment, and web application.

6. Project for system verification
6.1. Overview of the project
To clarify issues that may arise while conducting
the survey, in addition to considering an environment
to efficiently and effectively tackle future disasters.
To conduct a survey to identify buildings that were
washed away in the three afflicted prefectures of
Iwate, Miyagi, and Fukushima (excluding areas
affected by a nuclear power plant accident because
no aerial views were available for those areas).
Moreover, to verify the effectiveness of thismechanism to identify buildings that were washedaway using the WEB-GIS.

Figure 7. Tallying function to grasp progress of
survey work

Figure 8. System Configuration
Configuration of the web application distribution
environment involved five components (Figure 8).
1) Cloud Infrastructure. We selected a cloudinfrastructure because it offered flexibility forchanging the basic specifications, the ease of
installation of the environment, and the potential for
multiple accesses.
2) Middleware. We selected a middleware so thatmany people could simultaneously access, edit, andprocess the data over the spatial GIS system.
3) Application. We selected an application thatallows the user to bidirectionally interact with thespatial GIS using a web browser.
4) Administrator of the web application. The
administrator should be able to manage the progressof the survey and conduct a spatial analysis fromtheir local environment, as well as exchange datawith the cloud environment.
5) Investigator. Each investigator should have Flash
Player, which is typically installed on most new

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6.2. Investigators
Undergraduate students, graduate students, andresearchers from five research groups in different
universities were selected to conduct a study related
to disaster prevention and disasters. Two
independent investigators (different research groups)
conducted a survey of the same area to verify anagreement between two survey results. This
verification methodology is based on procedures
used in psychological research studies. Each researchgroup was sent an assignment table (in a Microsoft
Excel format) that contained the names of the areas
to be surveyed, the number of buildings in each area,
and a blank column for names of the investigators.
Each principal investigator (team leader: professor)
was responsible for assigning the required jobs to coinvestigator and managing the progress of thesurvey.

6.3. Instructions
As instruction manual was prepared and isavailable online at all times. The 18-page instruction
manual was prepared mainly by psychology
researchers with assistance from information
technology researchers and system developers. Twomain principles were applied to prepare theinstruction manual: 1. The number of pages should
be kept minimal; and 2. The manual should be laidout according to the workflow (Figure 9).
6.4. Instruction manual
The instruction manual included the following
chapters: Table of Contents
Purpose of This Project837

International Journal for Infonomics (IJI), Special Issue Volume 1, Issue 1, 2013

Chapter 1. Evaluation and Registration of Buildings
Washed Away by the Tsunami
Step 1: Access the URL to login from the screen
Step 2: Display a layer for easy evaluation
Step 3: Evaluate buildings that were washed awayeach survey area and for each building evaluation(Chapter 4). In case you have a concern or doubt,
please ask your team leader instead of making yourown judgment. This is important in order to maintainthe quality of the work."

6.5. Instruction manual
232,906 points were covered in 15,066 areas.
There were 25,905 survey areas that were partitioned
by roads. We subtracted 1,795 areas where surveys
could not be conducted because airplanes could not
fly due to the nuclear plant accident and 9,044 areas
where there were no buildings (survey points); thus,
resulting in 15,066 areas.

7. Results of System verification
Figure 9. Instruction Manual (image)
Step 4: Complete evaluation or logout withoutcompleting the evaluation
Chapter 2. Search
Step 1: Search by area ID
Step 2: Search by city, cho, or village
Chapter 3. Progress
Step 1: Check the progress by survey area
Chapter 4. Tallying
Step 1: Tally the progress status for each survey areaand building evaluation for each building
Step 2: Display the progress status for each survey
area and building evaluation for each building
The four competencies that are required to carryout this project are listed in the "Purpose of This
Project" and are based on the instructional design(ID). ID is a learning theory in psychology andeducational technology, and it refers to the processthat allows the investigators to clearly understandwhat they should learn while participating in thisproject. Users of the instruction manual said, "it iseasy to understand both the big picture of the projectand each job because my workflow is described in
the order that I perform the tasks over a small
number of pages." The following is the actual
statement in the "Purpose of This Project:""Thank you very much for participating in thisproject. This is a disaster relief project involving
multiple investigators to evaluate buildings that were
washed away in disaster areas through shared andcooperative work. We ask that work be performed
according to this manual. This manual is organizedaccording to the following four competencies that are
required to carry out this project: 1. Evaluate andregister buildings that were washed away by tsunami(Chapter 1), 2. Search by area (Chapter 2), 3. Check
progress (Chapter 3), 4. Tally and display progress in

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7.1. Results of concordant analysis
Two investigators belonging to two different
research groups conducted a survey of the same area.
Of the 163,205 points that were evaluated, 90.9%(148,342 points) were classified into the same
category (either completely washed away or partiallywashed away) by the two investigators, and 9.1%
(14,863 points) were evaluated differently-the ratioof agreement was 90.9%. A Pearson's chi-square test
revealed that the ratio of agreement was statisticallysignificant at 0.1% (Χ2(1)=109305.7, p<.001).
Another verification from a different viewpoint(similarity by symmetry) resulted in a Φ coefficientof 0.82, which means that there was a strong positive
correlation at a significance level of 0.1% (Φ=0.82,
p<.001) (Table 2).

7.2. Lack of data and data accuracy
An important issue to keep in mind is that there
were no aerial views of the areas near the Fukushima
Nuclear Power Plants since airplanes were notallowed to fly over these areas. Therefore, a survey
using this method was not possible in these areas.
Differences in the precision of the spatial
information lead to discrepancies between thebuilding information before the earthquake (building
foundation data) and aerial views after theearthquake. In some instances these data
discrepancies made it difficult to distinguish between
a building that was in fact washed away and abuilding that appeared to be washed away.

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International Journal for Infonomics (IJI), Special Issue Volume 1, Issue 1, 2013

Table 2. Result of experimentation by two investigators (A and B)

Figure 10. An Example of area where there was a discrepancy in judgment

Figure 11. Information processing framework to achieve a comprehensive common operational picture

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International Journal for Infonomics (IJI), Special Issue Volume 1, Issue 1, 2013

7.3. Operation management

9. Projected work

There were differences among the five researchgroups in the way the survey was conducted. Somegroups followed the instructions, while others did
not. Comparison of survey results conducted bydifferent investigators revealed areas with a highdegree of agreement and those with a low degree ofagreement. This was likely due to personal bias in
the criteria used by the investigators to makejudgments according to the instructions (Figure 10).

Multiple people judged the effectiveness andviability of the cloud-based participatory WEB-GIS
system to certify building damage due to thetsunamis. Although a web-based system can increase
the participation of investigators, it is often difficult
to guarantee the quality of investigation conducted.
The effectiveness of this system was demonstrated
with the assistance of psychological experiment
methodology. This methodology is also expected tobe effective in improving the reliability andappropriateness of data surveyed by multiple
investigators, rather than being only an experimental
model. In addition to our system functioning as aneffective survey, it was a great achievement for us togenerate a common operational picture among
investigators and stakeholders through the sharing of
the survey process on WEB-GIS. While this system
was configured to be a judgment system, it ispossible to adopt it to a wide variety of surveys
depending on how categories are set for judgment
and selection; therefore, it has promise as a highly
versatile survey system. We aim to build a systemwith an even higher level of viability by solving theissues that we found in the areas of data,
management, and systems.

7.4. System interface
We realized that it was necessary to develop aninterface to minimize human errors in the operation
management. In particular, there was an issue withinvestigator A mistakenly surveying an area that was
assigned to investigator B, which ended up
overwriting the evaluation result of investigator B.
To rectify this issue, we added a link to theassignment management table that allows an area tobe surveyed again and that takes the investigator
automatically to the login screen for the appropriate
survey area. Additionally, it became clear that achecking mechanism, using information such as auser ID, was required upon system login in the
future.

10. Acknowledgements
8. Information processing framework
Based on our research team’s experiences in thisdisaster, we proposed an information-processing
framework as shown in Figure 11. Areas enclosedwith dashed lines show a flow to obtain a common
operational picture based on an assumption that
actual damage situation is known. However, in theevent that an actual damage situation cannot be
determined, a flow to directly connect hazard
observation information from hazard observationequipment was used. This was implemented innormal time, in response to the initial response
system in order to minimize a delay in disaster
response. It is important to utilize a simulation innormal times in order to connect hazard observation
information to disaster response. In normal times, therelationship between a hazard scenario and social
asset information (vulnerability) draws a possible
damage result. With the aid of this framework, it isnecessary to minimize a delay in disaster response by
establishing an initial response system without an
input of actual damage information and by having
preparation based on possible damages. As disaster
response progresses and actual damages gradually
become known, approximated damages can be
replaced with actual damages by area or by type ofdamage.

Copyright © 2013, Infonomics Society

This research was supported by JST (Japan
Science and Technology Corporation), PRESTO(Precursory Research for Embryonic Science andTechnology).

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