Munenari INOGUCHI. Research Institute for Natural Hazards and Disaster Recovery, Niigata University, Japan 1. Takashi FURUYA

Transcription

1 How to Construct the Common Operational Pictures with Dynamic Maps Using the Mashup Technology - EMT at National and Municipal Level in 20 Great East Japan Earthquake Munenari INOGUCHI Research Institute for Natural Hazards and Disaster Recovery, Niigata University, Japan Takashi FURUYA Center for Risk Management and Safety Sciences, Yokohama National University, Japan 2 Reo KIMURA School of Human Science and Environment, University of Hyogo, Japan 3 Keiko TAMURA Risk Management Office, Niigata University, Japan 4 Haruo HAYASHI Disaster Prevention Research Institute, Kyoto University, Japan 5 Keywords Disaster Response, Common Operational Picture, MashUp, Emergency Mapping Team, Dynamic Map Abstract The Great East Japan Earthquake that occurred in 20 caused a tremendous amount of damage spanning over multiple prefectures due to severe vibrations and tsunami. In order to provide quick and appropriate disaster responses, prefectures must establish a common operational picture regarding damage situations and disaster response statuses among cities, "cho" districts, and villages. This is especially important along the coast to supplement basic functions of those municipalities. The needs of the front line disaster response workers were extracted, and the Emergency Mapping Team (EMT) clarified the characteristics and challenges related to the visualization of those needs. The EMT was put in place at the cabinet office in one-month right after the disaster occurred and continuing at the Iwate Prefecture Hall to investigate how maps should be utilized. Herein, we propose effective information sharing of disaster response activities using maps. Introduction We had a huge earthquake in March th, 20 called the 20 off the Pacific Coast of Tohoku Earthquake. This caused many kinds of disasters and the wide-area damage all over the eastern of Japan. Against this catastrophe, we decided to establish the emergency mapping team and to realize the development of Common Operational Picture (COP) among the responders of ministries and agencies in the central government. There are, however, two big problems. First is that we had to collect and integrate many kinds inoguchi@gs.niigata-u.ac.jp, 8050 Ikarashi Nino-cho, Nishi-ku, Niigata, , JAPAN 2 t-furuya@ynu.ac.jp 3 rkimura@shse.u-hyogo.ac.jp 4 tamura@gs.niigata-u.ac.jp 5 hayashi@drs.dpri.kyoto-u.ac.jp 64

2 and large volume of information, second is that it took much more time to figure out the actual damage. As the way to solve these problems, we selected MashUp Spatial Information. We decided to call researchers and GIS specialists to construct Emergency Mapping Team (EMT). In this activity, we realize the development of COP creating 500 maps in one and half month. It is necessary to provide support on a longer time scale until the recovery of the afflicted area is complete. As relief activities shift from recovery phase to reconstruction phase in the future, it is expected that targets of disaster response and countermeasures will also shift to households and individuals that are segmented. When these needs become a reality, then it will be essential to continually examine the utilization of geospatial information to support decision-making processes in closer collaboration with municipalities under a prefecture. Theory Figure shows the flow of information processing towards sharing a common operational picture that was proposed through initiatives for the Chuetsu Offshore Earthquake of It is imperative that we share a common operational picture in order to come up with an Incident Action Plan (IAP). To this end, it is necessary to understand the external situation surrounding an organization, and damages and response situations within each sector of the organization. For this purpose, we collected information from the various information systems, other organizations, and various sectors of the organization. An assumption for this information processing flow was that data regarding damages comes from each related organization quickly and accurately. However, for complex and wide-spreading disaster such as the Great East Japan Earthquake of 20, information to understand the situation itself was not sufficient due to reasons including the large number of missing people and the number of buildings that were washed away. This forced us to spend a significant amount of time researching this data. While information collection was given a priority in disaster response, the establishment of an initial action system and executing relief activities tended to lag behind until the information collection was completed and we had a good idea of the extent of damages. It is possible to call it as an "information collection imperative principle." It then became an important issue to account for damages that were not known to establish initial response system and to carry out disaster relief activities as soon as possible in order to share a common operational picture such as shown in Figure. Based on our experiences in this disaster, we proposed an information-processing framework as shown in Figure 2. Areas enclosed with dashed lines show a flow to obtain a common operational picture based on an assumption that actual damage situation is known. However, in the event that an actual damage situation cannot be determined, a flow to directly connect hazard observation information from hazard observation equipment was used. This was implemented in normal time, in response to the initial response system in order to minimize a delay in disaster response. It is important to utilize a simulation in normal times in order to connect hazard observation information to disaster response. In normal times, the relationship between a hazard scenario and social asset information (vulnerability) draws a possible damage result. With the aid of this framework, it is necessary 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. 65

3 As disaster response progresses and actual damages gradually become known, approximated damages can be replaced with actual damages by areaa or by type of damage. Information collection Information processing Information analysis Disaster informationn system Coordinatorr Status analysis group with Understanding stakeholders external situation Surveillance Mass media Information center Coordinator with other departments Material coordinator Administration and finance surrounding an organization Understanding status of damage and response in departments within the organization Resource Management group Planning Head Information strategist Common Operational Picture (COP) Incident Action Plan (IAP) Safety officer Safety considera -tions Plan authoriza -tion Incident commander Plan execution Response worker Plan execution Execution Officer Coordination with stakeholders Coordination officer Publicity Publicity Officer Figure. Information flow towards sharing a common operational picture Figure 2. Information processing frameworkk to achieve a comprehensive commonon operational picture Method Huge amounts of information were collected from the afflicted areas. Therefore, it was essential to consolidate the collected information, sort it according to its purposes, and convert itt into spatial information. 66

4 In reality, however, these huge amounts of dataa were not really organized using a standard format, since it required each piece of informationn to be "organized" during a process from information collection to consolidation. It should be noted that the activities of the EMT were carried out under the concept of Mashup. Mashup refers to forming a new service by combining technologies and contents from multiple sources. s This is a feature that functions as if it was a single web service and is formedd by combining multiple Application Program Interfaces (API). The EMT collected and organized related information from the Internet, made the maps neededd for disaster response in GIS, consolidated them into dynamic maps using the mashup technology over a cloud application, and then made as many unique layers as possible available over the world-wide. Figure 3 shows the top page of the EMT website. This page is composed of static and dynamic maps. The selection of a dynamic map, which navigates you to a mashup portal site, allows youu to superimpose various pieces of information. Using a dynamic map, youu can freely superimposee informationn distributed via domestic and foreign sources, in addition to a layer generated by the EMT, onto one map (Figure 4). Another feature of this website is that it makes it possible to combine information collected before b and after the disaster. Figure 3. The EMT website was composed of static maps and dynamic maps m (jump to a mashed-up portal). Results. EMT in Cabinet Office The EMT generated 500 static maps as seen in Table. Each map is a realizationn of a series of processes from spatial analyses using various pieces of information gathered from maps requested by government staff. This information was superimposed in i a process called mashup. Figure 4 depicts a representative map that was generated days after the disaster.. It shows transportation centers andd evacuation situations in areas under directives to evacuate or to stay indoors. This map is based on a hazardd scenario of "radioactive substances have leaked from the Fukushima Nuclear Plant." Concentric circles are a drawn inn areas under evacuation advisory and directive, centering on the t XY coordinate of the Fukushima Nuclear N Plant. In addition, point data 67

5 Figure 4. Generating a dynamic map based on a mashed-up portal. Table. Categories and Numbers of Developed Maps in EMT E in Cabinet Office Purpose of map Hazard observation information Hazard scenario Estimated damage Actual damage Social infrastructure Response policy Disaster response results Classification of map by visualized contents Number Observation of radioactivity 63 Areas under nuclear plant evacuation advisory and directiv ve 8 Planned power outage by Tokyo Electric Power Company 5 Seismic intensity distribution for each building Building distribution withinin areas under evacuation advisory and directive 5 Building distribution in low-altitude areas 33 Isolated people 3 Missing people 38 Injured people 40 Building damage 23 Fires 3 Population and number of households in each municipality 2 Distributio on of population age 65 and over 8 Facilities that can accept people who require assistance 7 Satellite images of disaster areas 2 Relationship between transportation centers and transportation capability 54 Resourcess to consider for long-term evacuation designation Resourcess to consider for specific disaster-afflicted area designation Resourcess to consider for specific disaster-afflicted local public organizations 5 Evacuation center provisio ons 8 Personal safety confirmation Applicatio on of rescue methods 9 Applicatio on of rescue methods and assistance methods 3 Goods procurement Temporary assistance staff dispatch 25 Utility damage recovery 88 Empty maps to record disaster response results 8 Visualization of the recognition of disasters to the society by trend leaders 7 Total 500 Total

6 for companies were used to indicate the locations of their buildings. The actual number of buildings was calculated by superimposing this data using a spatial statistical method. Locations of evacuation centers as well as the number of evacuees at each center (indicated by numbers next to circles " ") were superimposed with transportation centers, such as airports and harbors, to aid in the decision-making process regarding whether it was necessary to close or move existing evacuation centers, or whether to set up new evacuation centers where goods could be transported. 2. EMT in Iwate Prefecture The Disaster Response Centers of the Prefecture and municipalities displayed published information regarding the damages and disaster response activities. This information was displayed as text, numbers, and tables on map that were superimposed with multiple pieces of information in response to requests from different departments (users) of the prefecture. Types of generated maps include: blank maps, maps of evacuation centers, maps about temporary emergency housing, maps of hospitals and clinics, welfare facilities, and others. Table 2 shows a breakdown of the number of maps per category. Table 2. Categories and Numbers of Developed Maps as of early December 20 Major category Number of maps where Number of maps that were Total only one subject layer was used mashed up with temporary houses Medical service Landslide forecast Welfare and elderly nursing care service Social statistics Human and property damage Temporary emergency house 0 Evacuation center 0 Background figure 0 Total The Iwate Aging Society Department wanted to use maps to plan care-taking visits and new facility construction based on the spatial relationship between elderly care facilities and temporary emergency housing. The facilities were classified into five categories: consultation, care, visitation, day use, and others. As we generate maps with five categories for each of twelve municipalities, a balance between the quality and speed was found to be a bottleneck. We also found that prefectural employees themselves wanted to share the information with afflicted municipalities along the coast. For these reasons, we decided to introduce dynamic maps using the Internet where users can select ranges of information to be superimposed, instead of using static maps on paper. We provided user guidance sessions. As a result, employees were actively able to utilize the system to display the layers in any region, which could then be shared over the Internet (Figure 5). 69

7 Figure 5. Positional relationships between elderly nursing care facilities and temporary houses using Web-GIS Discussion Static maps were useful for the national level disaster response because at that level the purpose is to share a common operational picture. Fish that was show that grasping the overall picture through maps that show the entire disaster area. In contrast, maps for the prefectural level disaster response had to cover information not only in one city, cho, or village, but also wider areas under Regional Development Bureaus that function as comprehensive satellite offices of the prefectural government as well as variety of spatial ranges that span across cities, cho, and villages to secure medical system concerning hospitalization in a secondary medical jurisdiction. Furthermore, spatial positional relationships of temporary individual houses and medical and welfare facilities in these spatial ranges had to be grasped. These needs to visualize the whole picture as well as detailed situations on maps necessitated dynamic maps. Unlike static maps, dynamic maps allow users to flexibly change display areas and scale, and freely combine a variety of spatial dataset according to roles and challenges of each disaster response worker. The Aging Society Department used these dynamic maps prior to visiting afflicted municipalities for investigation to understand the range of needs with appropriate scale as needed to conduct more appropriate survey and planning. Dynamic maps were introduced at the national level for the Great East Japan Earthquake, and they featured a mashup of geospatial information from different information sources. At the prefecture level, the number of spatial datasets was greater. However, a high degree of freedom to set the range to be displayed satisfied the requirements of disaster response workers. It is now clear that COP, so essential for facilitating rapid and effective disaster management, cannot be achieved without a support team comprising members with relevant expertise. It would be, however, deeply 70

8 impractical to require individual local authorities to maintain high-skilled disaster response support teams at all times. In order to function effectively, these activities require know-how and skill, human resources, equipment, and foundational data. Within established disaster management practice there is a system in place known as DMAT (Disaster Medical Assistance Team), which sends highly specialized teams to areas affected by disasters in order to provide emergency medical assistance. Also, an Emergency Mapping Team (EMT) should be established on a national scale, together with an organizational structure that allows the team to be dispatched to disaster-affected areas to carry out mapping activities whenever needed. In addition, the efforts in Niigata were undertaken through strong collaboration between industry, government, academia and the public community, with each organization providing both staff and equipment individually. In other words, the entire project was voluntary, with each organization bearing any cost incurred. In financial terms also, then, a system must be established that can provide similar activities in the future with a stable source of support. It is our hope that, in the future, a system can be created which will link all of the organizations involved in disaster response and management together effectively throughout Japan. References ) G. Urakawa, H. Hayashi, K. Fujiharu, K. Tamura and H. Sakai, Constructing Common Operational Picture of Emergency Operation Center, Niigata Prefecture at Niigata-ken Chuetsuoki Earthquake, 2007, Journal of Social Safety Science, No.0, 2008 (in Japanese). 2) H. Hayashi, G. Urakawa, and K. Tamura, Emergency Mapping Center in Niigata Prefecture Emergency Operation Center at Niigata-ken Chuetsuoki Earthquake, Hito to Kokudo, No.0, Ministry of Land, Infrastructure, Transport and Tourism, 2009 (in Japanese). 3) K. Tamura, H. Hayashi G. Urakawa, and H. Sakai, 2007 Niigata-ken Chuetsuoki Earthquake, 2007 Emergency Operation Center Report, Author Biography Munenari INOGUCHI, Ph.D. Assistant Professor, Research Institute for Natural Hazards and Disaster Recovery, Niigata University, Japan Assistant Professor, Research Institute for Natural Hazards and Disaster Recovery, Niigata University, Japan Takashi FURUYA, Ph.D. Assistant Professor, Center for Risk Management and Safety Sciences, Yokohama National University, Japan Reo KIMURA, Ph.D. Associate Professor, School of Human Science and Environment, University of Hyogo, Japan Keiko TAMURA, Ph.D. Professor, Risk Management Office, Niigata University, Japan Haruo HAYASHI, Ph.D. Professor, Disaster Prevention Research Institute, Kyoto University, Japan 7