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Issuing a disaster certificate, which is used to decide the contents of a victim’s support, requires accuracy and rapidity. However, in Japan at large, issuing of damage certificates has taken a long time in past earthquake disasters. Hence, the government needs a more efficient mechanism for issuing damage certificates. This study developed an estimation system of roof-damaged buildings to obtain an overview of earthquake damage based on aero-photo images using deep learning. To provide speedy estimation, this system utilized the trimming algorithm, which automatically generates roof image data using the location information of building polygons on GIS (Geographic Information System). Consequently, the proposed system can estimate, if a house is covered with a blue sheet with 97.57 % accuracy and also detect whether a house is damaged, with 93.51 % accuracy. It would therefore be worth considering the development of an image recognition model and a method of collecting aero-photo data to operate this system during a real earthquake.

In the event of a natural disaster, local Japanese governments investigate the level of damage of the buildings and issue damage certificates to the victims. The damage certificate is used to determine the content of the support provided to the victims; hence, they must be issued rapidly and accurately. However, in the past, the investigation of damage was time-consuming, thus delaying the support provided to the victims. Additionally, while investigating the roof of the damaged building, it was difficult for the investigators to look at the entire roof and calculate the damage rate accurately. Therefore, we have developed an automatic method to calculate the damage rate of a roof using image recognition from aerial photos so that building damage investigation can be more accurate and rapid. We requested the staff in the disaster management division to evaluate the estimation results of this model and confirm its effectiveness. As a result, 80 % of the roof data obtained from this method was equal to or more accurate than the investigator checking from the ground. Additionally, we have developed an efficient flow for building damage investigation using the proposed system. In the future, we aim to investigate the system usage to ensure responsibility in data estimation.

Tsunami evacuation simulations are often used to determine necessary countermeasures that will reduce human loss effectively after earthquakes and subsequent tsunamis. However, so far there has been no simulation for the estimated building damage using up-to-date knowledge of seismic engineering. In this study, in order to clarify the effect of building damage on a tsunami evacuation, we first predicted building damage based on the nonlinear response analysis for a realistic strong ground motion and then simulated a tsunami evacuation considering road blockage due to the collapsed buildings. We used one district in Tanabe City in Wakayama Prefecture in Japan where we expect to have a 12 m of tsunami height after an earthquake along the Nankai Trough plate boundary. We found that the prepared capacity of evacuation sites is not enough to let everyone evacuate and that the number of survivors increases by 3–4% if all of the buildings and houses are seismically reinforced. Considering this, plus 1% of expected casualties inside the collapsed houses, it appears to be not as efficient to reinforce buildings and houses to prevent human loss in comparison with increasing the capacity of tsunami evacuation sites in the target district. However, the damage to building and houses will cause a lot of side effects which are not considered here, but will prolong the evacuation time. Thus, we concluded that we need to reinforce the buildings and houses as well as consider the appropriate placement, number, and capacity of the evacuation sites.

This chapter focuses on group discussion sessions targeting the Priority Areas of the Sendai Framework for Disaster Risk Reduction 2015–2030. Day one group discussion session efforts were on Priority Area One—Understanding Disaster Risks; and Day two emphasis was on Priority Areas 2, 3 and 4.

We proposed a classification of the information needs in the phases of disaster and disaster support activities carried out by Japanese information volunteers. The classification denoted irregularities and omissions in information support activities with the blank cells in the classification tables. According to the result, we proposed some styles of information support that would fill the gaps, and strongly recommended the remote help works targeting other information supporters as a probable fourth pillar of Japanese disaster response system.

Extracting the area where people have difficulty evacuating (hereafter difficult-to-evacuate areas, DEA) when tsunamis hit after an earthquake is important for effective disaster mitigation measures. The DEA was conventionally extracted by simply considering the walking speed, distance to the evacuation destination, and time needed for evacuation after considering the estimated tsunami inundation area. However, evaluating the DEA from such a simple scheme is insufficient because the behavior of residents and the road conditions to the evacuation destinations after an earthquake are not properly reflected in the scheme. In this study, agent-based tsunami evacuation simulations that can reflect the behavior of residents and real-time changes in the situation were conducted in Zihuatanejo, Guerrero, Mexico. It is a prime sightseeing destination under the high risk of megathrust events in the Guerrero Gap. First, by checking the simulation images at the tsunami arrival time, bottleneck locations were identified, and five additional models with different measures for the bottleneck locations were constructed and tested to find the best model with 195 casualties. Then, focusing on the best model, three indices for the casualties were proposed to extract the DEA effectively and quantitatively, and numerical analyses using the three indices was conducted. Finally, the subdistrict in the center of the target area (subdistrict 5) was quantitatively found to be the district that should be given the highest priority for measures. Moreover, an example model with a new measure in subdistrict 5 was validated to have 101 casualties. The key points for applying the proposed method for extraction of DEA in other areas are summarized.

This study uses mobility statistics combined with business census data for the eight Japanese prefectures with the highest coronavirus disease-2019 (COVID-19) infection rates to study the effect of mobility reductions on the effective reproduction number (i.e., the average number of secondary cases caused by one infected person). Mobility statistics are a relatively new data source created by compiling smartphone location data; they can be effectively used for understanding pandemics if integrated with epidemiological findings and other economic data sets. Based on data for the first wave of infections in Japan, we found that reductions targeting the hospitality industry were slightly more effective than restrictions on general business activities. Specifically, we found that to hold back the pandemic (that is, to reduce the effective reproduction number to one or less for all days), a 20%–35% reduction in weekly mobility is required, depending on the region. A lesser goal, 80% of days with one or less observed transmission, can be achieved with a 6%–30% reduction in weekly mobility. These are the results if other potential causes of spread are ignored; for a fuller picture, more careful observations, expanded data sets, and advanced statistical modeling are needed.

The 2014 Iyonada Earthquake, which occurred at 02:06 JST on 14 March, measured 6.2 on the Richter scale and originated in the Seto Inland Sea of Japan. To elucidate tsunami evacuation behavior, we examined two coastal communities in Kochi Prefecture, Okitsu and Mangyo, where residents evacuated to high ground in anticipation of a tsunami. In the event of a Nankai megathrust earthquake and tsunami, it is expected that a huge tsunami will be generated and these communities will be severely damaged. Before the Iyonada Earthquake, we had previously collected data about tsunami preparedness and evacuation plans from the residents of these communities, and after the earthquake, we conducted in-depth interviews and questionnaire surveys with the residents regarding the actual evacuation behaviors that they took. This enabled us to compare evacuation plans with evacuation behaviors. Results indicate that many residents responded quickly to the earthquake, either by immediately evacuating to emergency shelters on high ground or by preparing themselves for evacuation. Additionally, the earthquake revealed great differences between the prior evacuation plans and the actual situation of residents’ evacuation, such as specific triggers that significantly led residents to evacuate and the use of vehicles in evacuation.

 Abstract—Problem: This paper investigates the simulation of a community of spatial intelligent agents, an important issue for the implementation and evaluation of distributed algorithms. The research question is how to simulate this organization using Visual C#.NET. Objective: This paper intends to use the C# programming language to develop a simulator. In a simulated environment, a social agent needs to communicate with other agents and respond to received messages. Method: Our approach is to integrate the thread and delegate methods provided by the .NET framework. We enhance the architecture of a spatial intelligent agent in order to embed several in a simulated society. A basic C# program is presented to demonstrate how to implement a contract net protocol (CNP) among three simple agents. Results: Two results were achieved: 1) the responses and actions of three agents during a simulated CNP and 2) a simulated environment that contains distributed spatial intelligent agents that can interact with each other and a human user. Conclusion: The proposed methodology and presented code provide a flexible and efficient framework for C# developers to develop, simulate, and evaluate a society of advanced software agents using the .NET platform.

Problem:Strategic action planning and scheduling (SAP) in the coordination of a disaster response team involves selecting and decomposing an objective into sub-goals, grouping available units into coalitions and assigning them to the sub-goals, allocating units to tasks, and adjusting the decisions that have been made. The primary responsibility of a team’s incident commander (IC) in SAP is to coordinate the actions of operational units in disaster crisis/emergency response management by making macro/strategic decisions.Objective:In this paper, we completely model a real-world problem and present data related to the SAP problem. This data model is used to support the design and development of an appropriate approach to SAP.Method:The employed methodology is to analyze and study the SAP problem, which is composed of six essential dimensions: the problem domain, geographic information, geospatial-temporal macro tasks, strategic action planning, strategic action scheduling, and team structure.Result:The contribution of this paper is the SAP problem data model. It is designed as a unified modeling language (UML) class diagram consisting of entity types, attributes, and relationships associated with SAP problem data modeling.Conclusion:To evaluate the quality of SAP data modeling, the SAP problem data model is used to propose and develop an intelligent assistant software system to assist and collaborate with incident commanders in SAP. The study makes five novel contributions: 1) a complete data model for SAP problem modeling, 2) a presentation and aggregation of task information in geographic objects, 3) the expression and encoding of human intuition as human high-level strategy guidance for SAP, 4) the formulation of a strategic action plan, and 5) the integration of strategic action schedule information with other entities.

This field report describes two deployments of heterogeneous unmanned marine vehicle teams at the 2011 Great Eastern Japan Earthquake response and recovery by the Center for Robot-Assisted Search and Rescue (USA) in collaboration with the International Rescue System Institute (Japan). Four remotely operated underwater vehicles (ROVs) were fielded in Minamisanriku and Rikuzentakata from April 18 to 24, 2011, for port clearing and victim recovery missions using sonar and video. The ROVs were used for multirobot operations only 46% of the time due to logistics. The teleoperated ROVs functioned as a dependent team 86% of the time to avoid sensor interference or collisions. The deployment successfully reopened the Minamisanriku New Port area and searched areas prohibited to divers in Rikuzentakata. The IRS-CRASAR team planned to return from October 18 to 28, 2011, with an unmanned aerial vehicle (UAV), an autonomous underwater vehicle (AUV), and an ROV to conduct debris mapping for environmental remediation missions. The intent was to investigate an interdependent strategy by which the UAV and AUV would rapidly conduct low-resolution scans identifying areas of interest for further investigation by the ROV. The UAV and AUV could not be used; however, the ROV was able to cover 80,000 m2 in 6 h, finding submerged wreckage and pollutants in areas previously marked clear by divers. The field work (i) showed that the actual and planned multirobot system configurations did not fall neatly into traditional taxonomies, (ii) identified a new measure, namely perceptual confidence, and (iii) posed five open research questions for multirobot systems operating in littoral regions. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.

In this study, we propose a new system for searching the inside of a damaged building using grouped rescue robots. Because the assumed target environment is broad and variable, the proposed system is designed to have adaptability, scalability, and usability. The system consists of robots, sensors, a network, a communication protocol, user interfaces, and database management systems; their complementary capabilities allow them to satisfy the requirements for the system. This study presents the requirements and design of the proposed system, briefly describes each element, and provides examples of how the elements function as an integrated system. © 2011 Wiley Periodicals, Inc. © 2011 Wiley Periodicals, Inc.

Through experience with disaster and recovery support activities obtained as a result of Great Hanshin Earthquake, a research group composed of a support activity staff that includes the authors has been developing and studying implementation processes of an information system, a system that can be used by local governments and their surrounding communities immediately after a disaster. The Risk-Adaptive Regional Management Information System (RARMIS) concept is an outcome of these activities. In the concept for disaster risk management, an information system has been proposed that has three features: (1) continuity between emergency and routine use, (2) independence and decentralization, and (3) integrated space and time information. In this paper, the operational issue (1) is focused on and the importance of the implementation process is shown. Finally, two case studies are presented to qualitatively evaluate implementation processes of integrated temporal GIS.

In this paper, we address the needs for reassessing and improving the implementability of the public shelter plan that has been completed exclusively by some local administrative bodies. Using a case study in Nagata Ward of Kobe City, Japan, we propose a simulation and GIS-based model approach to reassess implementability by focusing on residents’ accessibility to nearby shelters and their accommodation capacity. The results show that there are significant differences in evacuation time among Cho-Chome community areas within Nagata Ward. It was also found that communities vary in accommodation capacity risk. Policy implications have been derived to identify suspect areas for further investigation and possible improvement, by way of promoting local residents agreement on their temporary shelters, and adding new designated shelters in appropriate locations. The paper concludes with a list of further research needed in order to integrate the proposed approach for implementation of the public shelter plan.

This research proposes a new practical approach for local residents who are at risk of a catastrophic tsunami. The approach is a unique composite of a computer simulation of a tsunami and collective evacuation behaviors, along with a series of workshops and evacuation drills to discover a feasible solution for successful evacuation without merely considering it a hopeless endeavor. The new tsunami estimation, reissued after the 3.11 catastrophe, is extremely severe, including warnings of 30-meter waves that could arrive only a few minutes after an earthquake. Given such dire warnings, people are likely to be too pessimistic and to feel hopeless in terms of evacuating after a tsunami. This research is aimed at developing an effective communication method, with the collaboration of a computer simulation, to encourage local residents in finding a practical and feasible way to evacuate and to avoid excess pessimism and hopelessness.

To realize safe autonomous evacuation, citizens should obtain well developed “mental model” for evacuation which includes appropriate perception mechanism to preserve flood risk and flexible “alternative set” for evacuation actions. Aiming at const meting well developed mental models which citizens' evacuation actions are determined based on, the paper develops a flood risk communication support system. Through communication among stakeholders assisted by the system, changes in flood risk perception and increase in the flexibility of the alternative plans of evacuation actions are observed in the experimental workshops in Kiyosu City, Aichi prefecture.