This study examined the regional spatial characteristics of tsunami flooding and building damage using geographic information systems. An analytical model that evaluates total building destruction risk was developed using building damage data from coastal areas in Iwate Prefecture. Building density characteristics in the study area were categorized into four types of environments: (1) many isolated buildings, (2) combination of isolated and neighboring buildings, (3) combination of neighboring and surrounding buildings, and (4) many neighboring buildings. Many isolated buildings were located along the narrow, low-lying areas facing the Pacific Ocean. In comparison, higher building densities were observed along the inner part of the enclosed gulf topography. Most buildings located near the shoreline collapsed. Farther inland, a higher percentage of buildings experienced half-collapse or no-damage. Closer inspection of the varying spatial distribution characteristics and resultant building damage among the 27 target areas led to the identification of several key indicators for predicted building damage including the structure, use, and density of the affected building and the extent of tsunami inundation. Based on the building damage characteristics following the 2011 tsunami, a building group destruction probability model was developed and verified. The proposed model successfully estimated building collapse ratios using the available data.

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This study discusses the domestic deployment of the disaster response team of the International Red Cross based in Japan. The team responded to the Niigata Chuetsu Earthquake, the Great East Japan Earthquake and Tsunami (GEJET), and the 2016 Kumamoto Earthquakes. Relief equipment such as large tents, water supply equipment, and generators were useful for supporting damaged medical facilities and improving the living conditions at the evacuation centers. Whilst many studies point out the difficulties in needs matching and logistics arrangements in receiving foreign medical teams in the GEJET, the international disaster response team of the Japanese Red Cross has overcome these challenges by utilizing the existing networks that were constructed before the event.

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We propose an agent-based simulation system for evacuations after earthquakes and tsunami. We focus on an improved model of communication among agents, by including a model of speech intelligibility in crowds, and the use of voice to change the evacuation-start behavior. This allows the model to represent the effects of evacuees calling to each other, and of automated emergency broadcast systems. To validate our model, we simulate hypothetical scenarios using data from the Great Hanshin-Awaji Earthquake and the Great East Japan Earthquake and tsunami as the initial conditions. Evacuation start and completion rates from the simulation were similar to those observed in the original events, based on data from post-disaster surveys, and showed the model’s ability to serve as a policy modeling tool.

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