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JDR Vol.13 No.2 pp. 347-357
(2018)
doi: 10.20965/jdr.2018.p0347

Paper:

Hybrid System for Generating Data on Human Flow in a Tsunami Disaster

Takehiro Kashiyama*1,†, Yoshihide Sekimoto*1, Masao Kuwahara*2, Takuma Mitani*3, and Shunichi Koshimura*4

*1Institute of Industrial Science, The University of Tokyo
Komaba 4-6-1, Meguro-ku, Tokyo 153-8505, Japan

Corresponding author

*2Graduate School of Information Sciences, Tohoku University, Miyagi, Japan

*3Center for Spatial Information Science, The University of Tokyo, Chiba, Japan

*4International Research Institute of Disaster Sciences, Tohoku University, Miyagi, Japan

Received:
October 31, 2017
Accepted:
February 11, 2018
Online released:
March 19, 2018
Published:
March 20, 2018
Keywords:
evacuation behavior, damage prediction, traffic simulation, tsunami damage, migration data
Abstract

Japan has suffered significant damage from countless earthquakes throughout its history. Thus, it is important to take prompt and effective measures against major future earthquakes predicted. Among the components of damage, measures against tsunamis are a top priority, as demonstrated by the catastrophic losses caused by the Great East Japan Earthquake (GEJE). To date, many studies have been conducted on tsunamis to investigate detection, prediction of flooding, and models of evacuation behaviors. Therefore, this study sought to integrate the results of increasingly advanced research in various fields to construct a system that generates data on human flow during a tsunami disaster. We proceeded with a scenario assuming the Great Nankai Trough Earthquake and considered Kochi City as a case study to conduct a trial tsunami evacuation simulation. We validated and evaluated the evacuation behaviors as a scheme for utilizing knowledge of the ever-changing conditions of evacuation and conducted a visualization and analysis of the simulation results.

Cite this article as:
T. Kashiyama, Y. Sekimoto, M. Kuwahara, T. Mitani, and S. Koshimura, “Hybrid System for Generating Data on Human Flow in a Tsunami Disaster,” J. Disaster Res., Vol.13 No.2, pp. 347-357, 2018.
Data files:
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Last updated on Oct. 01, 2024