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JDR Vol.13 No.7 pp. 1257-1271
(2018)
doi: 10.20965/jdr.2018.p1257

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Dynamic Integrated Model for Disaster Management and Socioeconomic Analysis (DIM2SEA)

Erick Mas*1,†, Daniel Felsenstein*2, Luis Moya*1, A. Yair Grinberger*2,*3, Rubel Das*4, and Shunichi Koshimura*1

*1Laboratory of Remote Sensing and Geoinformatics for Disaster Management
International Research Institute of Disaster Science (IRIDeS), Tohoku University
468-1 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8572, Japan

†Corresponding author

*2Department of Geography, The Hebrew University of Jerusalem, Jerusalem, Israel

*3GIScience Research Group, Institute of Geography, Heidelberg University, Heidelberg, Germany

*4Research & Development Center, Nippon Koei Co., Ltd., Tokyo, Japan

Received:
August 15, 2018
Accepted:
October 29, 2018
Published:
December 1, 2018
Creative Commons License
Keywords:
urban simulation, damage assessment, socioeconomic impact, disaster management, disaster simulation
Abstract

The DIM2SEA research project aims to increase urban resilience to large-scale disasters. We are engaged in developing a prototype Dynamic Integrated Model for Disaster Management and Socioeconomic Analysis (DIM2SEA) that will give disaster officials, stakeholders, urban engineers and planners an analytic tool for mitigating some of the worst excesses of catastrophic events. This is achieved by harnessing state-of-the-art developments in damage assessment, spatial simulation modeling, and Geographic Information System (GIS). At the heart of DIM2SEA is an agent-based model combined with post-disaster damage assessment and socioeconomic impact models. The large amounts of simulated spatial and temporal data generated by the agent-based models are fused with the socioeconomic profiles of the target population to generate a multidimensional database of inherently “synthetic” big data. Progress in the following areas is reported here: (1) Synthetic population generation from census tract data into agent profiling and spatial allocation, (2) developing scenarios of building damage due to earthquakes and tsunamis, (3) building debris scattering estimation and road network disruption, (4) logistics regarding post-disaster relief distribution, (5) the labor market in post-disaster urban dynamics, and (6) household insurance behavior as a reflection of urban resilience.

Cite this article as:
E. Mas, D. Felsenstein, L. Moya, A. Grinberger, R. Das, and S. Koshimura, “Dynamic Integrated Model for Disaster Management and Socioeconomic Analysis (DIM2SEA),” J. Disaster Res., Vol.13 No.7, pp. 1257-1271, 2018.
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