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

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  • Mas Erick
    Laboratory of Remote Sensing and Geoinformatics for Disaster Management International Research Institute of Disaster Science (IRIDeS), Tohoku University
  • Felsenstein Daniel
    Department of Geography, The Hebrew University of Jerusalem
  • Moya Luis
    Laboratory of Remote Sensing and Geoinformatics for Disaster Management International Research Institute of Disaster Science (IRIDeS), Tohoku University
  • Grinberger A. Yair
    Department of Geography, The Hebrew University of Jerusalem GIScience Research Group, Institute of Geography, Heidelberg University
  • Das Rubel
    Research & Development Center, Nippon Koei Co., Ltd.
  • Koshimura Shunichi
    Laboratory of Remote Sensing and Geoinformatics for Disaster Management International Research Institute of Disaster Science (IRIDeS), Tohoku University

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<p>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.</p>

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