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Author Yoshiki Ogawa; Yuki Akiyama; Ryosuke Shibasaki
Title Extraction of significant scenarios for earthquake damage estimation using sparse modeling Type Conference Article
Year 2017 Publication Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal ISCRAM 2017
Volume Issue Pages 150-163
Keywords Big data; Mobile phone GPS logs; People flow; Micro geodata; Damage distribution
Abstract The recent diversification and accumulation of data from GPS equipped mobile phones, building sensors, and other resources in Japan has caused a large increase in the number of earthquake disaster scenarios that can be identified. Disaster prevention planning requires us to contemplate which scenario should be focused on and the required response to various scenarios. As a means to solve this problem, the damage distribution of building collapse and fire from GPS data can be used to estimate future damage based on people flow and various hypocenter models of earthquakes. We propose a method that uses sparse modeling to extract scenarios that are important for disaster estimation and prevention. As a result, this paper makes it possible to quickly grasp the scenario distribution, which was previously impossible to do, and to extract the significant scenarios.
Address The University of Tokyo
Corporate Author (up) Thesis
Publisher Place of Publication Albi, France Editor Tina Comes, Frédérick Bénaben, Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN Medium
Track Analytical Modeling and Simulation Expedition Conference 14th International Conference on Information Systems for Crisis Response And Management
Notes Approved no
Call Number Serial 1453
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