Journal cover Journal topic
AGILE: GIScience Series Open-access proceedings of the Association of Geographic Information Laboratories in Europe
Journal topic
Volume 1
AGILE GIScience Ser., 1, 17, 2020
https://doi.org/10.5194/agile-giss-1-17-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
AGILE GIScience Ser., 1, 17, 2020
https://doi.org/10.5194/agile-giss-1-17-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  15 Jul 2020

15 Jul 2020

Creation of a Model for Estimating the Home-return Rate of Evacuees Using Mobile Phone Movement Histories and Its Application to the Nankai Trough Earthquake

Yoshiki Ogawa1, Taisei Sato2, and Yoshihide Sekimoto1 Yoshiki Ogawa et al.
  • 1The University of Tokyo, Meguro-ku, Tokyo, Japan
  • 2ZENRIN DataCom Co., Ltd., Minato‐ku, Tokyo, Japan

Keywords: Mobile Phone Location Data, Evacuation Prediction, Home-Return, Damage Estimation Model, Building Collapse, Disaster Recovery Phase

Abstract. Considering the 2011 Great East Japan Earthquake, by utilizing GPS based large-scale people flow data, we developed a home-return model considering city variables that can estimate the rate of people who will have returned home on any number of days after an earthquake tsunami disaster. We obtained high accuracy with the sparse logit model in this study. The model can be applied in estimating a disaster only by using grid-based city variables of GIS data and existing damage estimation models. In addition, we used the model in the case of the Nankai Trough megathrust earthquake and simulated the transition of post-disaster home-return ratio. The estimation result can help local governments plan the management of evacuation centers in terms of the management of supplies and goods for disasters. The study could help a new understanding of the quantitative relationship between people returning home after evacuation and city variables with regard to earthquake and tsunami hazards based on spatial information science.

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