R-tree representations of disaster areas based on probabilistic estimation

Authors:
Hiroyuki Mikuri;Naoto Mukai;Toyohide Watanabe
Affiliations:
Department of Systems and Social Informatics, Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan;Department of Systems and Social Informatics, Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan;Department of Systems and Social Informatics, Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan
Venue:
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Year:
2005

Citing 2
Cited 0

Digital city Kyoto

Communications of the ACM - How the virtual inspires the real
R-trees: a dynamic index structure for spatial searching

SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data

Quantified Score

Hi-index	0.00

Visualization

Abstract

In order to realize a navigation system for refugees in disaster areas, we must reduce computation costs required in setting escape routes. Thus, in this paper, we propose a method for reducing the costs by grasping whole danger regions in a disaster area from a global perspective. At first, we estimate future changes of dangerous regions by a simple way and link all regions with Danger Levels. Then, we index estimated dangerous regions by extended R-tree. In this step, we link the Danger Levels with depths of the extended R-tree and each Danger Level is managed at each depth of the extended R-tree. Finally, we show how our approach effects in setting escape routes.