Journal of Disaster Research
Online ISSN : 1883-8030
Print ISSN : 1881-2473
ISSN-L : 1881-2473
Special Issue on Disaster and Big Data Part 2
Extraction of Collapsed Buildings in the 2016 Kumamoto Earthquake Using Multi-Temporal PALSAR-2 Data
Wen LiuFumio Yamazaki
著者情報
ジャーナル オープンアクセス

2017 年 12 巻 2 号 p. 241-250

詳細
抄録

An earthquake (Mw6.2) struck Kumamoto Prefecture, Japan on April 14, 2016. A larger event (Mw7.0) struck the same area 28 hours later, on April 16. The series of earthquakes caused significant damage to buildings and infrastructures. Remote sensing is an effective tool to grasp damage situation over wide areas after a disaster strikes. In this study, two sets of ALOS-2 PALSAR-2 images taken before and after the earthquake were used to extract the areas with collapsed buildings. Three representative change indices, the co-event coherence, the ratio between the co- and pre-event coherence, and the z-factor combining the difference and correlation coefficients, were adopted to extract the collapsed buildings in the central district of Mashiki Town, the most severely affected area. The results of a building-by-building damage survey in the target area were used to investigate the most suitable threshold value for each index. The extracted results were evaluated by comparing them with the reference data from field surveys. Finally, the most valid factor was applied to larger affected areas for Kumamoto City and its surroundings.

著者関連情報

この記事は最新の被引用情報を取得できません。

© 2017 Fuji Technology Press Ltd.

This article is licensed under a Creative Commons [Attribution-NoDerivatives 4.0 International] license (https://creativecommons.org/licenses/by-nd/4.0/).
The journal is fully Open Access under Creative Commons licenses and all articles are free to access at JDR Official Site.
https://www.fujipress.jp/jdr/dr-about/
前の記事 次の記事
feedback
Top