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JDR Vol.12 No.2 pp. 241-250
(2017)
doi: 10.20965/jdr.2017.p0241

Paper:

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Extraction of Collapsed Buildings in the 2016 Kumamoto Earthquake Using Multi-Temporal PALSAR-2 Data

Wen Liu† and Fumio Yamazaki

Department of Urban Environment Systems, Graduate School of Engineering, Chiba University
1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan

†Corresponding author

Received:
October 31, 2016
Accepted:
January 19, 2017
Online released:
March 16, 2017
Published:
March 20, 2017
Creative Commons License
Keywords:
ALOS-2 PALSAR-2, synthetic aperture radar, coherence, intensity, damage extraction
Abstract
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.
Cite this article as:
W. Liu and F. Yamazaki, “Extraction of Collapsed Buildings in the 2016 Kumamoto Earthquake Using Multi-Temporal PALSAR-2 Data,” J. Disaster Res., Vol.12 No.2, pp. 241-250, 2017.
Data files:
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