Open AccessExtraction of Collapsed Buildings in the 2016 Kumamoto Earthquake Using Multi-Temporal PALSAR-2 Data
Author(s) -
Wen Li,
Fumio Yamazaki
Publication year - 2017
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.332
H-Index - 18
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2017.p0241
Subject(s) - field survey , seismology , disaster area , event (particle physics) , geology , environmental science , geography , remote sensing , meteorology , physics , quantum mechanics
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.