3 October 2017 Building damage mapping of 2016 Kumamoto, Japan, earthquake using ALOS-2/PALSAR-2 interferometric coherence
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The 2016 Kumamoto earthquake sequence started with a Mj (Japan Meteorological Agency magnitude) 6.5 event on 14 April, and culminated in a Mj 7.3 event on 16 April. Rapid damage assessment after natural disasters is crucial to fast crisis response. Synthetic aperture radar (SAR) interferometric analysis has a great potential due primarily to its phase difference. In this study, we demonstrated the applicability of interferometric coherence from SAR images for detection of building damages and liquefactions caused by the earthquake. Three ALOS-2/PALSAR-2 data acquired on 30 November, 2015, 7 March, 2016 and 18 April, 2016 were used. The interferometric coherence was calculated within several moving window pixels from pre- and post-disaster PALSAR-2 images. For damage assessment, normalized difference (ND) of interferometric coherence was calculated using pre- and co-disaster SAR image pairs. For validation, we adopted a map of estimated number of collapsed buildings calculated by the National research Institute for Earth science and Disaster resilience, Japan (NIED). The estimation map shows seven ranking of collapsed buildings within 250 m × 250 m area. The averaged ND of interferometric coherence indicates the trend of increase with corresponding to the increase of the estimated number of collapsed buildings. In addition, ND of interferometric coherence image showed liquefaction as a high value in urban areas. The distribution pattern was in good agreement with a liquefaction map referred to literatures. These results indicate the possibility of rapid damage mapping after the earthquake for fast crisis response using SAR interferometric coherence.
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Tomohisa Konishi, Tomohisa Konishi, Yuzo Suga, Yuzo Suga, } "Building damage mapping of 2016 Kumamoto, Japan, earthquake using ALOS-2/PALSAR-2 interferometric coherence", Proc. SPIE 10426, Active and Passive Microwave Remote Sensing for Environmental Monitoring, 104260F (3 October 2017); doi: 10.1117/12.2277832; https://doi.org/10.1117/12.2277832

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