Open AccessVerification of a Method for Estimating Building Damage in Extensive Tsunami Affected Areas Using L-Band SAR Data
Author(s) -
Hideomi Gokon,
Shunichi Koshimura,
Kimiro Meguro
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.p0251
Subject(s) - remote sensing , synthetic aperture radar , ground truth , correlation coefficient , radar , environmental science , computer science , image resolution , scale (ratio) , geology , geography , cartography , artificial intelligence , machine learning , telecommunications
Remote sensing technology is effective for identifying the Remote sensing technology is effective for identifying the extensive damage caused by tsunami disasters. Many methods have been developed to detect building damage at the building unit scale. Of these methods, X-band Synthetic Aperture Radar (SAR) data has a high resolution and is useful to investigate the detailed conditions on the Earth’s surface, although its spatial coverage is relatively small. In contrast, L-band SAR data has a lower resolution, leading to difficulties detecting building damage, although it can cover a broad area. During disasters, it is important to understand the damage across extensive areas in a short time; therefore, it is necessary to develop a method with broad coverage with high accuracy. The primary objective of this study is to develop a method to estimate building damage in tsunami affected areas using L-band SAR (ALOS/PALSAR) data. We developed our method by extending a previously proposed method for X-band SAR (TerraSAR-X) data. This study focused on Sendai City and Watari town in Miyagi Prefecture, where many houses were washed away during the 2011 Tohoku earthquake and tsunami. We verified that the function we developed produced good performance in estimating the number of washed-away buildings, corresponding with ground truth data with a Pearson correlation coefficient of 0.97. Verification was conducted in another study area, which yielded a Pearson correlation coefficient of 0.87.