{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T00:01:34Z","timestamp":1783468894679,"version":"3.55.0"},"reference-count":35,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003719","name":"Korea Aerospace Research Institute","doi-asserted-by":"publisher","award":["Satellite Information Application"],"award-info":[{"award-number":["Satellite Information Application"]}],"id":[{"id":"10.13039\/501100003719","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing, particularly using synthetic aperture radar (SAR) systems, can be an effective tool in detecting and assessing the area and amount of building damages caused by earthquake or tsunami. Several studies have provided experimental evidence for the importance of polarimetric SAR observations in building damage detection and assessment, particularly caused by a tsunami. This study aims to evaluate the practical applicability of the polarimetric SAR observations to building damage caused by the direct ground-shaking of an earthquake. The urban areas heavily damaged by the 2016 Kumamoto earthquake in Japan have been investigated by using the polarimetric PALSAR-2 data acquired in pre- and post-earthquake conditions. Several polarimetric change detection approaches, such as the changes of polarimetric scattering powers, the matrix dissimilarity measures, and changes of the radar scattering mechanisms, were examined. Optimal damage indicators in the presence of significant natural changes, and a novel change detection method by the fuzzy-based fusion of polarimetric damage indicators are proposed. The accuracy analysis results show that the proposed automatic classification method can successfully detect the selected damaged areas with a detection rate of 90.9% and false-alarm rate of 1.3%.<\/jats:p>","DOI":"10.3390\/rs12010137","type":"journal-article","created":{"date-parts":[[2020,1,3]],"date-time":"2020-01-03T04:43:03Z","timestamp":1578026583000},"page":"137","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Detection of Earthquake-Induced Building Damages Using Polarimetric SAR Data"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0887-1348","authenticated-orcid":false,"given":"Sang-Eun","family":"Park","sequence":"first","affiliation":[{"name":"Geoinformation Engineering, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoon Taek","family":"Jung","sequence":"additional","affiliation":[{"name":"Geoinformation Engineering, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1193\/1.1774182","article-title":"Use of satellite SAR intensity imagery for detecting building areas damaged due to earthquakes","volume":"2","author":"Matsuoka","year":"2004","journal-title":"Earthq. 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