{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T19:14:36Z","timestamp":1762542876110,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2018,7,8]],"date-time":"2018-07-08T00:00:00Z","timestamp":1531008000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["201708050001"],"award-info":[{"award-number":["201708050001"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Analyses of single-post-event polarimetric synthetic aperture radar (PolSAR) data permit fast and convenient post-disaster damage assessment work. By analyzing valid features, damaged and undamaged buildings can be quickly classified. However, the presence of oriented buildings in the disaster area makes the classification work more challenging. Many previous works extract the damage information of the disaster area by considering oriented buildings and undamaged parallel buildings as survived buildings. However, after-effect debris may create structures with random orientation angles. In our study on the Tohoku earthquake\/tsunami disaster event, we found that some damaged buildings with large building orientation angles (with respect to the satellite flight path) are grouped as oriented buildings (undamaged buildings). In this paper, we propose a new earthquake\/tsunami damage assessment method, particularly for urban areas, that takes this complex situation into consideration. The proposed method solves the problems of both urban-area extraction and damaged-building identification. For urban-area extraction, the proposed combined thresholding and majority voting method can accurately discriminate between urban and foreshortening mountain areas. Meanwhile, for damaged-building identification, the proposed new unsupervised damage assessment method classifies the buildings in a disaster area according to four conditions, and it outperforms the techniques used in existing works. The analysis results and the comparison with the supervised support vector machine (SVM) classification technique show that our proposed method can produce more accurate results for damage assessment using single-post-event PolSAR data.<\/jats:p>","DOI":"10.3390\/rs10071088","type":"journal-article","created":{"date-parts":[[2018,7,9]],"date-time":"2018-07-09T11:18:53Z","timestamp":1531135133000},"page":"1088","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Earthquake\/Tsunami Damage Assessment for Urban Areas Using Post-Event PolSAR Data"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4741-0851","authenticated-orcid":false,"given":"Yaqi","family":"Ji","sequence":"first","affiliation":[{"name":"Center for Environmental Remote Sensing, Chiba University, Chiba 263-8522, Japan"}]},{"given":"Josaphat Tetuko","family":"Sri Sumantyo","sequence":"additional","affiliation":[{"name":"Center for Environmental Remote Sensing, Chiba University, Chiba 263-8522, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8165-5791","authenticated-orcid":false,"given":"Ming Yam","family":"Chua","sequence":"additional","affiliation":[{"name":"Center for Environmental Remote Sensing, Chiba University, Chiba 263-8522, Japan"}]},{"given":"Mirza Muhammad","family":"Waqar","sequence":"additional","affiliation":[{"name":"Center for Environmental Remote Sensing, Chiba University, Chiba 263-8522, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2403","DOI":"10.1109\/TGRS.2009.2038274","article-title":"Earthquake Damage Assessment of Buildings Using VHR Optical and SAR Imagery","volume":"48","author":"Brunner","year":"2010","journal-title":"IEEE Trans. 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