{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T09:29:34Z","timestamp":1776504574424,"version":"3.51.2"},"reference-count":30,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,21]],"date-time":"2018-05-21T00:00:00Z","timestamp":1526860800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rapid damage mapping following a disaster event, especially in an urban environment, is critical to ensure that the emergency response in the affected area is rapid and efficient. This work presents a new method for mapping damage assessment in urban environments. Based on combining SAR and optical data, the method is applicable as support during initial emergency planning and rescue operations. The study focuses on the urban areas affected by the Tohoku earthquake and subsequent tsunami event in Japan that occurred on 11 March 2011. High-resolution TerraSAR-X (TSX) images of before and after the event, and a Landsat 5 image before the event were acquired. The affected areas were analyzed with the SAR data using only one interferometric SAR (InSAR) coherence map. To increase the damage mapping accuracy, the normalized difference vegetation index (NDVI) was applied. The generated map, with a grid size of 50 m, provides a quantitative assessment of the nature and distribution of the damage. The damage mapping shows detailed information about the affected area, with high overall accuracy (89%), and high Kappa coefficient (82%) and, as expected, it shows total destruction along the coastline compared to the inland region.<\/jats:p>","DOI":"10.3390\/rs10050802","type":"journal-article","created":{"date-parts":[[2018,5,22]],"date-time":"2018-05-22T04:34:03Z","timestamp":1526963643000},"page":"802","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Combining TerraSAR-X and Landsat Images for Emergency Response in Urban Environments"],"prefix":"10.3390","volume":"10","author":[{"given":"Shiran","family":"Havivi","sequence":"first","affiliation":[{"name":"Earth and Planetary Image Facility, Department of Geography and Environmental Development, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilan","family":"Schvartzman","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shimrit","family":"Maman","sequence":"additional","affiliation":[{"name":"Homeland Security Research Institute, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stanley R.","family":"Rotman","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan G.","family":"Blumberg","sequence":"additional","affiliation":[{"name":"Earth and Planetary Image Facility, Department of Geography and Environmental Development, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3983","DOI":"10.1080\/0143116031000103826","article-title":"Application of satellite remote sensing in natural hazard management: The Mount Mangart landslide case study","volume":"24","author":"Veljanovski","year":"2003","journal-title":"Int. J. 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