{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T17:57:19Z","timestamp":1792605439970,"version":"4.5.0"},"reference-count":34,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,3,5]],"date-time":"2021-03-05T00:00:00Z","timestamp":1614902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Urban infrastructures have become imperative to human life. Any damage to these infrastructures as a result of detrimental activities would accrue huge economical costs and severe casualties. War in particular is a major anthropogenic calamity with immense collateral effects on the social and economic fabric of human nations. Therefore, damaged buildings assessment plays a prominent role in post-war resettlement and reconstruction of urban infrastructures. The data-analysis process of this assessment is essential to any post-disaster program and can be carried out via different formats. Synthetic Aperture Radar (SAR) data and Interferometric SAR (InSAR) techniques help us to establish a reliable and fast monitoring system for detecting post-war damages in urban areas. Along this thread, the present study aims to investigate the feasibility and mode of implementation of Sentinel-1 SAR data and InSAR techniques to estimate post-war damage in war-affected areas as opposed to using commercial high-resolution optical images. The study is presented in the form of a survey to identify urban areas damaged or destroyed by war (Islamic State of Iraq and the Levant, ISIL, or ISIS occupation) in the city of Mosul, Iraq, using Sentinel-1 (S1) data over the 2014\u20132017 period. Small BAseline Subset (SBAS), Persistent Scatterer Interferometry (PSI) and coherent-intensity-based analysis were also used to identify war-damaged buildings. Accuracy assessments for the proposed SAR-based mapping approach were conducted by comparing the destruction map to the available post-war destruction map of United Nations Institute for Training and Research (UNITAR); previously developed using optical very high-resolution images, drone imagery, and field visits. As the findings suggest, 40% of the entire city, the western sectors, especially the Old City, were affected most by ISIS war. The findings are also indicative of the efficiency of incorporating Sentinel-1 SAR data and InSAR technique to map post-war urban damages in Mosul. The proposed method could be widely used as a tool in damage assessment procedures in any post-war reconstruction programs.<\/jats:p>","DOI":"10.3390\/ijgi10030140","type":"journal-article","created":{"date-parts":[[2021,3,5]],"date-time":"2021-03-05T05:03:15Z","timestamp":1614920595000},"page":"140","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Post-War Urban Damage Mapping Using InSAR: The Case of Mosul City in Iraq"],"prefix":"10.3390","volume":"10","author":[{"given":"Ali Darvishi","family":"Boloorani","sequence":"first","affiliation":[{"name":"Key Laboratory of Digital Land and Resources, East China University of Technology, Nanchang 330013, China"},{"name":"Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2967-6667","authenticated-orcid":false,"given":"Mehdi","family":"Darvishi","sequence":"additional","affiliation":[{"name":"Department of Physical Geography, Stockholm University, SE-106 91 Stockholm, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2498-0934","authenticated-orcid":false,"given":"Qihao","family":"Weng","sequence":"additional","affiliation":[{"name":"Centre for Urban and Environmental Change, Department of Earth &amp; Environmental Systems, Indiana State University, Terre Haute, IN 47809-1902, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangtong","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Land and Resources, East China University of Technology, Nanchang 330013, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.procs.2018.10.049","article-title":"Deformation monitoring of dam infrastructures via spaceborne MT-InSAR. The case of La Vi\u00f1uela (M\u00e1laga, southern Spain)","volume":"138","author":"Lazecky","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"39","DOI":"10.5194\/isprsannals-II-7-39-2014","article-title":"Optical and SAR data integration for automatic change pattern detection","volume":"II","author":"Mishra","year":"2014","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Stramondo, S., Bignami, C., Pierdicca, N., and Chini, M. (2007). SAR and optical remote sensing for urban damage detection and mapping: Case studies. 2007 Urban Remote Sens. Jt. Event URS, 1\u20136.","DOI":"10.1109\/URS.2007.371866"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1109\/MGRS.2019.2963140","article-title":"Monitoring buildings at landslide risk with SAR: A methodology based on the use of multipass interferometric data","volume":"8","author":"Noviello","year":"2020","journal-title":"IEEE Geosci. Remote. Sens. Mag."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1109\/TGRS.2008.2002695","article-title":"Exploiting SAR and VHR optical images to quantify damage caused by the 2003 Bam earthquake","volume":"47","author":"Chini","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-017-12058-3","article-title":"New insights into earthquake precursors from InSAR","volume":"7","author":"Moro","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.apgeog.2019.05.004","article-title":"Remote sensing-based mapping of the destruction to Aleppo during the Syrian Civil War between 2011 and 2017","volume":"108","author":"Lubin","year":"2019","journal-title":"Appl. Geogr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1080\/22797254.2019.1630322","article-title":"A correlation change detection method integrating PCA and multi-texture features of SAR image for building damage detection","volume":"52","author":"Li","year":"2019","journal-title":"Eur. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Nex, F., Duarte, D., Tonolo, F.G., and Kerle, N. (2019). Structural building damage detection with deep learning: Assessment of a state-of-the-art cnn in operational conditions. Remote Sens., 11.","DOI":"10.3390\/rs11232765"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Park, S.-E., and Jung, Y.T. (2020). Detection of Earthquake-Induced Building Damages Using Polarimetric SAR Data. Remote Sens., 12.","DOI":"10.3390\/rs12010137"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2900","DOI":"10.1109\/TGRS.2011.2113351","article-title":"High-resolution optical and SAR image fusion for building database updating","volume":"49","author":"Poulain","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.isprsjprs.2013.06.011","article-title":"A comprehensive review of earthquake-induced building damage detection with remote sensing techniques","volume":"84","author":"Dong","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1177\/0309133307083296","article-title":"Assessment and prediction of natural hazards from satellite imagery","volume":"31","author":"Gillespie","year":"2007","journal-title":"Prog. Phys. Geogr."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Washaya, P., Balz, T., and Mohamadi, B. (2018). Coherence change-detection with Sentinel-1 for natural and anthropogenic disaster monitoring in urban areas. Remote Sens., 10.","DOI":"10.3390\/rs10071026"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Ghandour, A., and Jezzini, A. (2018). Post-War Building Damage Detection. Proceedings, 2.","DOI":"10.3390\/ecrs-2-05172"},{"key":"ref_16","unstructured":"Matsuoka, M., and Yamazaki, F. (2000, January 24\u201328). Characteristics of satellite SAR images in the areas damaged by earthquakes. Proceedings of the IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. (Cat. No. 00CH37120), Elizabeth City, NC, USA."},{"key":"ref_17","unstructured":"Hosokawa, M., Jeong, B., and Takizawa, O. (2007, January 23\u201327). Earthquake damage detection using remote sensing data. Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1080\/01431160118187","article-title":"Decorrelation of SAR data by urban damages caused by the 1995 Hyogoken-nanbu earthquake","volume":"22","author":"Yonezawa","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","unstructured":"Yonezawa, C., Tomiyama, N., and Takeuchi, S. (2002, January 24\u201328). Urban damage detection using decorrelation of SAR interferometric data. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Toronto, ON, Canada."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1088\/0266-5611\/14\/4\/001","article-title":"Synthetic aperture radar interferometry","volume":"14","author":"Bamler","year":"1998","journal-title":"Inverse Probl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/36.175330","article-title":"Decorrelation in interferometric radar echoes","volume":"30","author":"Zebker","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"7547","DOI":"10.1029\/96JB03804","article-title":"Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps","volume":"102","author":"Zebker","year":"1997","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/36.898661","article-title":"Permanent scatterers in SAR interferometry","volume":"39","author":"Ferretti","year":"2001","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2375","DOI":"10.1109\/TGRS.2002.803792","article-title":"A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms","volume":"40","author":"Berardino","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Darvishi, M., Schl\u00f6gel, R., Bruzzone, L., and Cuozzo, G. (2018). Integration of PSI, MAI, and intensity-based sub-pixel offset tracking results for landslide monitoring with X-band corner reflectors-Italian Alps (Corvara). Remote Sens., 10.","DOI":"10.3390\/rs10030409"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Darvishi, M., Schl\u00f6gel, R., Kofler, C., Cuozzo, G., Rutzinger, M., Zieher, T., Toschi, I., Remondino, F., Mejia-Aguilar, A., and Thiebes, B. (2018). Sentinel-1 and Ground-Based Sensors for Continuous Monitoring of the Corvara Landslide (South Tyrol, Italy). Remote Sens., 10.","DOI":"10.3390\/rs10111781"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1332","DOI":"10.1109\/JSTARS.2020.2969726","article-title":"Performance evaluation of phase and weather-based models in atmospheric correction with Sentinel-1data: Corvara landslide in the Alps","volume":"13","author":"Darvishi","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1109\/JSTARS.2014.2364683","article-title":"Assimilation of GPS-derived atmospheric propagation delay in DInSAR data processing","volume":"8","author":"Fornaro","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pmed.1002567","article-title":"Injury and death during the ISIS occupation of Mosul and its liberation: Results from a 40-cluster household survey","volume":"15","author":"Lafta","year":"2018","journal-title":"PLoS Med."},{"key":"ref_30","unstructured":"United Nations Environment Programme (2017). Environmental Issues in Areas Retaken From Isil Mosul, Iraq Rapid Scoping Mission, UNEP."},{"key":"ref_31","unstructured":"World Bank (2018). Iraq Reconstruction and Investment, World Bank. Part 2."},{"key":"ref_32","unstructured":"Habitat for Humanity (2018). Initial Planning Framework for the Reconstruction of Mosul, HH."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2374","DOI":"10.1109\/TGRS.2006.873207","article-title":"On the Extension of the Minimum Cost Flow Algorithm for Phase Unwrapping of Multitemporal Differential SAR Interferograms","volume":"44","author":"Pepe","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2202","DOI":"10.1109\/36.868878","article-title":"Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry","volume":"38","author":"Ferreti","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/3\/140\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:33:25Z","timestamp":1760160805000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/3\/140"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,5]]},"references-count":34,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2021,3]]}},"alternative-id":["ijgi10030140"],"URL":"https:\/\/doi.org\/10.3390\/ijgi10030140","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,5]]}}}