{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T22:57:07Z","timestamp":1772060227193,"version":"3.50.1"},"reference-count":105,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,6,22]],"date-time":"2023-06-22T00:00:00Z","timestamp":1687392000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Science and Innovation","award":["PID2020-117812RB-I00\/AEI\/10.13039\/501100011033"],"award-info":[{"award-number":["PID2020-117812RB-I00\/AEI\/10.13039\/501100011033"]}]},{"name":"AUIP (Asociaci\u00f3n Universitaria Iberoamericana de Postgrado)","award":["PID2020-117812RB-I00\/AEI\/10.13039\/501100011033"],"award-info":[{"award-number":["PID2020-117812RB-I00\/AEI\/10.13039\/501100011033"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The high exposure of coastal areas worldwide to natural and anthropogenic disasters emphasizes the relevance of disaster management processes that ensure a prompt damage detection and identification of affected areas. This paper aimed to develop a novel approach for disaster monitoring in coastal areas using SAR data. The method was based on an interferometric coherence difference analysis of Sentinel 1 data. To calibrate and validate the method, the Emma Storm, a severe coastal storm that affected the southwest coast of the Iberian Peninsula in 2018, was chosen as a case study. A coastal land use\/land cover method optimization by optical and UAV field data resulted in an overall improvement of about 20% in the identification of disaster-affected areas by reducing false alarms by up to 33%. Finally, the method achieved hit and false alarm rates of about 80% and 20%, respectively, leading to the identification of approximately 30% (7000 ha) of the study area as being affected by the storm. Marshes and vegetated dunes were the most significantly impacted covers. In addition, SAR data enabled the impact assessment with a time lag of 2 days, contrasting the 25-day delay of optical data. The proposed method stands out as a valuable tool for regional-scale coastal disaster monitoring. In addition, it can be automated and operated at a low cost, making it a valuable tool for decision-making support.<\/jats:p>","DOI":"10.3390\/rs15133233","type":"journal-article","created":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T02:34:07Z","timestamp":1687487647000},"page":"3233","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Land Use\/Land Cover Optimized SAR Coherence Analysis for Rapid Coastal Disaster Monitoring: The Impact of the Emma Storm in Southern Spain"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3933-0421","authenticated-orcid":false,"given":"Pedro Andr\u00e9s","family":"Garzo","sequence":"first","affiliation":[{"name":"Instituto de Geolog\u00eda de Costas y del Cuaternario (IGCC\u2014UNMDP\/CIC), Instituto de Investigaciones Marinas y Costeras (IIMyC\u2014CONICET\/UNMDP), University of Mar del Plata, Funes 3350, Mar del Plata 7600, Argentina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6910-448X","authenticated-orcid":false,"given":"Tom\u00e1s","family":"Fern\u00e1ndez-Montblanc","sequence":"additional","affiliation":[{"name":"Earth Sciences Department, University of C\u00e1diz, INMAR, Av. Rep\u00fablica Saharaui s\/n (11510), Puerto Real, 11003 C\u00e1diz, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1007\/s11852-011-0155-2","article-title":"Tools for comprehensive estimate of coastal region marine economy potential and its use for coastal planning","volume":"16","author":"Gogoberidze","year":"2012","journal-title":"J. Coast. Conserv."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"105454","DOI":"10.1016\/j.ocecoaman.2020.105454","article-title":"Recommendations for linking climate change adaptation and disaster risk reduction in urban coastal zones: Lessons from East London, South Africa","volume":"203","author":"Busayo","year":"2021","journal-title":"Ocean Coast. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Zhao, Q., Pan, J., Devlin, A.T., Tang, M., Yao, C., Zamparelli, V., Falabella, F., and Pepe, A. (2022). 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