{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T14:50:40Z","timestamp":1779893440628,"version":"3.53.1"},"reference-count":56,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,19]],"date-time":"2020-08-19T00:00:00Z","timestamp":1597795200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012783","name":"Dipartimento della Protezione Civile, Presidenza del Consiglio dei Ministri","doi-asserted-by":"publisher","award":["convention between Department of Civil Protection and CIMA Research foundation, for the development of knowledge, methodologies, technologies and training useful for the implementation of national systems of monitoring, prevention and surveillance"],"award-info":[{"award-number":["convention between Department of Civil Protection and CIMA Research foundation, for the development of knowledge, methodologies, technologies and training useful for the implementation of national systems of monitoring, prevention and surveillance"]}],"id":[{"id":"10.13039\/100012783","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper presents a new method, based on clustering and thresholding, to automatically perform binary change detection in multitemporal spectral indices. The method is denoted as Buffer-From-Cluster Approach (BFCA). To estimate the distributions of changed and unchanged pixels, as needed for the purpose of a reliable thresholding of a spectral index, a clustering algorithm is preliminarily applied to identify image objects possibly corresponding to areas where significant changes occurred. Then, a buffer zone is created around the selected cluster to identify unchanged areas surrounding changed ones. The cluster and the buffer zone are jointly analyzed to estimate the distributions of changed and unchanged pixels and to verify that they can be distinguished from each other. Finally, the results of thresholding and clustering are combined to generate the binary change map. The BFCA has been conceived to map the extent of the areas affected by a natural disaster like wildfire. To validate the proposed method, burned area maps produced by applying the BFCA to spectral indices derived from Sentinel-2 data have been compared to maps produced by the Copernicus Emergency Management Service. For testing the multi-hazard detection capability, the same kind of exercise has been carried out for a flooding test case too. The positive results of the comparison have confirmed the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/rs12172681","type":"journal-article","created":{"date-parts":[[2020,8,19]],"date-time":"2020-08-19T21:37:40Z","timestamp":1597873060000},"page":"2681","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["A Method to Automatically Detect Changes in Multitemporal Spectral Indices: Application to Natural Disaster Damage Assessment"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8483-1490","authenticated-orcid":false,"given":"Luca","family":"Pulvirenti","sequence":"first","affiliation":[{"name":"CIMA Research Foundation, I-17100 Savona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giuseppe","family":"Squicciarino","sequence":"additional","affiliation":[{"name":"CIMA Research Foundation, I-17100 Savona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7945-159X","authenticated-orcid":false,"given":"Elisabetta","family":"Fiori","sequence":"additional","affiliation":[{"name":"CIMA Research Foundation, I-17100 Savona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dilley, M., Chen, R.S., Deichmann, U., Lerner-Lam, A., Arnold, M., Agwe, J., Buys, P., Kjekstad, O., Lyon, B., and Yetman, G. 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