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Events of this nature have resulted in the leveraging of new automated methodologies to identify and map burned areas. In this paper, we introduce a unified data-driven framework capable of mapping areas damaged by fire by integrating time series of remotely sensed multispectral images, statistical modeling, and unsupervised classification. We collect and analyze multiple remote-sensing images acquired by the Landsat-8, Sentinel-2, and Terra satellites between August\u2013October 2020, validating our proposal with three case studies in Brazil and Bolivia whose affected regions have suffered from recurrent forest fires. Besides providing less noisy mappings, our methodology outperforms other evaluated methods in terms of average scores of 90%, 0.71, and 0.65 for overall accuracy, F1-score, and kappa coefficient, respectively. The proposed method provides spatial-adherence mappings of the burned areas whose segments match the estimates reported by the MODIS Burn Area product.<\/jats:p>","DOI":"10.3390\/rs14215413","type":"journal-article","created":{"date-parts":[[2022,10,30]],"date-time":"2022-10-30T09:01:42Z","timestamp":1667120502000},"page":"5413","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Mapping Burned Areas with Multitemporal\u2013Multispectral Data and Probabilistic Unsupervised Learning"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4808-2362","authenticated-orcid":false,"given":"Rog\u00e9rio G.","family":"Negri","sequence":"first","affiliation":[{"name":"Science and Technology Institute (ICT), S\u00e3o Paulo State University (UNESP), S\u00e3o Jos\u00e9 dos Campos 12245-000, Brazil"},{"name":"Graduate Program in Natural Disasters, S\u00e3o Paulo State University (UNESP), National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), S\u00e3o Jos\u00e9 dos Campos 12245-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5412-3127","authenticated-orcid":false,"given":"Andr\u00e9a E. O.","family":"Luz","sequence":"additional","affiliation":[{"name":"Graduate Program in Natural Disasters, S\u00e3o Paulo State University (UNESP), National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), S\u00e3o Jos\u00e9 dos Campos 12245-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8002-5341","authenticated-orcid":false,"given":"Alejandro C.","family":"Frery","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Victoria University of Wellington (VUW), Wellington 6012, New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1073-9939","authenticated-orcid":false,"given":"Wallace","family":"Casaca","sequence":"additional","affiliation":[{"name":"Institute of Biosciences, Letters and Exact Sciences (IBILCE), S\u00e3o Paulo State University (UNESP), S\u00e3o Jos\u00e9 do Rio Preto 15054-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,28]]},"reference":[{"key":"ref_1","unstructured":"Luterbacher, J., Paterson, L., von Borries, R., Solazzo, K., Devillier, R., and Castonguay, S. 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