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In addition, they have a strong impact on the global carbon balance and, ultimately, on climate change. This review attempts to provide a comprehensive meta-analysis of studies on remotely sensed methods and data used for estimation of forest burnt area, burn severity, post-fire effects, and forest recovery patterns at the global level by using the PRISMA framework. In the study, we discuss the results of the analysis based on 329 selected papers on the main aspects of the study area published in 48 journals within the past two decades (2000\u20132020). In the first part of this review, we analyse characteristics of the papers, including journals, spatial extent, geographic distribution, types of remote sensing sensors, ecological zoning, tree species, spectral indices, and accuracy metrics used in the studies. The second part of this review discusses the main tendencies, challenges, and increasing added value of different remote sensing techniques in forest burnt area, burn severity, and post-fire recovery assessments. Finally, it identifies potential opportunities for future research with the use of the new generation of remote sensing systems, classification and cloud performing techniques, and emerging processes platforms for regional and large-scale applications in the field of study.<\/jats:p>","DOI":"10.3390\/rs14194714","type":"journal-article","created":{"date-parts":[[2022,9,22]],"date-time":"2022-09-22T23:07:55Z","timestamp":1663888075000},"page":"4714","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":94,"title":["Remote Sensing of Forest Burnt Area, Burn Severity, and Post-Fire Recovery: A Review"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5330-9990","authenticated-orcid":false,"given":"Eldar","family":"Kurbanov","sequence":"first","affiliation":[{"name":"Center for Sustainable Forest Management and Remote Sensing, Volga State University of Technology, Yoshkar-Ola 424000, Russia"}]},{"given":"Oleg","family":"Vorobev","sequence":"additional","affiliation":[{"name":"Center for Sustainable Forest Management and Remote Sensing, Volga State University of Technology, Yoshkar-Ola 424000, Russia"}]},{"given":"Sergey","family":"Lezhnin","sequence":"additional","affiliation":[{"name":"Center for Sustainable Forest Management and Remote Sensing, Volga State University of Technology, Yoshkar-Ola 424000, Russia"}]},{"given":"Jinming","family":"Sha","sequence":"additional","affiliation":[{"name":"School of Geographical Science, Fujian Normal University, Fuzhou 350007, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7202-646X","authenticated-orcid":false,"given":"Jinliang","family":"Wang","sequence":"additional","affiliation":[{"name":"Faculty of Geography, Yunnan Normal University, Chenggong District, Kunming 650500, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8659-5265","authenticated-orcid":false,"given":"Xiaomei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Environmental Science & Engineering, Fujian Normal University, Fuzhou 350007, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5822-032X","authenticated-orcid":false,"given":"Janine","family":"Cole","sequence":"additional","affiliation":[{"name":"Council for Geoscience, 280 Pretoria Street, Silverton, Private Bag X112, Pretoria 0001, South Africa"}]},{"given":"Denis","family":"Dergunov","sequence":"additional","affiliation":[{"name":"Center for Sustainable Forest Management and Remote Sensing, Volga State University of Technology, Yoshkar-Ola 424000, Russia"}]},{"given":"Yibo","family":"Wang","sequence":"additional","affiliation":[{"name":"Center for Sustainable Forest Management and Remote Sensing, Volga State University of Technology, Yoshkar-Ola 424000, Russia"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,21]]},"reference":[{"key":"ref_1","unstructured":"FAO, and UNEP (2020). 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