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However, the increase in its recurrence and intensity, as well as accidental fires can lead to socioeconomic and environmental losses. Due to this dual relationship with fire, near real-time (NRT) fire management is required throughout the region. In this context, we developed, to the best of our knowledge, the first Machine Learning (ML) algorithm based on the GOES-16 ABI sensor able to detect and monitor Active Fires (AF) in NRT in MATOPIBA. To do so, we analyzed the best combination of three ML algorithms and how long it takes to consider a historical time series able to support accurate AF predictions. We used the most accurate combination for the final model (FM) development. The results show that the FM ensures an overall accuracy rate of approximately 80%. The FM potential is remarkable not only for single detections but also for a consecutive sequence of positive predictions. Roughly, the FM achieves an accuracy rate peak after around 20 h of consecutive AF detections, but there is an important trade-off between the accuracy and the time required to assemble more fire indications, which can be decisive for firefighters in real life.<\/jats:p>","DOI":"10.3390\/rs14133141","type":"journal-article","created":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T01:40:36Z","timestamp":1656639636000},"page":"3141","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Near Real-Time Fire Detection and Monitoring in the MATOPIBA Region, Brazil"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1690-1175","authenticated-orcid":false,"given":"Mikhaela A. J. S.","family":"Pletsch","sequence":"first","affiliation":[{"name":"Earth Observation and Geoinformatics Division, National Institute for Space Research-INPE, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0876-0501","authenticated-orcid":false,"given":"Thales S.","family":"K\u00f6rting","sequence":"additional","affiliation":[{"name":"Earth Observation and Geoinformatics Division, National Institute for Space Research-INPE, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Felipe C.","family":"Morita","sequence":"additional","affiliation":[{"name":"Rocket Science Consulting, S\u00e3o Paulo 04131-001, SP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1052-5551","authenticated-orcid":false,"given":"Celso H. L.","family":"Silva-Junior","sequence":"additional","affiliation":[{"name":"Institute of Environment and Sustainability, University of California, Los Angeles, CA 90095, USA"},{"name":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA"},{"name":"Departamento de Engenharia Agr\u00edcola, Universidade Estadual do Maranh\u00e3o, S\u00e3o Lu\u00eds 65055-310, MA, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9545-5136","authenticated-orcid":false,"given":"Liana O.","family":"Anderson","sequence":"additional","affiliation":[{"name":"National Center for Monitoring and Early Warning of Natural Disasters\u2014CEMADEN, S\u00e3o Jos\u00e9 dos Campos 12247-016, SP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4134-6708","authenticated-orcid":false,"given":"Luiz E. O. 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