2018
DOI: 10.20873/uft.2359-3652.2018v5nespecialp30
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Qualificação E Delimitação De Áreas Queimadas Através Do Processamento Digital De Imagens Tm/Landsat

Abstract: O presente trabalho teve como objetivo qualificar e delimitar áreas queimadas através do processamento digital de imagens Landsat 8-TM, no período de maior ocorrência de áreas queimadas, em três áreas localizadas no Estado do Tocantins, durante os anos de 2013 e 2015. As áreas foram representadas por cenas que abrangem municípios das regiões Leste, Sul e Norte: sete municípios na cena 221/67 a Leste; treze municípios na cena 222/68 ao Sul e; vinte e três municípios na cena 223/65 ao Norte. A metodologia empreg… Show more

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“…We also used the burned area product obtained from the Center for Environmental Monitoring and Fire Management, Federal University of Tocantins, which corresponds to the surface affected by fire in the dry season (accessible upon request). The detection of the burned area was with the visual interpretation of the burn scars in two annual images obtained by the Landsat 5 and Landsat 8 satellites (spatial resolutions of 30 m) and from the Resourcesat satellite (spatial resolution of 23.5 m which were resampled to 30 m) [41]. Before the analyses, we revised and recalculated the burned areas for the period 2008-2017 considering surfaces equal or larger than 9 × 10 −4 km 2 (same area as a Landsat pixel).…”
Section: Datasetsmentioning
confidence: 99%
“…We also used the burned area product obtained from the Center for Environmental Monitoring and Fire Management, Federal University of Tocantins, which corresponds to the surface affected by fire in the dry season (accessible upon request). The detection of the burned area was with the visual interpretation of the burn scars in two annual images obtained by the Landsat 5 and Landsat 8 satellites (spatial resolutions of 30 m) and from the Resourcesat satellite (spatial resolution of 23.5 m which were resampled to 30 m) [41]. Before the analyses, we revised and recalculated the burned areas for the period 2008-2017 considering surfaces equal or larger than 9 × 10 −4 km 2 (same area as a Landsat pixel).…”
Section: Datasetsmentioning
confidence: 99%