Burned area mapping in Different Data Products for the Southwest of the Brazilian Amazon

Abstract

Fires affect the Amazon rainforest and cause various socio-environmental problems. Analyses of forest fire dynamics supporting actions to combat and prevent forest fires. However, many studies have reported discrepancies in the quantification of fire, especially in the tropics. We evaluated four operational products for estimating burned areas (MAPBIOMAS, MCD64A1, GABAM, and GWIS) in a part of the southwestern Brazilian Amazon. We used the year 2019 as a reference to assess the relative performance of each product through stratification by forest and non-forest areas. Statistical (Kolmogorov–Smirnov test) and geospatial analyses were performed using fuzzy similarity analysis and mapping of burned areas for forest and non-forest classes. The four products showed a divergence of up to 90.6% in the total area burned. MAPBIOMAS was the product with the largest area burned (3379 km²), and MCD64A1 detected the smallest area (325 km²). MAPBIOMAS and GABAM generally overestimates burn scars in forest areas compared to MCD64A1 and GWIS. Factors that influence the mapping of burned areas include cloud shadow, the spatial resolution of sensors, and external noises (drought and decomposition of bamboo forests). We highlight the importance of field validation when mapping imagery to differentiate the truly burned areas from targets with similar spectral behavior.