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Fires are one of the main sources of disturbance in fire-sensitive ecosystems such as the Amazon. Any attempt to characterize their impacts and establish actions aimed at combating these events presupposes the correct identification of the affected areas. However, accurate mapping of burned areas in humid tropical forest regions remains a challenging task. In this paper, we evaluate the performance of four operational BA products (MCD64A1, Fire_cci, GABAM and MapBiomas Fogo) on a regional scale in the southwestern Amazon and propose a new approach to BA mapping using fraction images extracted from data cubes of the Brazilian orbital sensors CBERS-4/WFI and CBERS-4A/WFI. The methodology for detecting burned areas consisted of applying the Linear Spectral Mixture Model to the images from the CBERS-4/WFI and CBERS-4A/WFI data cubes to generate shadow fraction images, which were then segmented and classified using the ISOSEG non-supervised algorithm. Regression and similarity analyses based on regular grid cells were carried out to compare the BA mappings. The results showed large discrepancies between the mappings in terms of total area burned, land use and land cover affected (forest and non-forest) and spatial location of the burned area. The global products MCD64A1, GABAM and Fire_cci tended to underestimate the area burned in the region, with Fire_cci underestimating BA by 88%, while the regional product MapBiomas Fogo was the closest to the reference, underestimating by only 7%. The burned area estimated by the method proposed in this work (337.5 km2) was 12% higher than the reference and showed a small difference in relation to the MapBiomas Fogo product (18% more BA). These differences can be explained by the different datasets and methods used to detect burned areas. The adoption of global products in regional studies can be critical in underestimating the total area burned in sensitive regions. Our study highlights the need to develop approaches aimed at improving the accuracy of current global products, and the development of regional burned area products may be more suitable for this purpose. Our proposed approach based on WFI data cubes has shown high potential for generating more accurate regional burned area maps, which can refine BA estimates in the Amazon. [ABSTRACT FROM AUTHOR]

The Caatinga biome, characterized by its dynamic vegetation due to climate and land use changes, experiences varied environmental responses during the dry and rainy seasons. This research aims to dissect the complexity of surface radiation fluxes, vapor pressure, and air and soil temperatures across three distinct vegetation densities within the Caatinga: recovering, degraded, and preserved. Utilizing data from Moderate Resolution Imaging Spectroradiometer/Enhanced Vegetation Index products to analyze these densities offers a novel lens through which to view the biome's reaction to climatic shifts. Our findings unveiled specific patterns of solar and longwave radiation fluxes that correlate with key climatic variables like air temperature and surface albedo. This investigation not only addresses a critical gap in our knowledge of a globally significant but underexplored biome, but it also advances our comprehension of how vegetation density influences radiation fluxes in arid settings. Insights from this study are vital for forecasting and mitigating the ecological and climatic impacts of land cover transformations in semiarid regions worldwide. Significantly, the degraded site displayed nearly double the solar radiation reflection (138 Wm−2) compared to the recovering site (68 Wm−2), underscoring the role of vegetation density in modulating local climate conditions, despite atmospheric consistency across the study sites. [Display omitted] • The Caatinga biome covers the world's most densely populated dry region. • The study observes radiation fluxes over different vegetation densities. • Recovering and degraded vegetation had higher incoming solar radiation. • Preserved Caatinga areas emitted the most intense longwave radiation. • Degraded Caatinga showed the highest surface albedo values. [ABSTRACT FROM AUTHOR]