Fire is one of the significant drivers of vegetation loss and threat to Amazonian landscapes. It is estimated that fires cause about 30% of deforested areas, so the severity level is an important factor in determining the rate of vegetation recovery. Therefore, the application of remote sensing to detect fires and their severity is fundamental. Radar imagery has an advantage over optical imagery because radar can penetrate clouds, smoke, and rain and can see at night. This research presents algorithms for mapping the severity level of burns based on change detection from Sentinel-1 backscatter data in the southeastern Peruvian Amazon. Absolute, relative, and Radar Forest Degradation Index (RDFI) predictors were used through singular polarization length (dB) patterns (Vertical, Vertical-VV and Horizontal, Horizontal-HH) of vegetation and burned areas. The Composite Burn Index (CBI) determ...

In the southeastern Peruvian Amazon, small-scale and artisanal gold mining has become a common activity and represents one of the greatest threats to forests. The study evaluated the natural regeneration of vegetation and the physicochemical properties of the soil for a chronosequence in Madre de Dios (Peru). Fourteen plots of 250 m2 were installed, distributed across areas with abandonment times varying from 2 to 19 years. All stems with a diameter at breast height ≥ 1 cm in each plot were recorded and classified according to size categories (saplings, poles, and trees). We recorded 1023 individuals distributed in 80 species and 27 families. The most abundant families were Fabaceae, Annonaceae and Euphorbiaceae. Inga thibaudiana, Ochroma pyramidale, and Cecropia membranacea were present in all three size categories. The plots exhibited high heterogeneity, with medium diversity and ver...