The forest fires of 2019 were among the most devastating ever recorded in Bolivia. In this study we analyze the relationship between forest fragmentation and meteorological drought with the spatial distribution of forest fires during that year in the Department of Santa Cruz, Bolivia. We carried out a classification of the natural vegetation using Landsat 8 satellite imagery. Forest fragmentation was defined according to the distribution of forest patch sizes and classified using seven categories; furthermore, distance to anthropogenically used areas and forest edges was quantified. Spatial patterns of meteorological drought severity were quantified using long-term series of precipitation and reference evapotranspiration. Areas burned during 2019 (July–December) were characterized by means of spectral indices (normalized burn ratio (NBR) and normalized delta burn ratio (dNBR)) and unsupervised classification methods (interactive self-organizing data analysis algorithm (ISODATA)). The results show that 61.9% of the total area burned occurred in large (>2,000,000 ha), relatively unfragmented patches. However, the highest proportion of fires (17.1%) occurred in relatively small patches (<20 ha). In addition, anthropogenically used zones and forest edges were most impacted by forest fires. Finally, the spatial patterns of drought severity also influenced the severity of forest fires.

The natural regeneration of ecosystems impacted by fires is a high priority in Bolivia, and represents one of the country’s greatest environmental challenges. With the abundance of spatial data and access to improved technologies, it is critical to provide an effective method of analysis to evaluate changes in land use in the face of the global need to understand the dynamics of vegetation in regeneration processes. In this context, we evaluated the dynamics of natural regeneration through phenological patterns by measuring the maximal and minimal spectral thresholds at four fire-impacted sites in Chiquitania in 2019 and 2020, and compared them with unburned areas using harmonic fitted values of the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR). We used two-way ANOVA test to evaluate the significant differences in the values of the profiles of NDVI and NBR indices. We quantified severity at the four study sites using the dNBR obtained from the difference between pre- and postfire NBR. Additionally, we selected 66 sampling sites to apply the Composite Burn Index (CBI) methodology. Our results indicate that NBR is the most reliable index for interannual comparisons and determining changes in the phenological pattern, which allow for the detection of postfire regeneration. Fire severity levels based on dNBR and CBI indices are reliable methodologies that allow for determining the severity and dynamics of changes in postfire regeneration levels in forested and nonforested areas.