Remote sensing applied to forest fires in Andean ecosystems: Detection and severity analysis in Cusco
Keywords:
Remote sensing; forest fires; fire severity; Andean ecosystemsAbstract
This research aimed to detect and analyze the severity of forest fires in Andean ecosystems of the Cusco region using remote sensing techniques. A quantitative, descriptive-explanatory, and applied approach was used, based on the processing of MODIS, VIIRS, and Landsat 8 satellite data, integrated into GIS platforms and Google Earth Engine. The methodological design was non-experimental and retrospective longitudinal, based on records from the period 2015–2024. Pre- and post-fire mosaics were constructed from this data, atmospheric masks were applied, and the NBR and dNBR indices were calculated to assess biomass loss with radiometric precision. The results allowed for the delimitation of a study area defined by a 20 km buffer around the largest glacial complex in southern Cusco, where hotspots were concentrated. Furthermore, spectral analysis revealed heterogeneous severity patterns, characterized by high-intensity patches embedded within matrices of moderate impact. Integrating temporal recurrence and severity allowed for the identification of critical zones where fire recurs with greater frequency and impact. In conclusion, remote sensing proved to be a robust tool for understanding the spatiotemporal dynamics of fire and providing essential input for risk management in Andean ecosystems.
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