This research investigates Paraguayan wildfires in the Cerro Chovoreca National Monument through satellite data to analyze precipitation patterns, burned area detection, and vegetation index anomalies. The first chapter provides an overview of forest fires in South America, focusing particularly on the Gran Chaco region of Paraguay, which has experienced a large loss of forest due to fires and deforestation. The second chapter reviews the different remote sensing techniques that have been applied in the detection of burned areas. These techniques include hyperspectral, multispectral, synthetic aperture radar (SAR), interferometric synthetic aperture radar (InSAR), Lidar and Thermal sensors. The third chapter evaluates the 2019 fire at Cerro Chovoreca by showing reduced precipitation from July to September and increased fire activity during that period. The results show that the Harmonized Landsat Sentinel-2 has strengths for burned area detection, considering its spatial resolution. However, the product presents some limitations due to temporal coverage and availability of imagery without clouds. Additionally, during the evaluation of the VNP64A1 product of the Visible Infrared Imaging Radiometer Suite instrument, it was observed that this product underestimated the burned areas on the dates when the fire was more intense. Finally, in order to analyze the post-fire impact on the region, an NDVI analysis was performed, revealing areas with high damage due to fires, which closely correspond with the burned areas detected. A time series analysis from 2002-2022 was carried out that demonstrates the vegetation recovery following the 2019 fires.