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Wildfires represent a growing threat to transitional ecosystems of the Colombian Orinoquía, where savannas and gallery forests converge under increasing anthropogenic pressure and climate variability. This study assesses fire severity and post-fire vegetation recovery in the La Danta Eco-Reserve using high-resolution multispectral imagery from Sentinel-2 processed within the Google Earth Engine (GEE) cloud-computing platform. A multi-temporal analysis was conducted for the period 2021–2025, during which a cumulative burned area of 1845 hectares was identified. Fire severity was quantified using the Differenced Normalized Burn Ratio (dNBR), allowing spatial discrimination of burn impacts across heterogeneous land covers. Results indicate that 73.8% of the burned area was affected by low to moderate-low severity fires, while 26.2% experienced moderate-high to high severity, leading to substantial biomass loss and structural vegetation damage. Post-fire vegetation dynamics were evaluated through time-series analysis of the Normalized Difference Vegetation Index (NDVI), revealing marked contrasts in ecosystem resilience. Savanna formations exhibited rapid recovery, reaching pre-fire NDVI levels within 6 to 12 months, reflecting high adaptive capacity to fire disturbances. In contrast, gallery forests and areas subjected to high-severity fires showed delayed and incomplete recovery even after 24 months, suggesting long-term ecological degradation. Additionally, fire recurrence analysis identified persistent hotspots spatially associated with roads, settlements, and other anthropogenic infrastructure. Overall, the results demonstrate the effectiveness of Sentinel-2 imagery for fine-scale fire monitoring and provide actionable insights to support targeted ecological restoration and fire management strategies in vulnerable Orinoquía ecosystems.