Contribution of SAR/Sentinel-1 images in the detection of burnt areas in the natural vegetation of the brazilian Pantanal biome

Abstract:

The Brazilian Pantanal biome, known for its rich biodiversity and wetlands, is experiencing frequent and destructive fires. Detecting and monitoring burnt areas is vital for comprehending their present ecological condition, a key indicator for climate change and protective measures. Optical remote sensing methods, traditionally used in fire mapping, have limitations due to atmospheric conditions. Microwave Synthetic Aperture Radar (SAR) is a promising alternative, excelling in challenging environments and demonstrating sensitivity to surface properties. This study aimed to assesses the potential of SAR images for detecting burnt areas in a conservation unit inserted in the Brazilian Pantanal after intense fires in 2020. For this, the Normalized Burn Ratio (NBR) index was calculated from Sentinel-2 images before and after fire, and then the difference between these images (dNBR). Differences in backscatter coefficients of pre- and post-fire SAR/Sentinel-1 images in the two polarizations (dVH and dVV) were also calculated. To detect burnt areas, the three differences were classified using the Random Forest algorithm. The results showed adequate coincidence of burned areas between dVH and dVV compared to dNBR and high accuracy values of the algorithm model, indicating consistency between SAR and optical data in identifying burnt areas.

Keywords:
Burnt area detection; Forest fire; Sentinel-1; Brazilian Pantanal; Remote sensing; Synthetic Aperture Radar