Forest Disturbance Mapping using Radar imagery.

Tropical forests play a crucial role in mitigating global warming and addressing climate change. However, the increasing degradation of these forests due to different natural and anthropogenic factors necessitates the establishment of robust monitoring systems. While earth observation techniques offer a means to monitor large areas, cloud cover poses a challenge to optical systems in the tropics. In such circumstances, synthetic aperture radar (SAR) imaging turns out to be a useful tool for forest monitoring. This study presents a methodology based on the Cumulative Sum algorithm, utilizing VV, VH, a combination of VV+VH, and the normalization of the same set of polarization of the Sentinel-1 GRD data for year 2022 in Gabon. The proposed method effectively detects the spatial and temporal occurrences of logging events in Gabon. The achieved overall accuracy of the method reaches 68.73%. Importantly, it demonstrates superior performance in identifying smaller disturbances compared to existing RADD alerts. The findings of this study underscore the efficacy of the proposed method in detecting forest disturbances within tropical regions. This approach holds significant promise for enhancing monitoring efforts and supporting conservation initiatives in these critical ecosystems.