Monitoring Canopy Water Content in the Indian Himalayan Forests Using Sentinel-1 Derived Vegetation Optical Depth

Forest fires severely impact the Indian Himalayan ecosystem, causing ecological damage and threatening biodiversity. Assessing wildfire risk is challenging due to uncertainties in fuel flammability and ignition probability. Live Fuel Moisture Content (LFMC), which represents the water ratio in biomass, is a key factor in determining burnable fuel. This study estimates LFMC using high-resolution Vegetation Optical Depth (VOD) data from Sentinel-1, leveraging microwave measurements to assess vegetation moisture and biomass content. A modified Water Cloud Model establishes the relationship between field-measured LFMC and VOD. The results show a positive correlation between VOD and LFMC, with correlation coefficients of 0.52 for VODVV and 0.55 for VODVH. These findings highlight the approach’s effectiveness in monitoring vegetation water stress and wildfire susceptibility.