Sentinel-1 Based Improved Snow Cover Mapping Method: Study on Himalayan Terrain

Snow is a crucial indicator of climate change and serves as a primary water supply source in the Himalayan region, making snow cover mapping essential for various applications, including hydrology, climate modeling, and avalanche forecasting. However, existing change detection methods have shown limited accuracy in this challenging terrain. This study proposes a new threshold-based approach using Sentinel-1 SAR data to improve snow cover mapping. The findings emphasize the importance of high sensitivity for comprehensive snow detection, crucial for resource management and disaster preparedness in the region. The research highlights the potential of cross-polarization channels for detecting snow at higher elevations, complementing the effectiveness of co-polarization channels for wet snow mapping. The proposed method emerges as the most suitable method, providing a favorable balance between accuracy, specificity, and sensitivity in Snow Cover (SC) mapping across winter months. These findings illustrate the capability of dual-polarization SAR data in improving snow cover mapping in the region.