Rule Based Land Cover Classification For Hilly Terrain Using Sentinel SAR Images

Satellite missions provide consistent Earth observation data for monitoring environmental changes and natural disasters. Sentinel-1, a SAR satellite from ESA's Copernicus program, delivers high-resolution, all-weather imagery, ideal for continuous monitoring. This study leverages Sentinel-1 SAR data to classify land cover in Dehradun, Uttarakhand, using a rule-based approach. Threshold values from VV and VH polarization data were used to differentiate forest, urban, agriculture, and water classes. Ground truth validation via Google Earth showed high accuracy. The results highlight the effectiveness of rule-based classification for SAR data, though scalability to heterogeneous landscapes remains a challenge. This study underscores the potential of Sentinel-1 for precise land cover mapping.