Monitoring forests using Synthetic Aperture Radar (SAR) imagery is crucial for tracking spatial and temporal changes, aiding in resource management and climate change analysis. SAR’s ability to penetrate cloud cover and provide consistent, high-resolution data makes it an essential tool for forest monitoring. Our study outlines a methodology for detecting forest changes using SAR, with a case study on the Western Ghats. The approach integrates SAR image acquisition, pre-processing and indices to assess forest cover and health. Change detection algorithms applied to temporal SAR data map forest changes over short period of time. In the case study, Sentinel-1C SAR data from April and October 2023 was used for its high temporal resolution. Pre-processing included radiometric calibration, speckle filtering, and terrain correction. Temporal analysis employed the Radar Vegetation Index (RVI), adapted from NDVI, to detect changes. Significant deforestation events were observed, especially in correlation with increased deforestation periods in the Upper Western Ghats. Spatial analysis revealed deforestation hotspots near rivers and roads, indicating the impact of human infrastructure. Seasonal trends showed higher deforestation rates during the dry season, highlighting easier access to remote areas. The integration of SAR data with advanced analytical techniques provides a robust framework for monitoring forests, offering valuable insights for policymakers and conservationists. Hope this chapter helps in basic understanding of SAR imagery pre-processing and its application in forest change studies.