This study employed an advanced geospatial methodology using the Google Earth Engine(GEE) platform to assess soil erosion in the Satluj Watershed thoroughly. To achieve this, the RevisedUniversal Soil Loss Equation (RUSLE) model was integrated into the study, which was revealedthrough several analytical tiers, each with a unique function. The study commenced with estimatingthe R factor, which was carried out using annual precipitation data from the Climate Hazards GroupInfra-Red Precipitation with Station (CHIRPS). The erodibility of the soil, which the K factor describes,was then calculated using the USDA soil texture classifications taken from the Open Land Map. Thethird layer emphasizes the LS factor, which analyzes slope data and how they affect soil erosionrates, using digital elevation models. To understand the impact of vegetation on soil conservation,the fourth layer presents the C factor, which evaluates changes in land cover, and the NormalizedDifference Vegetation Index (NDVI) derived from Sentinel-2 data. The P factor incorporates MODISdata to assess the types of land cover and slope conditions. Combining these layers with the RUSLEmodel produces a thorough soil loss map, revealing different levels of soil erosion throughout theSatlujWatershed. The preliminary findings indicate that 3.3% of the watershed had slight soil loss,0.2% had moderate loss, and 1.2% had high soil erosion rates. And 92% had severe rates of soil erosion.After a thorough investigation, the detected regions were divided into risk classifications, providingvital information for the watershed’s land management and conservation plans. The mean soil lossthroughout the watershed was determined to be 10,740 tons/ha/year. This novel method creates astrong foundation for evaluating soil erosion, while also highlighting the value of the cloud-basedgeospatial analysis and the RUSLE model in comprehending intricate environmental processes.