This study aimed to assess the spatial distribution of agricultural land use on saline soils in Soc Trang province in 2024. We used images from the Sentinel-1A radar satellite taken at different times to classify land use using a supervised method with the Random Forest algorithm on the Google Earth Engine platform. The resulting agricultural land use map was then overlaid with saline soil data from the Department of Agriculture and Rural Development of Soc Trang province to analyze spatial patterns concerning salinity levels. The classification output identified 11 land use categories: (1) water bodies, (2) built-up areas, (3) aquaculture, (4) rice–shrimp farming, (5) double rice crop, (6) triple rice crop, (7) other perennial crops, (8) other annual crops, (9) forest, (10) coconut, and (11) sugarcane. The classification demonstrated high accuracy assessment with an overall accuracy (T) at 91.26% and a Kappa coefficient at 0.89. The results revealed spatial differentiation in agricultural land based on different soil types. Areas with low to moderate saline soils have mainly distributed from none to low-tolerant crops as rice crops, annual plants, coconuts, sugarcane, and other perennial plants. Shrimp farming primarily identifies high-salinity areas. Coastal areas with very high salinity were associated with protective mangrove forests. This study highlights the effectiveness of Sentinel-1 radar images for land use classification and monitoring in saline environments. Furthermore, the result provides a scientific basis for land-use planning, crop cultivation, and soil salinity management toward the region's adaptive and sustainable agricultural development.