This study is used to assess the soil quality in the Thamirabarani river basin in South India using remote sensing (RS) and geographic information system (GIS) techniques. In this study, 13 parameters contributing to soil quality were analyzed to demarcate the soil quality zone in the basin using the remote sensing indices and in-situ sampling data. The parameters include soil organic matter, organic carbon, clay minerals, soil iron oxide, soil carbonate, soil salinity, soil moisture, soil erodibility, land use/land cover (LULC), soil texture, land surface temperature (LST), Normalized Difference Moisture Index (NDMI), and slope. They are derived from multiple data sources, including Landsat 9 Operational Land Imager (OLI) and ASTER DEM satellite images, in-situ soil sampling data, Survey of India—topographical maps, GSI—resource maps, IMD—rainfall data, and other collateral data sets. The GIS-based Analytical Hierarchy Process (AHP) technique analyses soil quality zonation at a site-specific scale. The soil quality zone (SQZ) map is classified into five soil quality zones (Very good, good, moderate, poor, and very poor) to represent the spatial characteristics of soil quality in the basin, wherein low values (soil quality index (SQI) = 36–44, and 45–51) showed the area with inferior and poor soil quality that covers 1% and 10% respectively. The moderate soil quality zone (SQI = 52–59) spread over the area of 46%. However, the soil quality zones showed good (SQI = 60–66) and excellent (SQI = 67–74) categories found in the areal coverage of 41% and 2%, respectively, mainly associated with riverbeds and irrigation lands in the basin. The results indicated that moderate to good soil quality zones suit agricultural and plantation practices, while impoverished zones require targeted soil management strategies. However, a few limitations include the complexity of soil resource assessment and the need for periodic monitoring and field-based validation to ensure the accuracy and sustainability of soil quality over time. This study underscores the importance of integrating remote sensing and GIS techniques for soil quality assessment, providing critical insights for sustainable land management and environmental conservation. This approach provides a significant methodological advancement for sustainable soil resource management and can aid rural development.