Integrating Remote Sensing and GIS for Sustainable Soil Management: A Case Study of Jamtara District, Jharkhand

This study assessed the spatial variability of key soil physicochemical properties in Jamtara district, Jharkhand, using field sampling and geospatial techniques to support sustainable agricultural planning. Soil analysis of 15 sites revealed moderate nitrogen (mean: 305.01 kg/ha) and soil organic carbon (0.71%), but widespread phosphorus (mean: 11.67 kg/ha) and potassium (mean: 188.15 kg/ha) deficiencies, especially in northern, central, and southeastern zones. Predominantly acidic soils (mean pH 5.53) highlight the need for liming to improve nutrient availability. Using Inverse Distance Weighting (IDW) interpolation and weighted summation, soils were classified into five quality grades; Grade III (moderate fertility) was most extensive (~ 37%), followed by Grades II and IV, with limited areas of high (Grade I) and low (Grade V) quality. Block-wise analysis revealed significant variability, with high-quality soils concentrated in Jamtara, Narayanpur, and Kundahit blocks, while Fatehpur showed predominantly moderate to low quality soils. Integration with Land Use/Land Cover (LULC) data demonstrated that higher-grade soils correlate with agricultural and fallow lands, whereas lower-grade soils align with barren and degraded lands. The soil quality map achieved 85.71% validation accuracy, confirming its reliability for land management. These findings highlight how parent material, topography, and land use affect soil health and show that integrating geospatial tools with traditional soil testing supports precise management and sustainable farming in the area.