The identification of degradation hotspots and optimized agricultural input deployment depends heavily on clear knowledge of soil property spatial distributions across different areas for guaranteeing soil fertility in the long term. GIS and remote sensing methods form the bridge to determine how soil quality changes across different land-use regions in Maharashtra, India. The research team applies sophisticated interpolation models to enhance both the predicted values in addition to spatial precision. Field researchers acquired soil samples from agricultural, urban, forest and barren land areas to measure pH levels and determine organic matter percentages and nitrogen (mg/kg), phosphorus (mg/kg), potassium (mg/kg) concentrations in the tested samples. Different landscapes demonstrate significant differences in their soil fertility levels according to the data. Soils from forest regions support the best natural soil renewal mechanism because they contain 5% organic matter while barrens experience extreme degradation because they have 1.5% organic matter due to soil erosion and vegetation loss. The nitrogen level in agricultural land reaches 96 mg/kg but proper management of phosphorus and potassium remains essential. The element of nitrogen appears at above-average levels (99 mg/kg) in urban soils due to industrial waste discharge but causes nutrient imbalance problems which negatively impact soil vitality. The study proves that implementing GIS system-based mapping for soil quality represents an effective method in sustainable land-use planning practices. The system helps policymakers establish soil degradation trends through which they can create precision agriculture programs together with conservation methods.