GIS-based multi-criteria crop land suitability assessment using the multi-influencing factor approach in the drought-prone region of Rarh Bengal

Identifying suitable farmland is crucial for sustainable crop production and enhancing climate resilience in drought-prone regions. Therefore, this study developed a GIS-based Multi-Influencing Factor (MIF) framework to evaluate the suitable land for four major crop groups (cereals, pulses, oilseeds, and cash crops) in the drought-prone Bankura district using sixteen physiographical, pedological, hydro-climatological, and infrastructural criteria. The analysis revealed that approximately 38.00% of the district is highly to very highly suitable for cereals, 37.57% for pulses, 45.00% for oilseeds, and 38.04% for cash crops. These highly suitable areas are concentrated in the eastern and southern parts of the district, where favourable topography, relatively higher rainfall, suitable soil texture, improved groundwater availability, and better irrigation infrastructure support agricultural productivity. Conversely, the western and northwestern plateau margins exhibit moderate to marginal suitability due to higher elevations, steeper slopes, coarse-textured soils, lower cation exchange capacity, limited irrigation facilities, and poor accessibility to agricultural markets. Among the evaluated factors, rainfall, soil texture, groundwater availability, irrigation intensity, and elevation were identified as the most influential determinants of crop suitability. Model validation using field observations demonstrated robust predictive performance, with overall accuracies of 0.85, 0.81, 0.79, and 0.88 for cereals, pulses, oilseeds, and cash crops, respectively, and corresponding Kappa coefficients of 0.79, 0.75, 0.73, and 0.84, indicating substantial to almost perfect agreement with the reference data. The resulting suitability maps provide a reliable spatial decision-support tool for crop planning, irrigation prioritization, and sustainable agricultural land management in drought-prone regions with similar environmental conditions.