GIS-based comparative analysis of AHP and MIF for agricultural land suitability in drought-prone Bankura district, Rarh Bengal

Assessing agricultural land suitability is essential for sustainable land-use planning and food security in drought-prone regions. This study evaluates agricultural land suitability in the Bankura district of Rarh Bengal using an integrated GIS-based Multi-Criteria Decision-Making (MCDM) framework and compares the performance of the Analytical Hierarchy Process (AHP) and Multi-Influencing Factor (MIF) techniques. Fifteen thematic layers representing topographic, pedological, hydrological, climatic, and infrastructural conditions were weighted and integrated to classify land into four suitability categories: very highly suitable (S1), highly suitable (S2), moderately suitable (S3), and marginally suitable (S4). The results indicate that approximately 38.5% (AHP) and 38.4% (MIF) of the district fall under highly to very highly suitable categories, predominantly in the eastern and southern blocks, characterized by gentle slopes, favourable soil texture, adequate soil fertility, and better irrigation accessibility. In contrast, 8.0% (AHP) and 4.4% (MIF) of the area, mainly along the western and north-western blocks, were identified as marginally suitable due to steep terrain, poor soil properties, limited drainage density, and recurrent water scarcity. Validation using ground reference data demonstrates that the MIF model outperformed AHP, achieving higher overall accuracy and agreement statistics (overall accuracy = 88%, Kappa = 0.85, AUC value = 0.803) compared to AHP (overall accuracy = 83%, Kappa = 0.78, AUC value = 0.722). The findings highlight the robustness of the MIF approach for agricultural suitability assessment in semi-arid environments and provide a spatially explicit decision-support framework for block-level agricultural planning, irrigation prioritization, and climate-resilient land management in drought-prone regions.