Assessment of crop suitability analysis using AHP-TOPSIS and geospatial techniques: A case study of Krishnagiri District, India

The cropped area of Krishnagiri district is about 37 % of the total geographical area, and due to the utilization of non-agricultural purposes (8.2% of agricultural land) it is mandatory to increase the agricultural production to feed the people. So, this study has been planned to find the agricultural suitability and crop suitability of the Krishnagiri district using AHP-TOPSIS and GIS techniques. In this study, three main limiting factors, such as climate, soil, and topographical parameters (Annual average rainfall, Annual average temperature, slope, pH, Electrical conductivity (EC), Soil organic carbon (SOC), available NPK, and soil texture), were used as criteria for the suitability of crops. All criteria maps were generated using Arc info 10.4 software. The AHP used to estimate the weight and TOPSIS (Technique for Order of Preference by Similarity to an Ideal Solution) approach was assign the rank of each criterion for the suitability analysis. Based on the relative closeness to the ideal solution(pi), the generated crop suitability maps were categorized into five classes, namely “highly suitable (S₁), moderately suitable (S₂), marginally suitable (S₃), and not suitable (N)”. The results revealed that, crop suitability maps finds that that maize, field bean, cluster bean, groundnut, pomegranate, lemon, and lemongrass were highly suitable for the Krishnagiri district. Rice, cotton, sugarcane, sunflower, and cashewnut were moderately suitable, and vanilla was unsuitable. This study will guide farm managers and land policymakers in making decisions and assist farmers in selecting crops that are highly suitable for achieving potential yield and profit.