IntroductionLand suitability assessment is crucial for identifying areas with high potential for agricultural production, promoting sustainable land use, and addressing food security challenges. In the study area, approximately 70% of the population depends on agriculture for their livelihood. Therefore, assessing land suitability is essential for ensuring efficient land utilization and enhancing agricultural productivity. Consequently, Dharmapuri District, Tamil Nadu, India, was selected as the study area. To evaluate agriculture production, several key parameters were analyzed, including Land Use and Land Cover (LULC), Slope (S), Depth to water level (DL), Soil Texture (ST), Annual Rainfall (AR), pH, Nitrogen (N), Organic Carbon (OC),Temperature (T), Soil Moisture (SM), Distance to River (DR), Aspect (A), Elevation (E), Proximity to road (PRD), Normalized Difference Built up Index (NDBI) and Salinity (S). The selected parameters were chosen based on their proven relevance in previous land suitability assessment studies. The study aims to evaluate Land Suitability Zone (LSZ) using hybrid approaches Trapezoidal Fuzzy Numbers Analytic Hierarchy Process (TRFN‐AHP), remote sensing and Geographic Information System (GIS).MethodsThe parameter weights were calculated using the TRFN‐AHP method.Result and DiscussionBased on the results, the land suitability for agriculture production was classified as not suitable (8.86%), marginally suitable (20.70%), moderately suitable (24.88%), highly suitable (27.12%) and very highly suitable (18.44%). The results of land suitability index for agriculture production was validated using Receiver Operating Characteristic (ROC) curve. In ROC curve, the area under the curve value is 0.76 indicates good predictive accuracy in the study area. Overall, the results demonstrate that the hybrid approach combining TRFN‐AHP, remote sensing, and Geographic Information System provides an effective decision-support framework for assessing land suitability for agricultural production, facilitating sustainable land‐use planning and improved agricultural productivity.