Integrating Remote Sensing Techniques for the Assessment of Agricultural Suitability and Capability for Crop Cultivation in Bapatla District, Andhra Pradesh, India

Abstract

The present study assesses the agricultural suitability and capability for crop cultivation in Bapatla District, Andhra Pradesh, India by Integrating remote sensing techniques. Today, technological resources such as GIS and remote sensing can locate soil types, water resources, and the terrain of a place with great accuracy, even underground. Thus, the specificity in land use planning is increased, hence effective reconciliation of productivity with various conservation efforts nowadays underground. Geospatial and remote sensing methods were used to analyze the agricultural suitability and land capabilities of the Bapatla District in Andhra Pradesh. Factors used in the study include geology, geomorphology, soil type, LULC, slope, elevation, drainage and infrastructure to distinguish zones by their agricultural capabilities. The method uses a Weighted Overlay Approach (WOA) to place land into five groups: those not used for farming, Low Suitability, Medium Suitability, High Suitability and Very High Suitability. The maps produced from the suitability assessment were confirmed using the robust Soil Adjusted Vegetation Index (SAVI) method. The research indicates that about half of the district's area is highly suitable, especially the deltaic and alluvial plains with generous soil and mild slopes and these places are mostly planted with paddy, cotton and pulses. Where there is salinity, steep slopes or city development, special actions such as improving the soil or choosing other uses for the land are considered. It points out that irrigation is important in the district and taking care of water resources helps maintain its productivity as climate conditions and groundwater change. Results from the research suggest policymakers, farmers and land-use planners what they can do to choose crops wisely, use resources more efficiently and address environmental risks. Proper use of land resources can help the district avoid soil damage, secure enough water and increase produce. The combination of GIS and remote sensing technologies is also potential for monitoring real-time crop condition, land use change, and soil moisture to facilitate dynamic decision-making. Verification of suitability classes of SAVI indices confirms the dependability of the approach and proposes its extension to other agriculturally diverse locations.