A GeoAI Approach for Land Use Land Cover Change Analysis of Bhilwara District, Rajasthan
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Abstract
In order to comprehend and measure changes in land use and land cover (LULC) in the Bhilwara district of Rajasthan, India, this study summarizes previous research on the use of Geographic Artificial Intelligence (GeoAI) and associated geospatial methodologies. Higher computational structures that effectively manage massive spatial inputs and generate precise maps of dynamic landscapes are required due to the fast growth of urban and agricultural areas in semi-arid Indian districts. This summary explains how GeoAI, which combines AI models with remote sensing and geographic data, improves conventional techniques for identifying, categorizing, and projecting LU/LC changes across time. The theoretical underpinnings of GeoAI, recent case studies in Bhilwara and related areas, methodological developments, and future research prospects are some of the major topics covered.
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