Predicting changes in land use and land cover using remote sensing and land change modeler

Human activities and climate change exert significant influence on global land-use and land-cover (LULC) alteration. The integration of geo-spatial and remote sensing technologies is pivotal in comprehending these dynamics and formulating strategies for future natural resource management. This research is centered on the modeling of spatio-temporal trajectories of landscape transformation spanning from 1988 to 2018, with a forward-looking scenario up to 2040. By leveraging imagery from Landsat 5, LISS-3, and Sentinel 2A MSI, a detailed assessment of LULC changes was carried out for the Mashi Dam command (CMD) area in Rajasthan, India, covering a total expanse of 90.07 km2. Rigorous validation of the 2018 land cover map against ground-truth data ensured the reliability of predictions, which were subsequently utilized to forecast LULC patterns for 2031 and 2041. The analysis uncovered significant impacts on cropland, barren land, built-up areas, and scrub land throughout the study period. Notably, built-up areas, water bodies, and barren land exhibited substantial growth from 2008 to 2018, while cropland experienced a decline of 4.75% in the same timeframe. Projections indicate a further reduction in cropland by 2041, accompanied by an expansion of barren land. These results underscore the critical imperative for effective land management strategies to mitigate the conversion of cropland and scrub land into barren areas, thereby ensuring the sustainable utilization of agricultural resources in the region.