Integrating Remote Sensing and GIS with Markov Chain Modeling for Land Use Change Analysis in Latur City, India

Abstract The city of Latur in Maharashtra state, India, has been witnessing fast urbanization, which has caused extensive changes in the land use due to emerging education hub. This research employs an integrated approach that uses both remote sensing and Geographic Information Systems (GIS) in addition to Markov chain modeling to evaluate changes in land use in Latur city during the period 2017-2024 and forecast changes up to 2033. Satellite imagery gathered by both Landsat and IRS satellites were used to map land use land cover which was in turn combined with GIS in order to assess land use land cover distributions and trends over time. A Markov chain model was subsequently applied to simulate land use transition and forecast future land use change. The findings indicate that the integrated methodology provided reasonable land use change predictions in Latur city; alongside a notable intensification of urban land cover, a notable decrease in agricultural land cover was observed. The research points out high conservation value areas and suggests land use practices to facilitate sustainable development so that urban expansion goes together with environmental measures and land transformation