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Abstract Human population growth, movement, and demand have a substantial impact on land use and land cover dynamics. Thematic maps of land use and land cover (LULC) serve as a reference for scrutinizing, source administration, and forecasting, making it easier to establish plans that balance preservation, competing uses, and growth compressions. The objective of this study is to identify the changeover of land-use changes in the Bhavani basin for the two periods 2005 and 2015, as well as to forecast and establish potential land-use changes in the year 2025 and 2030 by using QGIS 2.18.24 version MOLUSCE plugin (ANN-Multi layer perception) model.The five criteria, such as DEM, gradient, aspect, distance from the road and river, and built-up density, are used as spatial variable maps in the processes of learning in ANN-Multi layer perception to predict their influences on LULC between 2005 and 2010 and it was found that DEM, distance from the road and river, and built-up density have significant effects. The projected and accurate LULC maps for 2015 indicate a good level of accuracy, with an overall Kappa value of 0.69 and with a percentage of the correctness 76.28 %. ANN-Multi-layer perception model is then used to forecast changes in LULC for the years 2025 and 2030 which shows significant rise in cropland and built-up areas, by 20 km2 and 10 km2 respectively. The findings assist farmers and policymakers in developing optimal land use plans and better management techniques for the long-term development of natural resources.
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