Prediction of Land Use Land Cover Change Using a Coupled CA-ANN modeling in Dhanusha district of Nepal

Land cover refers to the physical cover that is visible on the surface of the earth, whereas land use refers to how individuals use the land. Remote sensing (RS) and Geographical Information Systems (GIS) are proven tools for assessing the LULC change. We used Landsat 5, 8, and 9 satellite images and employed the Maximum Likelihood Supervised Classification algorithm to identify the LULC types and detect changes in the Dhanusha district of Nepal. The change prediction was done using the QGIS 2.18 version MOLUSCE plugin. The four criteria, namely elevation, slope, distance from the road, and built-up were used as spatial variable maps in the learning processes in CA-ANN to predict the LULC of 2033. We assessed five major LULC classes viz. Forest, Water, Cultivated land, Settlement, and barren land. We discovered that the Dhanusha district lost 173.4ha and 300.9ha of its forests, 1381.55ha and 1864.84ha of its cultivated land, and 303.21ha and 452.04ha of its water bodies over 20 years, from 2003 to 2013 and 2013 to 2023 respectively. Significant losses were absorbed by growing urbanized areas and barren land, which expanded by 1157.19ha and 700.95ha in 2003–2013 and by 1674.03ha and 943.8ha in 2013–2023 respectively. By 2033, forest cover is predicted to drop to 22.67%, water bodies to 0.6%, and barren land to 3.16%, with urbanized areas rising to 6.08%. Urban planners are recommended to incorporate nature nature-based solutions for adaptation and mitigation plans for cities that are supported by reliable funding and policy.