Decadal assessment and future prediction of land use land cover changes in the Upper Yamuna basin using CA-ANN modeling

Land Use Land Cover (LULC) changes in rapidly developing regions substantially influence natural and socio-environmental systems. This study assesses decadal LULC transformations in the ecologically sensitive Upper Yamuna Basin, Uttarakhand, India, integrating remote sensing (Landsat 8 and Sentinel-2 A), Digital Elevation Model (DEM), and GIS tools. The Cellular Automata-Artificial Neural Network (CA-ANN) model was employed to simulate LULC changes for 2023 and project future scenarios for 2040, achieving an overall accuracy exceeding 87% and kappa coefficients above 0.87. Key physiographic factors, including slope (67.79% gentle to moderate) and drainage patterns, were analyzed to understand hydrological and topographical impacts. Results reveal a significant increase in settlement area from 8.06 km² (0.34%) in 2013 to 38.59 km² (1.63%) in 2023, projected to reach 61.47 km² (2.60%) by 2040, primarily at the expense of forests (declining from 54.20% to 49.82% in 2023, with further decrease to 46.74% in 2040) and agricultural land (from 3.19% to 1.32% in 2023, projected to further decline). Water bodies also decreased significantly from 58.07 km² (2.45%) to 30.64 km² (1.29%). Temperature trends indicate a warming climate with maximum temperatures increasing by 0.0421 °C per decade over 32 years, exacerbating environmental stress. These extensive LULC changes contribute to increased vulnerability to floods, erosion, and natural hazards amid rapid urbanization. The study highlights the urgent need for sustainable land management and policy interventions to preserve ecological integrity and mitigate the impacts of climate change in this Himalayan basin.