Machine Learning–Driven Analysis of Rangeland Influence on Lake Water Conditions Using Multisensor Sentinel‐2 and Landsat 8 Integration

ABSTRACT Rapid urbanization in cities, has led to significant land use land cover (LULC) transformations with implications for environmental sustainability. This study examines LULC changes and spectral indices dynamics between 2016 and 2024 using Landsat imagery. Nine spectral indices were computed: NDVI, NDWI, MNDWI, NDBI, BSI, SAVI, MSAVI, LSWI, and LULC classification. Results revealed substantial built‐up area expansion of 425.3 km 2 (5.0% increase), primarily converting rangeland which decreased by 232.7 km 2 (2.7% reduction). Water bodies declined by 93.9 km 2 (1.1%), while cropland remained stable due to protection policies. Vegetation indices showed spatial redistribution with localized decreases in urban expansion zones and increases in restoration areas. NDBI increased significantly in developing regions, while BSI unexpectedly decreased, suggesting vegetation recovery despite urbanization. The study provides crucial insights for sustainable urban planning and environmental management in rapidly urbanizing cities.