Anthropogenic disturbances resulting from extensive mining activities in tropical regions pose significant threats to native land use, leading to deforestation, biodiversity loss, climate change impacts, environmental degradation, health risks, landscape fragmentation, compromised ecological security, and societal well-being. Monitoring Land Use and Land Cover Change (LULCC) becomes imperative for evaluating the extent and nature of land degradation in mined areas. This study examined and compared land cover change patterns across three coalmined sites: Sohagpur (Site-I), Jamuna & Kotma (Site-II), Bishrampur (Site-III) in Central India over three decades using Landsat satellite imagery from 1994, 2007, and 2022. The Maximum Likelihood (ML) algorithm, within a supervised classification framework, was applied to discern mining impacts on decadal land use shifts. The analysis revealed that 7.32% to 17.61% of forest cover, 5.0% to 10% of water bodies, and 3% to 5% of agricultural lands were lost due to mining activities, with Site 3 and Site 2 experiencing greater losses compared to Site 1. Overall, native land cover diminished by 35% between 1994 and 2022. Indices including Soil Index, Climate Index, Terrain Index, Land Utilization Index, and Vegetation Index were derived to assess land degradation patterns. These indices were integrated using a weighted index model in ArcGIS to generate the Land Degradation Vulnerability Index (LDVI). Vulnerability notably escalated with mining expansion, particularly pronounced at Site 3 (Bishrampur) and lower at Site 1 (Sohagpur). The 'extremely vulnerable' class encompassed a substantial area (25-40%), while the 'low vulnerable' class was less than 5% across all sites. This study's comprehensive analysis aids policymakers, planners, and managers in prioritizing targeted interventions and implementing sustainable land management practices for ecorestoration, aligning with the goal of Zero Net Land Degradation (ZNLD) in coal-mined landscapes.