Post-mining Ecological Disturbance-Recovery Trajectories and Resilience Assessment of Open-pit Coal Mines Based on Long-term Remote Sensing Indices

Open-pit coal mining exerts long-lasting and cumulative disturbances on terrestrial ecosystems during the post-mining stage, and the associated environmental impacts and recovery processes exhibit pronounced temporal persistence and spatial heterogeneity. Long-term remote sensing monitoring is therefore essential for understanding post-mining ecosystem dynamics and evaluating restoration outcomes. In this study, we constructed a Mining Landscape Disturbance Index (MLDI) and a Mining Landscape Recovery Index (MLRI) based on the Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST). Combined with the LandTrendr algorithm, post-mining disturbance-recovery trajectories of 46 open-pit coal mines in northern China were systematically monitored and analyzed over the period 1984-2025. Using disturbance and recovery trajectory information extracted by LandTrendr, ecosystem resilience was comprehensively assessed from three dimensions: resistance, recovery capacity, and stability. Based on disturbance magnitude and recovery magnitude, the 46 mining areas were classified into four types: high disturbance-high recovery (HH), high disturbance-low recovery (HL), low disturbance-high recovery (LH), and low disturbance-low recovery (LL). The results indicate that the median MLRI values of all four types show an overall increasing trend at the interannual scale, suggesting a general post-mining recovery tendency of ecosystems during the study period, although significant differences exist in recovery levels and recovery rates among different types. Meanwhile, the median MLDI values also exhibit a continuous upward trend, reflecting persistent cumulative degradation pressure on mining ecosystems under long-term mining activities. Distinct multidimensional differentiation patterns were observed among the four disturbance-recovery types in terms of resistance, recovery capacity, and stability. This study provides an effective remote sensing-based framework for monitoring long-term post-mining ecological dynamics and offers scientific support for differentiated environmental management and ecological restoration strategies in post-mining areas.