This study focused on the Jinjie mining area by addressing the severe resource and environmental issues arising from excessive coal mining in Shenmu County, Northwest China. Multi-source remote sensing data from GF-1 and Landsat 8 OLI were utilized in this study. Specifically, the fused remote sensing ecological index (FRSEI) was constructed to conduct a detailed evaluation and analysis of the eco-environmental quality in the mining area from 2013 to 2023. The results indicated that the overall eco-environmental quality of the Jinjie mining area exhibited a trend of initial improvement, followed by degradation, and then improvement again over the decade. The eco-environmental quality of the mine pits and their surrounding areas was significantly lower than the overall level, confirming the destructive impact of coal mining on the eco-environment. Meanwhile, as the study area, Shenmu County is actively utilizing coal mining subsidence areas to develop the photovoltaic power generation industry, aiming to achieve green and low-carbon transformation. Although the construction of photovoltaic power plants initially led to the degradation of the condition of vegetation and the FRSEI, both gradually improved after the plants were operational. Furthermore, by comparing the FRSEI with the remote sensing ecological index (RSEI) calculated solely using Landsat 8 OLI data, we found a high degree of similarity between the two, thereby validating the stability and accuracy of the FRSEI. This study not only provides high-precision data support for eco-environmental monitoring in mining areas but also highlights the potential of multi-source remote sensing data fusion technology in improving monitoring accuracy, further providing a scientific basis for formulating sustainable development strategies specifically for the eco-environment in mining areas.

To reveal the impacts of long-term coal mining on groundwater flow fields and the environment, the Jinjitan Coal Mine in Shaanxi Province, China, was selected as the study area. A systematic investigation on the evolution of flow fields and migration of pollutants under long-term coal mining impact was conducted using methods including Self-Organizing Map (SOM) clustering analysis, water isotope analysis, and numerical simulation. The results show that groundwater in the study area is mainly derived from atmospheric precipitation, and the mine water is a mixture of 55% coal seam water and 45% Quaternary groundwater; long-term coal mining has led to two types of Quaternary groundwater level changes (stable and continuously declining); The groundwater level of the Jurassic aquifer shows an overall decline. However, where the aquifer is locally recharged by the Quaternary groundwater, the groundwater level shows a decline-then-rise variation. The overall groundwater flow field maintains the pattern of runoff from northeast to southwest and discharge into the Yuxi River, with no local or regional groundwater depression cones observed; numerical simulation results indicate an average groundwater level drop of 1.36 m over an 10-year period, with a maximum decrease of 4.89 m; the migration scope of oxygen demand and petroleum pollutants caused by domestic sewage pond leakage is limited, their maximum long-term (3650 d) migration distances are 253.47 m and 254.27 m, respectively, and their concentrations are far below the limit of the Class III groundwater quality standard. The research findings provide a scientific basis for the environmental protection, rational development, and utilization of groundwater in the Jinjitan Coal Mine area.