Heavy metal pollution in soils, especially in mineral aggregation areas, presents significant sustainability challenges affecting ecosystem health and human well-being. This study conducted source apportionment and risk analysis of soil heavy metals in Datian County, South China, to promote sustainable land use and pollution mitigation. We collected 103 surface soil samples (0–20 cm) from a typical mineral aggregation area and analyzed the concentration distributions of heavy metals using geostatistical methods. The geoaccumulation index (I_geo) and potential ecological risk index (RI) were employed to evaluate pollution levels and ecological risks. Our findings reveal that heavy metal concentrations substantially exceeded Fujian Province’s background values, with Cd exhibiting severe pollution levels. Cd, Pb, and Cu pose moderate to high ecological risks. Major pollution sources include metal smelting enterprises, soil parent materials, mixed sources of mineral extraction and traffic pollution, atmospheric deposition, and agricultural pollution. Their contribution rates were found to be 15.66%, 17.72%, 38.32%, 8.25%, and 20.05%, respectively. Utilizing principal component analysis (PCA) and positive matrix factorization (PMF) models integrated with geostatistical methods, this study provides robust source identification and highlights sustainable practices for soil management. The results offer a scientific basis for developing strategies to mitigate heavy metal pollution and enhance environmental sustainability in the region.

Vegetation serves as a crucial indicator for monitoring ecosystems and plays a vital role. This paper employs remote sensing techniques to monitor vegetation in Taojiang County, aiming to explore the effects of ecological restoration projects on vegetation in mining areas. The study uses the Theil–Sen median slope and Mann–Kendall tests to analyze the trend of fractional vegetation coverage (FVC) changes in mining areas, the CASA model to estimate net primary productivity (NPP) in mining areas, and random forest models to assess the importance of influencing factors. Overall, FVC in the study area has slightly increased from 0.729 to 0.847. The FVC in mining areas reached its lowest point at 0.423 in 2011 and recovered to 0.718 in 2023 due to artificial restoration. From 2004 to 2011, FVC in mining areas showed an overall downward trend, while from 2013 to 2023, it showed an overall upward trend. The trend of NPP in mining areas is similar to that of FVC, with NPP being 939.8 g/m² y in 2004, 2011, and 2020, 788.3 g/m² y in 2011, and 855.7 g/m² y in 2020. Results from the random forest simulation indicate that the primary factor affecting FVC in mining areas is distance from roads, followed by elevation. This study finds that ecological restoration projects play a significant role in achieving ecological recovery and sustainable development in mining areas.