Spatiotemporal change analysis of environmental quality in mining areas based on long-term landsat images

Abstract

The mining of ion-adsorption rare-earth elements (REE) in South China has caused severe ecological disturbances in mining areas. Therefore, environmental monitoring and evaluation of REE mining areas have become a prerequisite for the sustainable development of the ion-adsorption REE industry. In this study, a remote sensing-based ecological index (RSEI) model was used to evaluate changes in the environmental quality of REE mining areas. Thirty Landsat images from 1986 to 2019 were used in a case study of the Lingbei mining area in Dingnan County, China. Google Earth images were used for visual interpretation and comparison with the classification results of different types of land damage and restoration for different disturbance levels. The random forest (RF) method was used for classification, and the underlying mechanism of the environmental changes was discussed. The results show that the RSEI accurately reflects the environmental quality of the REE mining areas. The analysis of the spatiotemporal distribution of the environmental quality in the REE mining areas shows that since 1986, mining techniques, such as pool leaching, heap leaching, and in-situ leaching, resulted in surface vegetation removal and topsoil stripping, causing extensive environmental damage. After 2011, the environmental quality was slowly restored due to the optimization of mining technology and the government’s focus on environmental management, resulting in the recovery of mining sites. The changes in the environmental quality of the REE mining areas in different disturbance states indicate that the area affected by human disturbance is 15.44 km2, accounting for 44.43% of the total mining area and 16.31% of the area exhibits serious impacts on the ecological environment. The proposed method provides a quantitative approach to describe the evolution of environmental quality in the mining area over the past 34 years, providing a scientific basis for the sound management of the mining areas to promote the regional sustainable development.