Assessing ecological restoration in an alpine mining region on the Qinghai-Tibet Plateau: A multi-source remote sensing and modeling approach

The Muli mining area, the largest coal mining region on the Qinghai-Tibet Plateau, China, serves as a critical ecological buffer zone for the Yellow River Basin. However, prolonged unsustainable mining activities have led to severe environmental degradation, including vegetation ecosystem deterioration and disruption of river systems and wetlands, heightening concerns over ecological security in alpine grassland mining regions. In response, ecological restoration in the Muli mining area has been elevated to a national strategic priority. To comprehensively assess restoration effectiveness, this study integrates multi-source datasets—including ground-based meteorological observations, soil properties, and remote sensing imagery—and applies the Carnegie-Ames-Stanford Approach (CASA) and InVEST models. Within a framework designed for evaluating the ecological benefits of major restoration projects, we quantify both the magnitude and spatial heterogeneity of ecological recovery in the Muli mining area from 2001 to 2023, focusing on changes in ecosystem quality and ecosystem services. Additionally, machine learning algorithms are employed to identify and interpret the key natural drivers influencing restoration outcomes. Our results show that: (1) Since 2014, ecosystem quality and services have exhibited an overall stabilizing and improving trend, although localized degradation persists in certain areas. (2) The overall degree of recovery is relatively high, with notable project effectiveness. Specifically, areas showing varying degrees of improvement account for 78.31%, 66.36%, and 96.07% of the total area in the Jiangcang, Juhugeng, and Duosuogongma mining sites, respectively. (3) Elevation, solar radiation, and temperature are the primary natural factors controlling the spatial pattern of ecological recovery. These findings not only provide a scientific reference for evaluating restoration efforts in the Muli mining area but also offer a transferable methodological template for assessing ecological recovery at other mining sites in similar high-altitude environments.