Surface mining identification and ecological restoration effects assessment using remote sensing method in Yangtze River watershed, China

Abstract

Abstract Mineral resource development is necessary for economic growth, but its negative impacts on land, ecology, and the environment are significant and cannot be ignored. Identification the mine restoration process in a large scale is challenging without specific mining location information. Besides, how to quantitatively evaluates the ecological restoration effects became important for management and supervision. Here, we propose a systematic workflow that utilizes open-source remote sensing data to identify and assess large-scale surface mining areas' restoration status and ecological quality without prior knowledge of mine locations, and implemented in Yangtze River region, the largest watershed area in China. The process includes: (1) extracting surface mining areas using masking, morphological operations, and visual interpretation techniques; (2) constructing time-series of Bare Surface Percentage (BSP) for each mining area on the Google Earth Engine platform to distinguish between abandoned and active mines and examine their restoration rates; (3) constructing the Remote sensing Ecological indicator for Mining areas (REM) to quantify ecological quality and its temporal changes. The results show that: (1) the proposed method effectively identifies surface mining areas with higher boundary delineation accuracy and smaller omission numbers; (2) a total 1,183 mine sites were identified in the study area, of which 381 abandoned mines showed a significant decreasing trend in BSP from 2016 to 2021, with a median decreasing from 98% in 2016 to 81% in 2022, indicating better vegetation recovery during this period. (3) the REM of abandoned mines generally showed a stable upward trend from 2016 to 2022, and vice versa. This study provides a systematic solution for identifying surface mining areas and monitoring restoration scope and ecological quality on a broader scale. It can be extended to other areas and support further ecological restoration decision-making.