Monitoring ecosystem restoration of multiple surface coal mine sites in China via LANDSAT images using the Google Earth Engine

The restoration of surface mining (open-cast) sites is key to meeting global ecosystem restoration targets. With the improving of data availabilities and technologies, it has become possible to expand restoration monitoring from single to multiple mine sites on a large scale. Based on the MODIS global disturbance index (MGDI), this study proposes a mine landscape restoration index (MLRI), by coupling the LST and EVI to simultaneously monitor the restoration of multiple mine sites. Restoration areas were identified by MLRItime-series analysis and classified into significant consistent increase (SCI) andsignificant anti-consistent increase (SAI) areas. The restoration effects of 46 surface coal mine sites located in the ecologically fragile northwestern region of China from 2000 to 2019 were assessed based on 3,675 LANDSAT images from the Google Earth Engine. Results show that the MLRI was effective at identifying restoration areas and processes, and this effectiveness was validated by high-resolution images and field investigations of mine samples. The overall percentage of restored area for mines that started mining before 2000 was 55.01% ; for mines that starting mining after 2000, 33.68%. According to the differences of SCI and SAI area percentages, 46 mine sites were classified into three clusters, with 13, 11, and 22 mine sites, respectively. The mine sites with high restoration percentage are located mainly in Hailar and Shanbeimengnan regions. This study provides a new approach for monitoring the restoration effects of multiple mine sites and informs government managers about developing mine restoration programs and sustainable mining development plans.

Automated summary

Surface mining restoration is crucial for global ecosystem restoration goals, and this study introduces a new method, MLRI, to monitor the restoration effects of multiple mine sites. By analyzing 3,675 LANDSAT images, the study shows that the MLRI effectively identifies restoration areas and processes, providing valuable information for government managers in developing mine restoration programs.