Open-pit coal mining poses a severe threat to regional ecological security. Rapid and accurate monitoring of ecological quality changes is crucial for regional ecological restoration. In this study, taking the Wujiata open-pit coal mine as an example, the Red-Edge Normalized Difference Vegetation Index (RENDVI), Salinity Index (SI-T), WETness index (WET), Normalized Differential Built Soil Index (NDBSI), Land Surface Temperature (LST), and Desertification Index (DI) were used to construct the Open-pit Mine Remote Sensing Ecological Index (OM-RSEI) through Principal Component Analysis (PCA). The ecological quality and restoration conditions of typical mining areas in arid and semi-arid regions were monitored and evaluated. The results shown that: (1) The contribution rates and eigenvalues of OM-RSEI were higher than those of conventional RSEI, OM-RSEI was more applicable in open-pit mining areas. (2) From 2018 to 2023, the OM-RSEI of the Wujiata open-pit coal mine showed a 'V' shaped fluctuation that was damaged and then gradually recovered. (3) The degraded area of Wujiata open-pit coal mine and its 5 km buffer zone accounted for 78.02%, and the improved area accounted for 19.16%. (4) The average Moran's I index of OM-RSEI in the study area was 0.8189, and the high-high clustering corresponded to the 'good' and 'excellent' distributions, while the low-low clustering corresponded to the 'poor' and 'less-poor' distributions. The OM-RSEI provided a new indicator for monitoring and evaluation of ecological restoration in open-pit coal mines, which can provide theoretical support for ecological restoration in open-pit coal mining areas.

An ancient landslide located in Xichang, China, that was reactivated by mining excavation and rainfall was investigated in this study. The volume of the reactivated landslide was approximately 1200 x 104 m3, thus posing a major threat to the mining area's safety. Field surveys, drilling, on-site monitoring, laboratory studies, and numerical analyses were performed to investigate the landslide deformation characteristics and reactivation mechanism. The reactivated landslide was divided into four zones: the leading-edge collapse, the sliding, the uplifting, and the traction sliding zones. X-ray diffraction and ring shear tests indicate that the sliding zone soil exhibits significant strength-weakening characteristics when exposed to water, and the residual cohesion and internal friction angle decrease by 26.9% and 28.9%, respectively, as the moisture content increases from 15 to 24%. Additionally, a three-dimensional numerical simulation was conducted to quantitatively analyze the stability evolution of the landslide. The results showed that the topographic, stratigraphic lithology, and sliding zone soil properties provided the basic conditions for landslide formation, while mining excavation and concentrated rainfall triggered landslide reactivation. Furthermore, a conceptual model characterizing the reactivation process was constructed, and the reactivation process was divided into five stages: leading-edge collapse, sliding, extrusion and bulging, deformation expansion, and accelerated creep deformation. This study provides a basis for understanding the reactivation mechanism of ancient open-pit mine landslides.

Open-pit mining seriously damages the original vegetation community and soil layer and disturbs the carbon cycle of vegetation and soil, causing instability in the mining ecosystem and decrease in the carbon sequestration capacity of the mining area. With the deepening of environmental awareness and the influence of related policies, the ecological restoration of open-pit mines has been promoted. The mining ecosystem is distinct owing to the disperse distribution of mines and small scale of single mines. However, the carbon sequestration capability of mines after ecological restoration has not been clearly evaluated. Therefore, this study evaluated the carbon sequestration capacity of restoration mines, taking the mines of the Yangtze River Basin in Jurong City, Jiangsu Province as the research objects. Firstly, the visual effects of the vegetation and soil in their current status were determined through field investigation, the methods for sampling and data collection for the vegetation and soil were selected, and the specific laboratory tests such as the vegetation carbon content and soil organic carbon were clarified. Meanwhile, the evaluation system consisting of three aspects and nine evaluation indexes was established by using the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE). The process of evaluation included the following: the establishment of the judgment matrix, calculation of the index weight, determination of the membership function, and establishment of the fuzzy membership matrix. Finally, the evaluation results of the restoration mines were determined with the 'excellent, good, normal and poor' grade classification according to the evaluation standards for each index proposed considering the data of the field investigation and laboratory tests. The results indicated that (1) the evaluation results of the mines' carbon sequestration capacity were of excellent and good grade at a proportion of 62.5% and 37.5%, which was in line with the field investigation results and demonstrated the carbon sequestration capacity of all the restored mines was effectively improved; and (2) the weights of the criterion layer were ranked as system stability > vegetation > soil with the largest value of 0.547, indicating the stability of the system is the main factor in the carbon sequestration capacity of the mines and the sustainability of the vegetation community and the stability of soil fixation on the slope. The proposed evaluation system effectively evaluates the short-term carbon sequestration capability of the restoration mining system according to the visual effects and the laboratory testing results, objectively reflecting the carbon sequestration capacity via qualitative assessment and quantitative analysis. The evaluation method is relatively applicable and reliable for restoration mines and can provide a reference for similar ecological restoration engineering.

The collapse of open-pit coal mine slopes is a kind of severe geological hazard that may cause resource waste, economic loss, and casualties. On 22 February 2023, a large-scale collapse occurred at the Xinjing Open-Pit Mine in Inner Mongolia, China, leading to the loss of 53 lives. Thus, monitoring of the slope stability is important for preventing similar potential damage. It is difficult to fully obtain the temporal and spatial information of the whole mining area using conventional ground monitoring technologies. Therefore, in this study, multi-source remote sensing methods, combined with local geological conditions, are employed to monitor the open-pit mine and analyze the causes of the accident. Firstly, based on GF-2 data, remote sensing interpretation methods are used to locate and analyze the collapse area. The results indicate that high-resolution remote sensing can delineate the collapse boundary, supporting the post-disaster rescue. Subsequently, multi-temporal Radarsat-2 and Sentinel-1A satellite data, covering the period from mining to collapse, are integrated with D-InSAR and DS-InSAR technologies to monitor the deformation of both the collapse areas and the potential risk to dump slopes. The D-InSAR result suggests that high-intensity open-pit mining may be the dominant factor affecting deformation. Furthermore, the boundary between the collapse trailing edge and the non-collapse area could be found in the DS-InSAR result. Moreover, various data sources, including DEM and geological data, are combined to analyze the causes and trends of the deformation. The results suggest that the dump slopes are stable. Meanwhile, the deformation trends of the collapse slope indicate that there may be faults or joint surfaces of the collapse trailing edge boundary. The slope angle exceeding the designed value during the mining is the main cause of the collapse. In addition, the thawing of soil moisture caused by the increase in temperature and the reduction in the mechanical properties of the rock and soil due to underground voids and coal fires also contributed to the accident. This study demonstrates that multi-source remote sensing technologies can quickly and accurately identify potential high-risk areas, which is of great significance for pre-disaster warning and post-disaster rescue.