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Underground mining activity has existed for more than 100 years in Nansi lake. Coal mining not only plays a supporting role in local social and economic development but also has a significant impact on the ecological environment in the region. Landsat series remote sensing data (1988~2019) are used to research the impact of coal mining on the ecological environment in Nansi lake. Then support vector machine (SVM) classifier is applied to extract the water area of the upstream lake from 1988 to 2019, and ecological environment and spatiotemporal variation characteristics are analyzed by Remote Sensing Ecology Index (RSEI). The results illustrate that the water area change is associated with annual precipitation. In terms of ecological quality, the area of poor ecological quality areas increased by 101.782 km 2 , while the area of good and excellent quality areas decreased by 218.988 km 2 from 2009 to 2019. So compared with 2009, the ecological quality of the lake is worse in 2019, and then the reason for this change is due to large-scale underground mining. Therefore, the coal mines from the natural reserve may be closed or limited to the mining boundary for protecting the lake's ecological environment., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Abundant coal resources also exist under rivers and oceans besides lands. Underwater mining has a history of more than 100 years. For a long time, all the technological measures in the mining process are to protect the mine itself, and mining engineers seldom consider the non-pollution damage to the ecological environment caused by mining subsidence. Thus, mining under a medium-sized reservoir is selected as a case study in this paper, the damage hazard of underground mining on a reservoir's ecological environment is researched based on reservoir area variations from Landsat remote sensing and subsidence basin volume calculations. The results illustrate the subsidence basins by large-scale mining under a reservoir can alter the original topography of the reservoir bottom, which will form new stagnant water basins, and also a large water area will be dried up. The non-pollution damage is difficult to be recovered and even irreversible, especially for small- and medium-sized reservoirs. The subsidence basin volume was 3.04 × 107 m3 until 2018, which was more than the original reservoir capacity. Most of the water would flow into the subsidence basin and cause the reservoir water to dry up. The essence of non-pollution damage hazard is bottom subsidence caused by underwater mining. Therefore, governments should limit mining activities or close the coal mines for protecting the ecological environment of the reservoir. [ABSTRACT FROM AUTHOR]

Underground extraction can be roughly classified into three types, i.e., subcritical, critical, and supercritical extraction, in accordance with the geological conditions in the overburden and the geometry of mined-out areas. In 2016, we proposed an approach based on the interferometric synthetic aperture radar (InSAR) technique and the probability integral method (PIM) for the cost-effective prediction of 3-D mining-induced displacements (abbreviated as InSAR-PIM). Due to the inherent assumption of critical extraction in the PIM, the InSAR-PIM method performs well in predicting the 3-D displacements caused by critical and/or supercritical extraction, but poorly for subcritical extraction. In this paper, we first propose a generalized PIM (GPIM) by modifying the traditional PIM with a simplified Boltzmann function. We then replace the PIM of the InSAR-PIM with the proposed GPIM to develop an extension of InSAR-PIM (referred as to InSAR-GPIM). The InSAR-GPIM was tested in the Qianyingzi coal mining area, China. The results show that the InSAR-GPIM-predicted horizontal and vertical displacements caused by subcritical, critical, and supercritical extraction agree well with the in situ observations, with average root-mean-square errors of about 0.032 and 0.050 m, respectively. These accuracies represent improvements of 60.9% and 59% when compared with the accuracies predicted by the InSAR-PIM in the horizontal and vertical directions. The results indicate that the InSAR-GPIM is capable of accurately predicting 3-D mining-induced displacements under different extraction conditions (i.e., subcritical, critical, and supercritical extraction), and it performs much better than the InSAR-PIM in the case of subcritical extraction. It is therefore believed that InSAR-GPIM will have a wider scope of applications than the previous InSAR-PIM. [ABSTRACT FROM PUBLISHER]

Mining-related deformations are the direct cause for most of geohazards (e.g., landsides, building damage, and aquifer broken). Limited by available number of current space-borne SAR sensors and their near-polar flighting configuration, previous InSAR methods based on multi-track SAR datasets are hardly to performed to accurately retrieve mining-induced 3-D time-series displacements. This paper presents a method for retrieving mining-induced 3-D time-series displacements from single-track SAR datasets by fusing a mining-related prior deformation model. Compared with the previous multi-track SAR-based methods, the presented method has much less requirement on SAR data and can significantly improves the accuracy of estimated time-series deformations in the north direction. Finally, 13 ascending TerraSAR-X images over Yulin coal mining area, China, were selected to test the proposed method. [ABSTRACT FROM AUTHOR]