According to traditional concepts, the movement of overlying strata and surface damage caused by coal mining in horizontal coal seams are symmetrical in terms of spatial distribution. However, in a lot of engineering practices, this symmetry has not been discovered. We often use the symmetry function to establish the profile prediction function of the surface damage, which results in a large difference between the prediction result and the actual situation. To solve this problem, this paper takes subsidence velocity as an example. Firstly, the spatial distribution functions of subsidence velocity on both sides were deduced theoretically. Through comparison, it is found that the change rate of the spatial distribution curve of the coal pillar side subsidence velocity is smoother than that of the goaf side and the subsidence velocity curves are skewed to the left. Secondly, based on the idea of lossless propagation of harmonic waves and idealizing the propagation environment, the spatial propagation relationship of surface subsidence velocity in the time domain is established. Then, the Box–Cox transform function is introduced to improve the normal distribution probability density function, and a new dynamic subsidence prediction model based on the Box–Cox transformation is obtained, which is suitable for the full mining stage. The model is tested by practical cases, the prediction accuracy is better than 7%, and the prediction results can meet the needs of engineering prediction accuracy (10%). The results of this research can enrich the existing subsidence prediction theory and provide theoretical and technical support for the prediction of dynamic surface damage caused by similar mining.

After large-scale land consolidation in hilly loess region of the Loess Plateau in China, land subsidence has a wide affecting area and considerable difficulty of prevention. Hence, large-scale, stabilized, and continuous deformation monitoring is urgently needed for slopes. In this study, land consolidation zone in the loess platform area of Weinan, China, was selected as the object, and the 30-scene Sentinel-1A data in Jan, 2018 to Dec, 2019 were analyzed. The mean annual velocity of ground deformation was from -6.19 mm∙a-1 to 3.86 mm∙a-1, and Accumulated deformation velocity was within -8.49 mm∙a-1 to 7.24 mm∙a-1. Accumulated deformation of land consolidation changed with the seasons changing. The interrelationship between the spatiotemporal variations in ground subsidence and the precipitation, ground water, loess engineering properties was also discussed. Accumulated deformation of land consolidation changed with the seasons changing. The precipitation accelerated the subsidence by unexpected strong precipitation reflects that the infiltration of rainwater can lead to compacted loess deformation which caused by moistening effect. Under varying ground water environment, external loads may lead to soil collapse, resulting in non-uniform land subsidence. Co-compression deformation of original loess and compacted loess is main influencing factors of subsidence. These findings have important implications and significant positive effects on the prevention of potential hazard such as subsidence and side slope slip.

Jiaozuo, located in the northwest of Henan Province, is one of the six major anthracite production bases in China. It is susceptible to land subsidence due to over a hundred years of mining history, continuous urbanization, frequent human activities, etc., which poses a great threat to urban infrastructure construction and people’s production and lives. However, traditional leveling techniques are not sufficient for monitoring large areas of land subsidence due to the time-consuming, labor-intensive, and expensive nature of the process. Furthermore, the results of conventional methods may not be timely, rendering them ineffective for monitoring purposes. With the continuous advancement of urbanization, land subsidence caused by groundwater extraction, ground load, and other factors in daily life poses a great threat to urban infrastructure construction and people’s production and lives. In order to monitor the land subsidence in the area of Jiaozuo city, this article uses the Sentienl-1A satellite data covering the city from March 2017 to March 2021 to obtain the accumulated land subsidence and the average land subsidence rate based on the Small Baselines Subset InSAR (SBAS-InSAR) technology. The results indicate that the surface of Jiaozuo area is generally stable, and there has been no large-scale settlement. The settlement rate is roughly between −1 mm/a and 2.2 mm/a, and the areas with obvious land subsidence are mainly located in the southeast and east of Jiaozuo city center. After field investigation, it was found that the land subsidence is mainly caused by two reasons: groundwater excessive mining and excessive surface load. In the northeast of Jiaozuo city, there is a certain uplift area. After on-site investigation, it was found that the area is connected to a tailings pond of an aluminum mine, constantly accumulating abandoned rock masses and sediment, causing an annual uplift rate of +6~+ 24 mm/a. The large-scale extraction of groundwater from farmland in the urban–rural integration area for irrigation of wheat has led to the settlement of buildings in the area with a rate of −11–−74 mm/a.

Ningdong coal base area located in northwestern China is one of the largest coal-producing bases in China. The aim of this work is to investigate a regional-scale mining subsidence over the Ningdong coal base area, by using both conventional and advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) methods. Fifteen L-band SAR images from ALOS-2 satellite and 102 C-band images from Sentinel-1A satellite spanning between November 2014 and July 2019 were used for the analysis. To increase the spatial extent of the displacement signal because of decorrelated effects, we modified the traditional Small Baseline Subset (SBAS) method to incorporate the coherence into the inverse problem, hereafter we call it coherence-based SBAS method. Instead of excluding decorrelated pixels present in the interferograms, we keep all the pixels in the time series analysis and down-weighted the decorrelated pixels with coherence. We performed the coherence-based SBAS method to both the two SAR datasets to obtain the subsidence rate maps and displacement time-series over the mining areas, and compared the results with that from the traditional stacking InSAR method. We evaluated the effectiveness of L-band and C-band DInSAR for monitoring mining subsidence by comparing differential interferograms and displacements derived from SBAS method between ALOS-2 and Sentinel-1A data. Compared to C-band, L-band SAR are less affected by phase aliasing due to large displacement gradients. The most significant subsidence was found at Maliantai mine with −264 mm/year detected by SBAS method from Sentinel-1 data. We validated the InSAR displacement accuracy by comparing both ALOS-2 and Sentinel-1 results with 18 GPS stations above five active mining regions. The average RMSE between InSAR and GPS measurements is 28.4 mm for Sentinel-1 data and 21 mm for ALOS-2 data. Our results demonstrate that the combined exploitation of L-band and C-band SAR data through both conventional and advanced DInSAR methods could be crucial to monitor ground subsidence in mining areas, which provides insights into subsidence dynamics and determine the characteristic surface response to longwall advance.