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Accurate monitoring of mining three-dimensional deformation plays an important role in analyzing the subsidence mechanism and assessing potential geological hazards in the mining area. This paper combines TerraSAR-X and RADARSAT-2 heterogeneous SAR images employing MSBAS technology to obtain the three-dimensional time-series of deformation of the 132 610 working face in the Fengfeng mine from December 2015 to February 2016. The monitoring results show that the maximum surface subsidence and the subsidence rate during the monitoring period were –243 mm and 4.42 mm/day, and the maximum east-west horizontal movement was –80~30 mm. The surface subsidence basin is in the active stage, which is prone to pose a threat to the safety of the surrounding structures. Comparison with the leveling data shows that the root-mean-square deviation of the vertical deformation obtained by MSBAS technology is 10.7 mm, and the accuracy can reach the centimeter level. Meanwhile, based on the vertical deformation obtained by MSBAS technology, combined with the proportionality relationship between horizontal movement and tilt, the north-south horizontal movement was estimated as –80~70 mm, which provided a solution for obtaining the north-south horizontal movement of the mining area by InSAR. Analysis of the three-dimensional time-series of the surface deformation at the main sections shows that the surface deformation features during the mining process of the 132610 working face match well with the general model of mining subsidence, but the working face inclination angle has an influence on the surface deformation. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) oblique photogrammetry has been extensively employed in mining, albeit predominantly for reconstructing three-dimensional scenes and detecting changes within mining sites, lacking predictive capabilities. Leveraging 3D real scene model data, this study presents a two-stage prediction model, merging the probabilistic integral method with recurrent neural network (PIMF-RNN), to mitigate the impact of internal and external factors on surface subsidence, thereby enhancing predictive accuracy. Building upon this framework, a methodology was developed to forecast the maximum surface subsidence height and affected area under the block caving method, offering crucial data support for mitigating hazards associated with this mining technique. Analysis of surface data from Pulang copper mine during 2018–2020 demonstrates a prediction accuracy of 91.47% for maximum surface subsidence height and 87.52% for subsidence area. This research expands the potential applications of UAV oblique photogrammetry techniques within mining contexts. Furthermore, it establishes a cost-effective and efficient operational procedure for predicting mine surface subsidence. [ABSTRACT FROM AUTHOR]

The extraction of underground mineral deposits can cause surface subsidence, which will bring danger to surface buildings or structures. In this paper, the Panlong lead–zinc mine in Guangxi, China, was taken as an example to analyze the correlation between underground mining‐induced surface subsidence trends, and the depth of extraction. Based on the stochastic probability integral method, the surface subsidence trend at various different mining depths was analyzed. The results showed that with the increase of mining depth, the surface subsidence presents an obvious increasing trend, but the rate gradually decreases. The maximum surface subsidence is closely related to the mining depth and is less notably affected by the mining size. The maximum surface subsidence along the dip direction is basically the same as that along the strike direction for the same mining depth of the same ore body. In addition, numerical simulation by FLAC3D was conducted to analyze the evolution trend of surface subsidence at different mining depths. The subsidence cloud map demonstrated a significant expansion of the subsidence area until a depth of 680 m. With the further increase of mining depth, the subsidence area did not substantially increased, while the maximum subsidence at the center of the subsidence zone was increasing. Finally, the maximum subsidence at the center of the subsidence zone was measured by Global Positioning System (GPS) monitoring instruments. The observed data showed that subsidence trend along the direction of the mineral body was basically consistent with the theoretical and numerical simulation results above. This verifies the reliability and accuracy of the above research methods for analyzing surface settlement trend. [ABSTRACT FROM AUTHOR]

The fluid–solid coupling effect is an important factor which cannot be ignored to study the surface subsidence of deep coal seam mining in the area with abundant underground water. To study the influence of boundary permeability characteristics on surface subsidence in deep near‐horizontal coal seam mining under the effect of fluid–solid coupling, the pore water pressure field, vertical stress field, surface subsidence, and vertical displacement of a rock seam during deep mining under different permeability boundary conditions were analyzed based on fluid–solid coupling theory, taking the 3−1501 working face of Erdos Hongqinghe coal mine as an example. The results revealed that the permeability characteristics of different hydraulic boundaries affected the pore water pressure, vertical stress in the rock layer, and surface subsidence during deep mining. Moreover, the trends of pore water pressure, vertical stress, and surface subsidence of a fixed‐head permeability boundary were largely the same as those under impermeable boundary conditions, but the calculated results of the fixed‐head permeability boundary were lower than those for the impermeable boundary at the same depth. The maximum surface subsidence for the fixed‐head permeable boundary condition and the impermeable boundary condition was 879 and 925 mm, respectively, which were 239 and 285 mm higher than those obtained when the fluid–solid coupling effect was neglected (an increase of 37.3% and 44.5%, respectively). The field monitoring trend for the subsidence basin aligns closely with the subsidence basin trend under the influence of fluid–solid coupling. Considering the constant head permeable boundary conditions in the context of fluid–solid coupling yields accurate surface subsidence results. The results have provided a theoretical basis for the analysis and prediction of coal mining surface subsidence considering the fluid–solid coupling effect. [ABSTRACT FROM AUTHOR]

As the extraction of mineral resources intensifies, ground subsidence in mining areas has escalated, posing substantial challenges to sustainable development and operational safety. This subsidence, resulting directly from mining activities, significantly compromises the safety of nearby residents by damaging residential structures and infrastructure. Thus, developing precise and dependable methods for predicting ground subsidence is crucial. This study introduces an innovative Cabs-Unet model, which enhances the U-Net architecture by integrating a Convolutional Block Attention Module (CBAM) and Depthwise Separable Convolutions (DSC). This model aims to predict the spatiotemporal dynamics of the Interferometric Synthetic Aperture Radar (InSAR) time series. Employing Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS InSAR) technology, we gathered and validated data on ground subsidence at the Pengzhuang coal mine from May 2017 to November 2021, covering 130 scenes, with its accuracy corroborated by levelling survey results. An empirical evaluation of the Cabs-Unet model in two distinct subsidence zones demonstrated superior performance over conventional methods like Convolutional Long Short-Term Memory (ConvLSTM) and Predictive Recurrent Neural Network (PredRNN), with Root Mean Square Error (RMSE) values of 1.44 and 1.70, respectively. These findings highlight the model’s efficacy in accurately predicting spatiotemporal InSAR ground subsidence. Further predictive analysis using InSAR data indicated an expected increase in subsidence, projecting cumulative declines of −457 mm in Area A and −1278 mm in Area B by 17 July 2022. Our model proves effective in assessing subsidence, promptly detecting potential risks and facilitating the rapid implementation of risk mitigation strategies. [ABSTRACT FROM AUTHOR]

Accurately monitoring the change of mine area in the mining process is beneficial to mine safety management. This paper briefly introduces the collection of remote sensing images by unmanned aerial vehicles (UAVs) and its application in measuring surface mining subsidence and surrounding vegetation in the mining area. A case study was carried out in some mining areas of Nanshan Mountain, Yuncheng City, Shanxi Province. The surface mining subsidence value and vegetation-related parameters were measured by comparing the digital elevation model and multi-spectral images collected on May 12 and June 12, 2023. The validity experiment verified that the UAV image data could be used to measure the mining subsidence and vegetation parameters. Moreover, it was found that mining underground coal could lead to significant ground subsidence and pollute the surrounding environment, reducing vegetation. The innovation of this article lies in using UAV-collected remote sensing images instead of manually collecting ground elevation data and vegetation distribution data, providing effective references for safe mining in mining areas. [ABSTRACT FROM AUTHOR]

Borehole-to-surface electrical (BTSE) technology plays an important role in detecting mining subsidence area in coalfields. However, the ambiguity of linear inversion and the influence of surrounding rock resistivity reduced the effectiveness and accuracy of BTSE technology in identifying mining subsidence area. In this study, the damped least-squares inversion method constrained by inequality was investigated based on the basic principles of BTSE technology. On this basis, a novel method using the ratio of post- to pre-mining inversion resistivity was proposed to detect mining subsidence area. Finally, the application effect of this method was analyzed by using theoretical model and laboratory mining model, respectively. It was found that the resistivity inversion of the BTSE constrained by inequality could obtain good layered information of the stratum provided by prior information. Using the ratio of post- to pre-mining inversion resistivity can eliminate the influence of surrounding rock on the abnormal resistivity and highlight the resistivity anomalies caused by stratum collapse during coal mining. The application results of the theoretical model and laboratory mining model illustrated the feasibility and effectiveness of this novel method in detecting mining subsidence area, which provides important theoretical basis and reference for its future promotion and application. [ABSTRACT FROM AUTHOR]

SBAS-InSAR technology is effective in obtaining surface deformation information and is widely used in monitoring landslides and mining subsidence. However, SBAS-InSAR technology is susceptible to various errors, including atmospheric, orbital, and phase unwrapping errors. These multiple errors pose significant challenges to precise deformation monitoring over large areas. This paper examines the spatial characteristics of these errors and introduces a spatially constrained SBAS-InSAR method, termed SSBAS-InSAR, which enhances the accuracy of wide-area surface deformation monitoring. The method employs multiple stable ground points to create a control network that limits the propagation of multiple types of errors in the interferometric unwrapped data, thereby reducing the impact of long-wavelength signals on local deformation measurements. The proposed method was applied to Sentinel-1 data from parts of Jining, China. The results indicate that, compared to the traditional SBAS-InSAR method, the SSBAS-InSAR method significantly reduced phase closure errors, deformation rate standard deviations, and phase residues, improved temporal coherence, and provided a clearer representation of deformation in time-series curves. This is crucial for studying surface deformation trends and patterns and for preventing related disasters. [ABSTRACT FROM AUTHOR]

The geological environment damage caused by coal mining subsidence has become an important factor affecting the sustainable development of mining areas. Reconstruction of the Coal Mining Subsidence Field (CMSF) is the key to preventing geological disasters, and the needs of CMSF reconstruction cannot be met by solely relying on a single remote sensing technology. The combination of Unmanned Aerial Vehicle (UAV) and Synthetic Aperture Radar (SAR) has complementary advantages; however, the data fusion strategy by refining the SAR deformation field through UAV still needs to be updated constantly. This paper proposed a Prior Weighting (PW) method based on Satellite Aerial (SA) heterogeneous remote sensing. The method can be used to fuse SAR and UAV Light Detection and Ranging (LiDAR) data for ground subsidence parameter inversion. Firstly, the subsidence boundary of Differential Interferometric SAR (DInSAR) combined with the large gradient subsidence of Pixel Offset Tracking (POT) was developed to initialize the SAR preliminary CMSF. Secondly, the SAR preliminary CMSF was refined by UAV LiDAR data; the weights of SAR and UAV LiDAR data are 0.4 and 0.6 iteratively. After the data fusion, the subsidence field was reconstructed. The results showed that the overall CMSF accuracy improved from ±144 mm to ±51 mm. The relative errors of the surface subsidence factor and main influence angle tangent calculated by the physical model and in situ measured data are 1.3% and 1.7%. It shows that the proposed SAR/UAV fusion method has significant advantages in the reconstruction of CMSF, and the PW method contributes to the prevention and control of mining subsidence. [ABSTRACT FROM AUTHOR]

Surface water and sediment rare earth elements (REEs) concentrations can reflect the impact of human activities on aquatic ecosystems. Variations in formation time may result in changes in the geochemical characteristics of REEs in the water‒sediment system of coal mining subsidence lakes. However, our understanding of this phenomenon is limited. The spatial distribution, coexistence patterns, and fractionation characteristics of REEs were investigated in coal mining subsidence lakes with different subsidence times in the Huainan coalfield in eastern China. The results indicate that REEs concentrations in lake water are relatively low. Both compartments are enriched in light rare earth elements (LREEs), and the degree of enrichment increases with time, which can be attributed to the combined influences of natural processes and human activities. Under alkaline water conditions in the study area, LREEs are preferentially removed from the aqueous phase, leading to their enrichment in sediments. The anomalous behavior of Ce is associated with the oxidative environment under alkaline conditions, whereas the Eu anomaly is influenced primarily by the dissolution of feldspar minerals. Agricultural activities result in significant inputs of light rare earth elements (La) to farmlands each year through the application of rare earth fertilizers. These elements are ultimately released into coal mining subsidence lakes, resulting in noticeable anomalies of La in the majority of lakes within the study area. These findings indicate that the lakes in the subsidence area are strongly affected by agricultural activities. The difference between lakes with different numbers of sinking years is reflected mainly in the degree of enrichment of LREEs, and the older the lake is, the greater the degree of enrichment of LREEs. These research results provide a scientific basis for the treatment and protection of the water environment in coal mining subsidence lakes influenced by anthropogenic activities. Through this series of studies, we will improve our understanding of the behavior of REEs in the aquatic environment under the influence of human activities and to provide support for sustainable mineral resource development and environmental protection policy formulation. [ABSTRACT FROM AUTHOR]

The high groundwater level coal mining areas have a long history of mining and are mainly located in east-central region of China. Subsidence caused by coal mining occur in several different periods. However, the subsidence change regularity in each periods remains unclear. This study aimed to reveal the subsidence change regularity in high groundwater level coal mining areas during different periods. The Juye coal mine, located in Heze City, Shandong Province, China, was selected for the study. Firstly, 55 Sentinel-1A radar satellite images from August 2018 to July 2020 were acquired for this research. The "two-track method" of D-InSAR technology was employed to process the images. Secondly, based on subsidence velocity of 1.7 mm/day, the subsidence process was divided into three periods: initial, active and weakening. Thirdly, elevation data of ground levelling points were used to check the accuracy of subsidence monitoring using Sentinel-1A data. At last, the subsidence change process in different periods was analyzed and the change regularity was summarized. The results are shown as follows: (1) the monitoring accuracy of different periods is high, and R2range from 0.961 to 0.983. (2) The subsidence characteristics are not obvious in initial period. The subsidence funnel begin to form and the mean maximum subsidence in center is greater than 1400 mm in active period. The subsidence velocity gradually decrease and eventually stabilize in weakening period. (3) Appearance of subsidence, development of subsidence funnels and formation of subsidence basins are spatial period characteristics of coal mining-induced subsidence. The results can provide an important basis for land conservation in mining areas. [ABSTRACT FROM AUTHOR]

Shuozhou is a typical coal mining city, and the Pingshuo Antaibao open-pit coal mine in its area is one of the largest open-pit coal mines in China. The mining of coal resources is an important part of ensuring national energy security, and at the same time, it inevitably has a certain impact on the ecology, such as coal dust generated by open-pit mining will affect air quality, soil, water and vegetation. It is of great significance to explore the temporal and spatial variation of ecological environment quality in coal mining cities for ecological protection and sustainable social and economic development. Based on the Google Earth Engine (GEE) platform, this paper combines the index-based coal dust index (ICDI) and Remote Sensing Ecological Index (RSEI) models to construct an improved RSEI (IRSEI) that can reflect coal mining cities. This paper explores the spatial–temporal evolution characteristics and spatial correlation of ecological environment quality in Shuozhou from 2000 to 2020. The results showed that the average value of IRSEI in Shuozhou was between 0.262 and 0.418, and the overall change showed an upward trend. The growth areas of ecological environment quality are mainly located in the eastern and southwestern areas with good vegetation growth, and these regions have vigorously implemented the Northern Shelter Forest Project, afforestation and greening projects, implemented the forest resource management and protection responsibility system, promoted the construction of ecological civilization, and significantly improved the ecological environment. While the declining areas are mainly located in the central and southern regions where mining activities and human activities are more intensive. The IRSEI in the study area showed a significant spatial positive correlation, and the agglomeration types of the spatial pattern were mainly high-high and low-low agglomeration types, with the high-high agglomeration types mainly distributed in the eastern and southwestern regions, and the low-low agglomeration types distributed in the northern and south-central regions of the study area. The trend of low and low agglomeration has decreased, which further proves that the ecological restoration measures taken by the government, such as returning farmland to forests, integrating protection and restoration of mountains, waters, forests, fields, lakes, grasslands, and sands, controlling soil erosion, and stage wise reclamation of coal mining subsidence areas, have improved the ecological environment quality of Shuozhou. This study provides a reference for understanding the spatiotemporal changes of the ecological environment of coal mining cities, and is conducive to formulating appropriate ecological protection strategies. [ABSTRACT FROM AUTHOR]

Coal seam mining causes fracture and movement of overlying strata in goaf, and endangers the safety of surface structures and underground pipelines. Based on the engineering geological conditions of 22,122 working face in Cuncaota No.2 Coal Mine of China Shenhua Shendong Coal Group Co., Ltd. a similar material model test of mining overburden rock was carried out. The subsidence of overburden rock was obtained through the full-section strain data of distributed optical fiber technology, and the characteristics of mining surface subsidence were studied. The Weibull model was used to adjust the mathematical form of the first half of the surface subsidence curve via the MMF function. On this basis, the prediction model of coal seam mining surface subsidence was established, and the parameters of the prediction model of surface subsidence were determined. The test results show that with the advancement of coal seam mining, the fit goodness of the surface subsidence prediction curve based on the MMF optimization model reaches 0.987. Compared with the measured values, the relative error of the surface subsidence prediction model is reduced to less than 10%. The model displays good prediction accuracy. The time required for settlement stability in the prediction model is positively correlated with parameter a and negatively correlated with parameter b. The research results can be further extended to the prediction of overburden "three zones" subsidence, and provide a scientific basis for the evaluation of surface subsidence compression potential in coal mine goaf. [ABSTRACT FROM AUTHOR]

Coal mining has led to escalating ecological and environmental issues in significant coal and grain production areas, posing a severe danger to food security. This study examines the disturbance patterns of soil factors and microbial communities in coal and grain production areas, and attempts to understand the impact of subsidence and water accumulation stress on soil characteristics and microbial communities in coal mining subsidence areas with high subsidence levels. Five specific regions of Zhao Gu Yi Mine, situated in Henan Province and under the ownership of Jiaozuo Coal Group, were chosen. Aside from the control group (CK), the study blocks situated in the coal mining subsidence zones consisted of perennial subsidence ponding (PSP), seasonal subsidence ponding (SSP), the neutral zone (NZ), and the horizontal deformation zone (HDZ). The soil nutrient indices and the stoichiometric properties of soil C, N, and P were assessed on the surface of each block. The organization of the soil microbial community was identified using high-throughput sequencing. The findings indicate that: 1. Substantial disparities exist in soil properties and microbial community structure between the subsidence and non-subsidence zones. The levels of soil organic mater (SOM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), and available phosphorus (AP) all decrease to different extents in the subsidence area. Additionally, the coal mining subsidence waterlogged area exhibits higher levels compared to the coal mining subsidence non-waterlogged area. Conversely, the soil water content (SWC), C/N ratio, C/P ratio, and N/P ratio all increase to varying degrees. 2. Regarding the composition of the community, the presence of Proteobacteria is considerably greater in the non-water-logged area of coal mining subsidence (NZ, HDZ) compared to the water-logged area and control group (p < 0.05). The prevalence of Firmicutes in the subsidence water area was substantially greater compared to both the subsidence non-waterlogged area and the control group (p < 0.05). The prevalence of Gemmatimonadota is markedly greater in the waterlogged area of mining subsidence compared to the non-waterlogged area and CK (p < 0.05). The Ascomycota population reached its highest value in the neutral zone (NZ), which was significantly greater than the values observed in the seasonal subsidence ponding (SSP) and perennial subsidence ponding (PSP) regions (p < 0.05). On the other hand, the Rozellomycota population had its highest value in the SSP region, which was significantly greater than the values observed in the other regions (p < 0.05). 3. The abundance and variety of soil bacteria and fungi, as well as their important populations, are associated with different levels of soil characteristics. The primary elements that influence the alteration of microbial communities are soil nutrients and soil water content. The presence of coal mine subsidence and water accumulation has a notable impact on the properties of the soil in the surrounding area. This study offers a scientific foundation for reclaiming land affected by subsidence caused by coal mining in regions where coal and grain production are the dominant industries. [ABSTRACT FROM AUTHOR]

During underground coal seam mining, changes in the working face advancement rate can easily affect the compaction state of granules in the collapse zone. This is an important factor in the induction of gas disasters and surface subsidence in mining areas. In this work, a cyclic loading and unloading mechanical test of granules under different loading rates was carried out. The changes in mechanical parameters of the granules at various stages were investigated. It is shown that the strain of each group of specimens under cyclic loading shows an increasing trend and the final strain increases with the loading rate. The input energy of the granules increases under cyclic loading, and under a low loading rate, the compaction force needs to overcome interparticle friction to destroy the relatively stable structure, which results in a need for more energy to achieve the same level of deformation. The acoustic emission ringing counts of each group of granules specimens show an overall increasing trend, with the highest proportion of ringing counts in the first loading stage. The compaction of pores and filling of particles under cyclic loading is a "uniform compaction, stable change, slow adjustment" dynamic process. When the loading is slow, the relative positions of the granule particles in each stress gradient are more adequately adjusted. The results of this study provide important theoretical support for the scientific formulation of gas control strategies and the prevention of surface subsidence in air-mining zones under different mining speeds. [ABSTRACT FROM AUTHOR]

The mining of deep underground coal seams induces the movement, failure, and collapse of the overlying rock–soil body, and the development of this damaging effect on the surface causes ground fissures and ground subsidence on the surface. To ensure safety throughout the life cycle of the mine, fully distributed, real-time, and continuous sensing and early warning is essential. However, due to mining being a dynamic process with time and space, the overburden movement and collapse induced by mining activities often have a time lag effect. Therefore, how to find a new way to resolve the issue of the existing discontinuous monitoring technology of overburden deformation, obtain the spatiotemporal continuous information of the overlying strata above the coal seam in real time and accurately, and clarify the whole process of deformation in the compression–tensile strain transition zone of overburden has become a key breakthrough in the investigation of overburden deformation mechanism and mining subsidence. On this basis, firstly, the advantages and disadvantages of in situ observation technology of mine rock–soil body were compared and analyzed from the five levels of survey, remote sensing, testing, exploration, and monitoring, and a deformation and failure perception technology based on spatiotemporal continuity was proposed. Secondly, the evolution characteristics and deformation failure mechanism of the compression–tensile strain transition zone of overburden were summarized from three aspects: the typical mode of deformation and collapse of overlying rock–soil body, the key controlling factors of deformation and failure in the overburden compression–tensile strain transition zone, and the stability evaluation of overburden based on reliability theory. Finally, the spatiotemporal continuous perception technology of overburden deformation based on DFOS is introduced in detail, and an integrated coal seam mining overburden safety guarantee system is proposed. The results of the research can provide an important evaluation basis for the design of mining intensity, emergency decisions, and disposal of risks, and they can also give important guidance for the assessment of ground geological and ecological restoration and management caused by underground coal mining. [ABSTRACT FROM AUTHOR]

This study aims to provide a comprehensive analysis of the impacts of high-intensity coal mining on vegetation in Liangbei Town, a typical deep coal mining area in central of China. Using Landsat remote sensing data from 2000 to 2023, processed by the Google Earth Engine (GEE) platform, the study calculates the Normalized Difference Vegetation Index (NDVI). Temporal and spatial distribution patterns of vegetation were assessed using LandTrendr algorithm, Sen's slope estimation, the Mann–Kendall test, the coefficient of variation, and the Hurst index. Vegetation growth dynamics were further analyzed through transfer matrix and intensity analysis frameworks. Driving factors influencing vegetation trends were evaluated using local climate data and surface deformation variables from SAR imagery. Temporal Dimension: From 2000 to 2023, the annual NDVI in Liangbei Township showed an upward trend with a growth rate of 0.0894 (10a)−1, peaking at 0.51 in 2020. Spatial Dimension: The NDVI distribution in Liangbei Township displayed a pattern of being lower in the center and higher around the edges, with values concentrated between 0.4 and 0.51, covering 50.34% of the total area. Trend of Change: Between 2000 and 2023, 83.28% of the area in Liangbei Township experienced significant improvement in the NDVI, with vegetation growth trends shifting primarily from slight to significant improvement, encompassing a total area of 10.98 km². This shift exhibited a marked tendency. Driving Factors: Deep mining in Liangbei Township is concentrated in the eastern part, with SAR imagery indicating a maximum surface subsidence of 0.26 m. As surface subsidence increases, the NDVI significantly decreases. The findings suggest that in the future, 91.13% of the vegetation in Liangbei Township will display an antipersistent change trend. The study offers critical insights into the interaction between mining activities and vegetation cover can serve as a reference for environmental evolution and management in similar mining areas. [ABSTRACT FROM AUTHOR]

Xuzhou used to be a significant coal resource-based city in eastern China and a typical mining area with a high groundwater level. Prolonged underground mining activities and rapid urbanization have profoundly transformed its regional landscape pattern. Therefore, analyzing the laws of regional land use and the spatiotemporal evolution of landscape ecological security holds significant importance for regional sustainable development. Based on multi-period remote sensing data from 1990 to 2020, this study analyzed the intensity of land use changes and transformation characteristics in the eastern mining area of Xuzhou over a 30-year period. On this basis, the ecological security status of the landscape over different periods was evaluated by the Landscape Ecological Security Index. Lastly, spatial autocorrelation analysis was conducted to reveal the overall characteristics and local variations in the spatial distribution of landscape ecological security. The results indicate the following: (1) Over the course of 30 years, due to mining-induced land subsidence and water accumulation, the water area increased by 67.41%, exhibiting the highest dynamic change in land use; construction land area came next, increasing by 30.75%; cultivated land area declined the most gently. (2) From 1990 to 2010, the overall landscape ecological security status of the study area displayed a deteriorating trend, and areas with low ecological security were closely associated with mining distribution and urbanization zones. From 2010 to 2020, guided by ecological restoration plans, the fragmentation of landscape patches decreased, leading to evident improvements in local landscape ecological security. (3) The results of spatial autocorrelation analysis revealed a significant positive correlation and spatial clustering in the distribution of landscape ecological security areas. The high-high aggregation areas were mainly distributed around cultivated land, while the low-low aggregation areas were primarily distributed within the coal mining subsidence zone. Overall, coal mining subsidence and urbanization were the main factors influencing the landscape ecological security status in the high-water-level mining area. In territorial spatial planning, emphasis should be placed on the connectivity and diversity of landscapes to enhance landscape ecological security. The results offer essential information and decision support for governmental authorities and land use planners, aiming to achieve regional sustainable development. [ABSTRACT FROM AUTHOR]

Coal mining inevitably causes damage to the surface ecological environment. In response to the characteristics of multiple factors, wide scope, and long time series of surface ecological environment damage in coal mining subsidence areas, how to integrate multiple data sources and monitoring methods to achieve monitoring and trend analysis of ecological damage throughout the entire mining cycle still needs to be studied. In addition, the 110 mining method provides an innovative method for underground coal mining to reduce its surface ecological damage, but the differences in surface damage between the two mining modes and the effectiveness of the 110 method in realizing surface ecological damage-reducing mining still need to be studied in depth. Therefore, this study takes the surface ecological damage in the mining area of Lvliang City, a typical resource city in Shanxi Province, China, as the object. It establishes a four-in-one "Satellite–UAV–Ground–Underground" information monitoring method, proposes a historical big data evolution analysis method, constructs three spatial scales of historical big databases, clarifies the current situation and development trend of damage in coal mining areas in Lvliang City and explores the differences in surface ecological environment damage characteristics in coal mining areas based on the 121 and 110 mining methods. The results show that: (1) The existing coal mining subsidence area in Lvliang City is as high as 92,191.47 hectares, and it is expected to continue to increase to 130,739.55 hectares in the future 2035, with a growth rate of 41.812%, which realizes the goals of mapping the current situation, retracing the history and predicting the future of the ecological damage of the surface in Lvliang City. (2) The surface NDVI of the 110 working face is restored to the average level of the mining area faster than that of the 121 working face. The surface crack width, step displacement, length, distribution density, and surface settlement height of the 110 working face are all smaller than those of the 121 working face. It has been verified that the unique top-cutting and swelling filling effect of the 110 methods can effectively reduce the ecological damage caused by coal mining subsidence. And its widespread application can effectively realize the ecological environmental protection of the coal mine area and contribute to the high-quality development of the coal industry in Lvliang City. [ABSTRACT FROM AUTHOR]

Northwest China is both an important coal storage base and an ecologically fragile area, and soil water content (SWC) is a key factor limiting the ecological development of Northwest China. Revealing the characteristics of spatial and temporal distribution changes of soil water content in mining areas under coal mining disturbance and the influencing mechanism is crucial for the protection of water resources in mining areas. In this study, the soil water content (depth 0–1000 cm) of a typical coal mine subsidence area in the western part of Shendong Coal Group was monitored in situ for 1 year after mining, and the absolute value, variability, and spatial distribution of soil water content were temporally analysed by combining classical statistics, 2D Ordinary Kriging and 3D Empirical Bayesian kriging spatial interpolation. sequence analysis. The results showed that the shallow SWC (0 ~ 60 cm) was distributed horizontally in bands, and gradually increased along the direction from northwest to southeast; with the increase of coal mining time, the absolute value of SWC decreased by 0.81% ~ 33.58%, and the coefficient of variation decreased and then increased, with the range of variation from 2.19% ~ 34.49%. The deep SWC (100 ~ 1000 cm) was stratified vertically and increased with soil depth, and the shallow and deeper soil moisture would gradually migrate to the middle layer under the influence of coal mining. In addition, this paper accurately portrays the three‐dimensional spatial and temporal distribution of soil water content by the 3D EBK model, which further reveals the mechanism of coal mining's influence on soil water content. This study can provide technical and data support for predicting and evaluating the potential impacts of mining activities on the water cycle, and help mining areas to formulate policies for managing and protecting water resources. [ABSTRACT FROM AUTHOR]

The movement and deformation of rock strata and the ground surface is a dynamic deformation process that occurs as underground mining progresses. Therefore, the dynamic prediction of three-dimensional surface deformation caused by underground mining is of great significance for assessing potential geological disasters. Synthetic aperture radar interferometry (InSAR) has been introduced into the field of mine deformation monitoring as a new mapping technology, but it is affected by many factors, and it cannot monitor the surface deformation value over the entire mining period, making it impossible to accurately predict the spatiotemporal evolution characteristics of the surface. To overcome this limitation, we propose a new dynamic prediction method (InSAR-DIB) based on a combination of InSAR and an improved Boltzmann (IB) function model. Theoretically, the InSAR-DIB model can use information on small dynamic deformation during mining to obtain surface prediction parameters and further realize a dynamic prediction of the surface. The method was applied to the 1613 (1) working face in the Huainan mining area. The results showed that the estimated mean error of the predicted surface deformation during mining was between 80.2 and 112.5 mm, and the estimated accuracy met the requirements for mining subsidence monitoring. The relevant research results are of great significance, and they support expanding the application of InSAR in mining areas with large deformation gradients. [ABSTRACT FROM AUTHOR]

Mining-induced surface deformation disrupts ecological balance and impedes economic progress. This study employs SBAS-InSAR with 107-view of ascending and descending SAR data from Sentinel-1, spanning February 2017 to September 2020, to monitor surface deformation in the Fa'er Coal Mine, Guizhou Province. Analysis on the surface deformation time series reveals the relationship between underground mining and surface shifts. Considering geological conditions, mining activities, duration, and ranges, the study determines surface movement parameters for the coal mine. It asserts that mining depth significantly influences surface movement parameters in mountainous mining areas. Increasing mining depth elevates the strike movement angle on the deeper side of the burial depth by 22.84°, while decreasing by 7.74° on the shallower side. Uphill movement angles decrease by 4.06°, while downhill movement angles increase by 15.71°. This emphasizes the technology's suitability for local mining design, which lays the groundwork for resource development, disaster prevention, and ecological protection in analogous contexts. [ABSTRACT FROM AUTHOR]

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The subsidence of the earth's surface in mining areas is characterized by fast speed and large gradients. Conventional small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) monitoring can significantly underestimate results, making it challenging to capture the surface's temporal subsidence features. In this context, this paper proposes a method for monitoring subsidence in mining areas. It utilizes a phase unwrapping network (PUNet) and a fused Weibull model within the SBAS-InSAR framework to address nonlinear and large-gradient subsidence. The basic principle of this method is to first process the SAR images using the small baseline method to obtain the differential interferogram, utilizing the PUNet to obtain reliable large-gradient unwrapped phases. Next, the Weibull model parameters of each pixel are calculated based on the unwrapped phase, and the temporal subsidence of each point on the surface is determined using the calculated parameters. This method introduces a nonlinear model into the SBAS-InSAR solution, which is more consistent with the subsidence characteristics of mining areas. Through experimentation in a backfilled mining working face, the proposed method in this paper yields superior monitoring results compared to conventional approaches. [ABSTRACT FROM AUTHOR]

Due to the lack of field monitoring points, the monitoring data is incomplete, making it difficult to obtain more complete characteristics of mining subsidence. To address this issue, a novel method for interpolating missing subsidence points is proposed. Firstly, the subsidence data are decomposed into multi-frequency domains utilizing the empirical mode decomposition (EMD) method. Subsequently, the missing subsidence data are reconstructed by combining the radial basis function (RBF) with phase space reconstruction technology. The interpolation accuracy is then analyzed under various conditions, including different mining degrees, sample numbers, and observation point locations. The results indicate that the interpolation accuracy increases with the mining degree coefficient. During the active stage of surface subsidence, a larger sample number correlates positively with higher interpolation accuracy. However, in the recession stage, the impact of sample number on interpolation accuracy is less pronounced compared to the timeliness of sample acquisition. The location of observation points has minimal effect on interpolation accuracy. By applying this method to the 833 working face in the Shanjiacun coal mine, the mean absolute percentage error (MAPE) is less than 20%, and the mean squared error (MSE) is below 0.5 mm, objectively demonstrating the method's effectiveness and engineering applicability. These research findings offer valuable technical support for mine safety production and ecological environment protection. [ABSTRACT FROM AUTHOR]

Mining subsidence is a serious threat to the ecosystems of mining regions. Accurate prediction of mining subsidence is essential for a scientific assessment of mining-induced damage. This study proposed a prediction model of mining subsidence based on an unskewed continuous probability distribution over an infinite interval. This method is an extension of the commonly used subsidence prediction method, the probability integration method, employed by Chinese engineers. It has the same scope of application as the probability integration method. This method does not have a specific expression and encourages engineers to screen appropriate unskewed continuous probability distribution functions and incorporate them into this model to establish prediction equations. By not solely considering one prediction method developed based on a specific function, it avoids limiting the improvement of prediction accuracy. The reliability of this method was validated by comparing it with actual subsidence data from the mining area. The results indicate that this approach can further improve the accuracy of mining subsidence prediction compared to the probability integration method. [ABSTRACT FROM AUTHOR]

Research on the deformation characteristics and failure modes of buried pipelines under local suspension conditions caused by groundwater loss in coal mining subsidence areas is conducive to grasping the failure evolution law of pipelines and providing technical support for the precise maintenance of gathering and transportation projects and the coordinated mining of gas and coal resources. First, a test system for monitoring the deformation of pipelines under loading was designed, which mainly includes pipeline load application devices, end fixing and stress monitoring devices, pipeline end brackets, and stress–strain monitoring devices. Then, a typical geological hazard faced by oil and gas pipelines in the gas–coal overlap area—local suspension—was used as the engineering background to simulate the field conditions of a 48 mm diameter gas pipeline with a localized uniform load. At the same time, deformation, top–bottom strain, end forces, and damage patterns of the pipeline were monitored and analyzed. The results show that the strain at the top and bottom of the pipeline increased as the load increased. In this case, the top was under pressure, and the bottom was under tension, and the conditions at the top and bottom were opposite.. For the same load, the strain tended to increase gradually from the end to the middle of the pipeline, and at the top, it increased significantly more than at the bottom. The tensile force carried by the end of the pipeline increased as the applied load increased, and the two were positively correlated by a quadratic function. The overall deformation of the pipeline evolved from a flat-bottom shape to a funnel and then to a triangular shape as the uniform load increased. In addition, plastic damage occurred when the pipeline deformed into a triangular shape. The results of the investigation clarify for the first time the mathematical relationship between local loads and ultimate forces on pipelines and analyze the evolution of pipeline failure, providing a reference for pipeline field maintenance. Based on this, the maximum deformation of and the most vulnerable position in natural gas pipelines passing through a mining subsidence area can be preliminarily judged, and then the corresponding remedial and protection measures can be taken, which has a certain guiding role for the protection of natural gas pipelines. [ABSTRACT FROM AUTHOR]

The solid backfilling mining method is one of the methods used to solve problems arising from strata and ground subsidence in underground mines. Through 2D physical analog modeling, 3D numerical simulation, and field measurement, the effects of the solid backfilling method were analyzed, providing a better insight into optimizing the configurations of a working face beneath a city for safety, environmental problems, and its use in production. In the physical modeling, MatchID software was employed to capture the movement characteristics of overlying strata and ground subsidence during mining and backfilling. Key parameters such as vertical displacement, subsidence characteristics, and rock mass stress variations were monitored and analyzed. In the numerical simulation, FLAC3D was used to simulate and analyze the effect of the backfill body on strata and ground subsidence above the backfill working face. For the field measurements, the Continuously Operating Reference Station (CORS) system was used to confirm the effective control of ground subsidence. With a filling ratio of 80%, the three methods are consistent and show a maximum subsidence value of 0.46 mm (physical simulation), 50.4 mm (numerical simulation), and 47 mm (experienced), significantly lower than the predicted subsidence, which is 281 mm. Therefore, this study demonstrates the reliability and scientific validity of both the physical analog modeling method and the field measurement method in measuring the efficiency of solid backfilling, providing valuable insights into strata and ground subsidence control in longwall coal mining. [ABSTRACT FROM AUTHOR]

Ground subsidence caused by extraction of longwall panels has always been a great concern all over the world. Conventional longwall mining system (CLMS) gives rise to wavy subsidence causing great damage to surface structures. A coal mine in Shanxi, China, utilizes a split-level longwall layout (SLL) for a sub-horizontal No. 8 coal seam to improve the cavability of mudstone interlayer and top coal. This layout, however, also produced unexpectedly favorable surface subsidence. Subsidence of No. 6 and No. 8 longwall panels was monitored while mining was conducted. Field instrumentation and numerical simulation were carried out. It is demonstrated that an asymmetric subsidence profile with stepped subsidence and cracks occurred on the tailgate side but relatively mild and smooth deformation on the other. Due to elimination of conventional parallelepiped gate pillar, No. 6 and No. 8 gobs were connected. Extraction of two SLL panels acted as one supercritical panel. The maximum possible subsidence was reached which lowers the likelihood of potential future secondary subsidence as underground gob fractures and voids have closed. Therefore, SLL is more favorable for post-mining land reuse as gobs are more consolidated underground. [ABSTRACT FROM AUTHOR]

Surface subsidence hazards in mining areas are common geological disasters involving issues such as vegetation degradation and ground collapse during the mining process, which also raise safety concerns. To address the accuracy issues of traditional prediction models and study methods for predicting subsidence in open-pit mining areas, this study first employed 91 scenes of Sentinel-1A ascending and descending orbits images to monitor long-term deformations of a phosphate mine in Anning City, Yunnan Province, southwestern China. It obtained annual average subsidence rates and cumulative surface deformation values for the study area. Subsequently, a two-dimensional deformation decomposition was conducted using a time-series registration interpolation method to determine the distribution of vertical and east–west deformations. Finally, three prediction models were employed: Back Propagation Neural Network (BPNN), BPNN optimized by Genetic Algorithm (GA-BP), and BPNN optimized by Artificial Bee Colony Algorithm (ABC-BP). These models were used to forecast six selected time series points. The results indicate that the BPNN model had Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE) within 7.6 mm, while the GA-BP model errors were within 3.5 mm, and the ABC-BP model errors were within 3.7 mm. Both optimized models demonstrated significantly improved accuracy and good predictive capabilities. [ABSTRACT FROM AUTHOR]

Affected by geological factors, the scale of surface deformation in a hilly semi-desertification mining area varies. Meanwhile, there is certain dense vegetation on the ground, so it is difficult to construct a high-precision and complete image of a subsidence basin by using a single monitoring method, and hence the laws of the deformation and inversion of mining parameters cannot be known. Therefore, we firstly propose conducting collaborative monitoring by using InSAR (Interferometric Synthetic Aperture Radar), UAV (unmanned aerial vehicle), and 3DTLS (three-dimensional terrestrial laser scanning). The time-series complete surface subsidence basin is constructed by fusing heterogeneous data. In this paper, SBAS-InSAR (Small Baseline Subset) technology, which has the characteristics of reducing the time and space discorrelation, is used to obtain the small-scale deformation of the subsidence basin, oblique photogrammetry and 3D-TLS with strong penetrating power are used to obtain the anomaly and large-scale deformation, and the local polynomial interpolation based on the weight of heterogeneous data is used to construct a complete and high-precision subsidence basin. Compared with GNSS (Global Navigation Satellite System) monitoring data, the mean square errors of 1.442 m, 0.090 m, 0.072 m are obtained. The root mean square error of the high-precision image of the subsidence basin data is 0.040 m, accounting for 1.4% of the maximum subsidence value. The high-precision image of complete subsidence basin data can provide reliable support for the study of surface subsidence law and mining parameter inversion. [ABSTRACT FROM AUTHOR]

Objectives: As a continuation of mining subsidence, the surface secondary subsidence (including sinking and uplift) of closed mines poses a potential threat to the safety of surface buildings-structures in mining areas. However, at this stage, the law analysis of the surface secondary subsidence of closed mines under different geological mining conditions is not yet comprehensive. Due to the high underground water level, thick Quaternary loose layers, and multiple coal seams in the Huainan mining area, monitoring and analyzing the surface secondary subsidence of closed mines in the Huainan mining area has important theoretical and practical values. Methods: First, in order to verify the reliability of the monitoring results, the StaMPS software is employed to simultaneously perform persistent scatterers interferometry and small baseline subset processing. Amplitude dispersion index and amplitude difference dispersion index are used to select coherent points, respectively. Then, the unwrapped phases of the coherent points are obtained by a three-dimensional phase unwrapping algorithm. Finally, the surface subsidence of the coherent points are obtained by using temporal-domain low-pass and spatial-domain high-pass filtering. Results: The results show that: (1) The surface uplifts after the closure of Xinjisan and Lizuizi-Xinzhuangzi-Xieyi mines, with a maximum uplift rate of 51.1 mm/a, and is located in Xinzhuangzi mine, while the surface of Panyi mine is still sinking due to its late closure in September 2018. (2) The surface secondary subsidence law of closed mines in Huainan mining area is sinking stage‐stable stage‐uplift stage, which is consistent with the surface subsidence law of closed mines in Xuzhou mining area, but the sinking, stable and uplift stages do not necessarily occur successively over time. (3) There may be a hydraulic connection between Lizuizi, Xinzhuangzi, and Xieyi mines. The groundwater first rises from the junction of Xinzhuangzi and Xieyi mines and then flows to the southeast and northwest sides. Conclusions: Although the law of surface subsidence in the closed mines of Huainan and Xuzhou mines is relatively consistent, there are differences in the law of surface uplift due to different hydrogeological mining conditions. Therefore, in future work, we will continue to pay attention to the law of surface secondary subsidence of closed mines under different geological mining conditions [ABSTRACT FROM AUTHOR]

This study explores the environmental changes in the disturbed area of coal mining and presents the driving factors of ecological self-restoration. Specifically,we measured the soil nutrient and soil enzyme indicators in the mining area and non-mining area from 2014 to 2017 and 2019,and evaluated the stoichiometric characteristics of soil carbon (C),nitrogen (N),and phosphorus (P). The experimental results show that the total phosphorus concentration gradually recovered with the increase of mining years,while organic matter,available potassium,and urease first increased and then decreased with the increase of mining years. There were significant differences in total phosphorus,C/ N ratio,N/ P ratio, and C/ P ratio between the working face and the subsidence disturbance zone. Random forest analysis showed that soil sucrase,urease,available potassium,total nitrogen,total phosphorus,C/ P ratio,C/ N ratio, and water-soluble salts were the key factors influencing soil nutrient cycling in different time periods; while C/ N ratio,N/ P ratio,total phosphorus,alkaline phosphatase,and water-soluble salts were the key factors influencing soil nutrient cycling at different locations. Mining years of the working face has differing influence path on soil factors and soil enzymes. This study could provide theoretical proof for the artificial guided self-restoration plan in coal mining subsidence areas and for ecological restoration in western mining areas. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Large-scale exploitation of underground mineral resources causes surface collapse, reduces land use efficiency, and brings a series of ecological and environmental problems. This is significantly important for the ecological restoration work of mining areas to accurately extract the subsidence range and depth of coal mine surface and formulate the regulation model suitable for coal mine subsidence areas. In this research, we used Differential Interferometric Synthetic Aperture Radar (D-InSAR) technology to extract the subsidence range of the Zhaogu Mining Area in Henan Province based on multi-source remote sensing data. We constructed the Spectral-Spatial Residual Network (SSRN) to classify the land use information within the subsidence range. Finally, we constructed a fuzzy comprehensive evaluation model based on the improved G1 method that assesses the extent of land damage in the subsidence area. Additionally, a suitable governance model for the subsidence area in the Zhaogu Mining Area is proposed. The results can provide technical support and data reference for the comprehensive treatment of subsidence in the Zhaogu Mining Area. [ABSTRACT FROM AUTHOR]

The article presents the results of significance analyses of selected mining and geological variables for an area of underground mining activity. The study area was a region of an underground copper ore mine located in southwest Poland. The input data consisted of satellite radar data from the Sentinel 1 mission as well as mining and geological data. The line-of-sight subsidence, calculated with the use of the small baseline subset method and arranged in time series, was decomposed to extract the vertical component. The significance analysis of individual variables for the observed surface subsidence was performed using the SHapley Additive exPlanations method for the XGBoost machine learning model. The results of the analysis showed that the observed ground surface subsidence velocities were most influenced by the thickness of the PZ3 layer, which is located approximately 200 m above the roof of the mined seam, the thickness of the seam, and the timing of mining. It was also found that the proposed model was able to detect a nonlinear relationship between the analyzed excavations. The most significant influence on ground subsidence over mine excavations are mining parameters such as the spatially averaged thickness of the deposit and the time since liquidation of the deposit. The proposed approach can be successfully employed in planning both mining operations and mine closure in such a manner that the environmental impact is minimized. [ABSTRACT FROM AUTHOR]

Coal mining causes surface subsidence, resulting in the loss of phosphorus from the soil surface and affecting crop growth. To provide a basis for the reclamation of soils in coal mining subsidence areas, using the Suntuan mine area in Huaibei City as an example, indoor soil cultivation experiments were conducted to investigate the effects of applying different types of phosphate rock powders (mechanically activated and nonmechanically activated), active minerals (zeolite, kaolin, bentonite) and phosphorus solubilizing microorganisms (Pseudomonas fluorescens, Aspergillus niger) on soil pH, available phosphorous content, and the conversion of soil phosphorus fractions. The results showed that the combined action of phosphate rock powder and phosphorus solubilizing bacteria could significantly improve the soil acidic environment. The application of phosphate rock powder, active minerals, and phosphorus solubilizing microorganisms can promote the release of available phosphorous in soil, and Aspergillus niger has a better effect than Pseudomonas fluorescens. Soil content of H2O-P, NaOH-Pi, NaHCO3-Pi, and HCl-P increased, NaOH-Po decreased, and some treatment groups had reduced Residual-P content. Together, phosphate rock powders, active minerals, and phosphorus solubilizing microorganisms can mitigate soil acidification, promote soil phosphorus release, result in the transformation of soil phosphorus fractions, and improve phosphate fertilizer utilization. [ABSTRACT FROM AUTHOR]

Coniolo and Brusaschetto, are two small towns located in the Monferrato area of the Alessandria Province, northern Italy. These communities have similar histories related to development and subsequent abandonment of marl quarry activity that began more than a century ago and continued until recently. Quarrying occurred until soil conditions, water infiltration, and excessive depth made cost of extracting and7 lifting material prohibitive. Quarries consisted of tunnels located directly beneath the towns at about 150 m below ground surface. Collapse of the tunnels led to surface subsidence and destruction of overlying homes and much of the municipal infrastructure. In the early Twentieth Century, regulations pertaining to mine and quarry safety were typically deficient, entirely absent, or not followed. Extractive activities of non-energy mineral resources from quarries and mines were and continue to be widespread in Italy, which currently ranks fifth among what are now countries of the European Union (EU). Mining sites are present in all regions of Italy, particularly in the northern part of the country and along coasts, often in areas of geohydrogeological risk. Consequences of anthropogenic pressures that alter the natural environment, such as the physical size of aquifer drawdowns, are linked to issues for a number of extractive sites across the country. This report analyzes historical and technical documents, conducts a geomorphological analysis of hilly slopes surrounding these communities, and examines urban planning and geophysical surveys to determine the impact of subsurface quarrying activities on the overlying ground surface. The study highlights significant problems that are applicable to other localities globally. This research demonstrates: (a) the importance of geological considerations to development and abandonment of mining activity in inhabited areas; (b) the importance of establishing and following safety protocols; and (c) the manner in which economic interests can take precedence over the well-being and lives of those employed to extract resources. [ABSTRACT FROM AUTHOR]

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The probability integral method is one of the most widely used methods for predicting surface subsidence induced by underground mining in China. In its parameter calculation, the least square algorithm is commonly employed for fitting parameters. However, in the process of fitting parameters, the results are easily affected by ill-conditioned normal matrices and the interference of outliers, resulting in divergent problems. To solve these problems, the principle of robust ridge estimation was introduced in this paper, and a parameter calculation model for the probability integral method based on this principle (hereafter referred to as the established model) was established. Besides, a parameter calculation experiment with manual intervention was conducted in combination with engineering examples. The results demonstrate that the parameter calculation method based on robust ridge estimation can suppress the interference of outliers, overcome the problem of ill-conditioned matrix, and ensure the effectiveness and reliability of parameter estimation results. Compared with the conventional least squares method, the robust ridge estimation method demonstrates greater accuracy in predicting surface subsidence parameters, which validates its rationality and accuracy in underground mining engineering. The research findings provide technical support for obtaining similar parameters for surface subsidence in mining areas and hold significant engineering application value. [ABSTRACT FROM AUTHOR]

To fully comprehend the patterns of land and ecological damage caused by coal mining subsidence, and to scientifically carry out ecological mine restoration and management, it is urgent to accurately grasp the information of coal mining, particularly in complex coaling areas, such as North Anhui, China. In this paper, a space–air–ground collaborative monitoring system was constructed for coal mining areas based on multi-source remote sensing data and subsidence characteristics of coaling areas were investigated in North Anhui. It was found that from 2019 to 2022, 16 new coal mining subsidence areas were found in northern Anhui, with the total area increasing by 8.1%. In terms of land use, water areas were increased by 101.9 km2 from 2012 to 2022, cultivated land was decreased by 99.3 km2, and residence land was decreased by 11.8 km2. The depth of land subsidence in the subsidence areas is divided into 307.9 km2 of light subsidence areas with a subsidence depth of less than 500 mm; 161.8 km2 of medium subsidence areas with a subsidence depth between 500 mm and 1500 mm; and 281.2 km2 of heavy subsidence areas with a subsidence depth greater than 1500 mm. The total subsidence governance area is 191.2 km2, accounting for 26.5% of the total subsidence area. From the perspective of prefecture-level cities, the governance rate reaches 51.3% in Huaibei, 10.1% in Huainan, and 13.6% in Fuyang. The total reclamation area is 68.8 km2, accounting for 34.5% of the subsidence governance area. At present, 276.1 km2 within the subsidence area has reached stable subsidence conditions, mainly distributed in the Huaibei mining area, which accounts for about 60% of the total stable subsidence area. [ABSTRACT FROM AUTHOR]

Understanding the distribution and development patterns of mining-induced fissures is crucial for environmental protection and geological hazard prevention. To address labor-intensive manual inspection, an automated approach leveraging Convolutional Neural Networks (CNNs) and Unmanned Aerial System Photogrammetry (UASP) is proposed for fissure identification and mapping. Initially, the ResNet-50 network was employed for the binary classification of the cropped UASP orthophoto images. A comparative analysis was conducted to determine the optimal model between DeepLabv3+ and U-Net. Subsequently, the identified fissures were mosaicked and spatially projected onto the original orthophoto image, incorporating precise projection data, thereby furnishing a spatial reference for environmental governance. The results indicate a classification accuracy of 93% for the ResNet-50 model, with the U-Net model demonstrating a superior identification performance. Fissure orientation and distribution patterns are influenced by the mining direction, ground position of the mining workface, and topographic undulations. Enhancing the CNN performance can be achieved by incorporating variables such as slope indices, vegetation density, and mining workface locations. Lastly, a remote unmanned approach is proposed for the automated mapping of mining-induced fissures, integrated with UAS automated charging station technology. This study contributes to the advancement of intelligent, labor-saving, and unmanned management approaches advocated by the mining industry, with potential for broad applications in mining environmental protection efforts. [ABSTRACT FROM AUTHOR]

Water-soluble mining was invariably associated with surface subsidence, which in some cases escalated to the movement, deformation, and even collapse of the overlying rock layers, triggering grave subsidence calamities. The caprock of the salt-bearing strata in the Longgui salt rock mining area was closely adjacent to the third aquifer, which mainly consisted of fractured, porous, high-permeability materials such as mudstone conglomerates, rendering the geological conditions highly complex. Years of water-soluble mining had led to significant surface subsidence in the mining area, with a trend toward accelerated subsidence. In this study, the geological conditions of the Longgui salt rock mining area were analyzed, and through simulated experiments of pillar dissolution mining, the mechanisms of surface subsidence in the area were examined. Over time, the dissolution gradually perforated the pillars and caprock, with the pillars ceasing to support the caprock, ultimately transforming small cavities into a large single cavity. Utilizing subsidence data, this research employed numerical simulation to inverse and predict subsidence patterns from 2019 to 2025, revealing that the maximum subsidence reached 1367.6 mm in mining area I and 1879.5 mm in mining area II, with subsidence rates of 12.05 mm/y and 44.78 mm/y, respectively. Moreover, the impact of ground subsidence on the construction of adjacent subways was assessed by establishing monitoring points and evaluating subsidence along subway cross-sections and longitudinal directions. The findings provided valuable insights for guiding the prevention and control of surface subsidence calamities in the Longgui salt rock mine and similar mining areas in Guangzhou, China. [ABSTRACT FROM AUTHOR]

In order to investigate the changes in soil enzyme activity and their influencing factors in coal mining subsidence areas with high underground water levels, in this study, we collected soil samples at different depths (SL: 0–20 cm; ML: 20–40 cm; DL: 40–60 cm) in a deep coal seam subsidence area (T1), a shallow coal seam subsidence area (T2), and control non-subsidence areas (W1 and W2) in eastern China. Soil physicochemical properties and enzyme activities were determined, and the mechanism of the latter's response to coal mining subsidence was investigated based on correlation analysis, redundancy analysis, and structural equation modeling. The results show the following: (1) In the coal mining subsidence areas, the soil pH value (pH), soil available nitrogen (AN), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM) contents were lower than those in the non-subsidence areas, while the soil water content (SWC) and bulk density (BD) were higher than those in the non-subsidence areas and increased with depth. (2) The activities of soil urease (URE), sucrase (SUC), alkaline phosphatase (ALP), and catalase (CAT) gradually decreased with depth and were all lower than those in the non-subsidence areas; the largest decreases with respect to the latter were 24.33%, 18.73%, 38.89%, and 5.88%, respectively. (3) The soil nutrient environment had a highly significant and direct positive effect on enzyme activity, with AN, AP, and SOM contents having the greatest impact. (4) Soil BD had a highly significant and direct negative effect and an indirect negative effect (by affecting nutrients) on enzyme activity. The results of this study on the effects of soil physicochemical properties on enzyme activity provide a basis for the ecological restoration of mines. [ABSTRACT FROM AUTHOR]

Time series dynamic prediction of surface deformation in mining areas can provide reference data for coal mine safety and production, which has important impacts. The combination of interferometric synthetic aperture radar (InSAR) technology and the probability integral method (PIM) is commonly used for predicting deformation. However, most surface subsidence prediction in mining areas is based on the static PIM parameters, failing to achieve the three-dimensional (3D) dynamic deformation prediction. This paper proposed a 3D deformation dynamic prediction model (InSAR-3D-CTPIM) between InSAR deformation observations and dynamic coordinate-time PIM (CTPIM) parameters, which can realize the prediction of east–west, north–south, and vertical series deformation caused by mining. The method has been validated by simulation experiments and real experiments in the mining area of Jiansheng Coal Mine in Baisha Reservoir, Henan Province, China. The results showed that the modeling accuracy was improved by 34.3% compared to the traditional multi-rate model, and the accuracy was improved by 28.5% compared to the vertical deformation obtained by the traditional static PIM method. The InSAR-3D-CTPIM model can be used to predict the evolutionary history of basin-wide surface deformation dynamics in coal mining areas, and provide a reference for the early warning and prediction of geological hazards in coal mining areas. [ABSTRACT FROM AUTHOR]

Dynamic predictions of surface subsidence are crucial for assessing ground damage and protecting surface buildings. Based on Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology, a method for making dynamic predictions of large-scale surface subsidence in mining areas can be established; however, the problem of phase coherence loss in InSAR data makes it impossible to predict the complete dynamic subsidence basin. In this study, a method combining the WeiBull time function and the improved probabilistic integral method (IPIM) model was established based on the PIM model, and a method for predicting the dynamic subsidence basin in the mining area was proposed by integrating the IPIM and the combined WeiBull time function. Time-series subsidence data, obtained using SBAS-InSAR, were used as fitting data, and the parameters of the combined WeiBull function were inverted, pixel by pixel, to predict the dynamic subsidence of the working face in the study area. Based on the predicted surface subsidence results of a certain moment in the working face, the parameters of the IPIM model were inverted to predict the subsidence value in the incoherent region. The subsidence predictions of the combined WeiBull time function and the IPIM model were fused using inverse distance weighting (IDW) interpolation to restore the complete subsidence basin in the mining area. This method was tested at the Wannian Mine in Hebei, and the obtained complete subsidence basin was compared with the measured data, with an absolute error range of 0 to 10 mm. The results show that the dynamic subsidence basin prediction method for the SBAS-InSAR mining area, involving the combination of the IPIM model and the combined WeiBull model, can not only accurately fit the time series of surface observation points affected by mining but also accurately restore the subsidence data in the incoherent region to obtain complete subsidence basin information in the mining area. [ABSTRACT FROM AUTHOR]

Underground coal mining in coal-grain overlapped areas leads to land subsidence and deformation above the goaf, damaging cultivated land. Understanding the influencing process of coal mining on cultivated land and crops is important for carrying out timely land reclamation and stabilizing crop yield. Research has been carried out by using crop growth parameters to evaluate the damaging degree of cultivated land when the mining subsidence is stable, but few studies focus on the influence of land damage on crop growth when the subsidence is unstable during coal mining. Therefore, this study tracked the three growth stages of winter wheat by using UAV multispectral imagery to explore the dynamic influence of underground mining on winter wheat aboveground biomass (AGB). Firstly, a winter-wheat-AGB estimation model (R2 = 0.89, RMSE = 2.18 t/ha) was developed by using vegetation indexes (VIs), textures, and terrain data extracted from UAV imagery. Secondly, based on the winter-wheat-AGB estimation model, the winter wheat AGB was successfully estimated and mapped at different growth stages. The AGB of winter wheat in the coal mining-affected area was approximately 5.59 t/ha at the reviving stage, 8.2 t/ha at the jointing stage, and 15.6 t/ha at the flowering stage. Finally, combined with the progress of coal mining, the dynamic changing process of crops during underground mining can be inferred by analyzing the spatiotemporal variation in winter wheat AGB. Results showed that, in the dip direction, winter wheat AGB at the flowering stage was the highest at the compression zone, followed by the inner stretch zone, outer stretch zone, and neutral zone. The distance from the waterlogged area and the existence of cracks were found to be the important moderating variables affecting the crop growth status in the mining subsidence area. In the strike direction, there were significant differences in the wheat AGB-affected area as the mining proceeded. Even areas where AGB had previously significantly increased gradually transitioned to significant decreases with the end of mining. The research explores the dynamic changes in winter wheat AGB and land damage status during coal mining. It provides a rapid and non-destructive land-damage-monitoring method to protect cultivated land in mining areas. [ABSTRACT FROM AUTHOR]

:F1y ash,cement,coal gangue and water are used as backfill materials to backfill in mine, which can not only reaiize the large-scale utiiizaiion of soiid waste resources, but ako effectively control the surface subsidence of the mine. In this study, the rheologccal properiies, mechanical properiies and hydration characteristics of cemented gangue backfill werestudeed. The rheologccal properties, compressive strength, hydration products and nicrostructure of gangue backfill werestudeed respectively. The results showed that when the content of 325 ordinary Portland cement was 15%, the content of low cakum lly ash !s more than 20%,and the mass concentration of slurry was kept above 77%,the minimum compressive strength of the prepared gangue backfill sample at 28 d curing age was more than 4. 229 MPa, which provided good roof support for underground backfill mining. Secondly, the influence of fly ash content and slurry mass concentrafion on the rheological properties of gangue filfing slurry were Investigated by rheological test, the corresponding rheologccal parameters and rheologcal equation fitting of filing slurry are obtamed. In addition, the mineral composition, hydration products and rmcrostructure of gangue cemented backfill materials were studied. Therefore, this study can provide some theoretical guidance for the apphcation of sohd waste n the ield of mine backi. [ABSTRACT FROM AUTHOR]

Revealing the spatiotemporal evolution characteristics and key driving processes behind the habitat quality is of great significance for the scientific management of production, living, and ecological spaces in resource-based cities, as well as for the efficient allocation of resources. Focusing on the largest coal-mining subsidence area in Jiangsu Province of China, this study examines the spatiotemporal evolution of land use intensity, morphology, and functionality across different time periods. It evaluates the habitat quality characteristics of the Pan'an Lake area by utilizing the InVEST model, spatial autocorrelation, and hotspot analysis techniques. Subsequently, by employing the GTWR model, it quantifies the influence of key factors, unveiling the spatially varying characteristics of their impact on habitat quality. The findings reveal a notable surge in construction activity within the Pan'an Lake area, indicative of pronounced human intervention. Concurrently, habitat degradation intensifies, alongside an expanding spatial heterogeneity in degradation levels. The worst habitat quality occurs during the periods of coal mining and large-scale urban construction. The escalation in land use intensity emerges as the primary catalyst for habitat quality decline in the Pan'an Lake area, with other factors exhibiting spatial variability in their effects and intensities across different stages. [ABSTRACT FROM AUTHOR]