Mining-induced Ground Research Articles

Development Law and Prevention Methods of Mining-induced Ground Cracks: A Review

ABSTRACT Mining-induced ground cracks in coal mining areas pose a significant threat to the ecological environment and the safety of individuals and property. To achieve sustainable development in mining environments and resource utilization, it is crucial to elucidate the formation mechanisms, types, development laws, research methods, and prevention strategies associated with ground cracks. In this paper, we classify mining-induced ground cracks based on various research purposes. Relevant research methods are summarized, and we systematically review the research progress on the development law of different mining-induced ground cracks. The unique development patterns of ground cracks in the Aeolian sand area of the western mining region in China are analyzed, highlighting a double cycle. Simultaneously, we explore prevention methods for mining-induced ground cracks. Results indicate that the evolution law and formation mechanism of mining-induced ground cracks are influenced by various geological and mining factors, showing complexity, diversity, and unity. However, research methods have their limitations. Building upon these findings, we propose a monitoring and analysis systems for mining-induced ground cracks to enhance real-time monitoring, data processing, and subsequent analysis. It is recommended to make further efforts in seven aspects. These endeavors aim to better comprehend the intricate behavior of ground cracks in coal mining areas, providing a theoretical reference for land ecological restoration.

A novel method combining strata movement and UAV infrared remote sensing technology to evaluate mining ground damage

Mining-induced ground fissures are common problems associated with mining damage in shallowly buried coal seams in the western mining area of China. To evaluate the surface mining damage of the 12203 working face of the Huojitu Colliery in Shendong mining area, low-altitude infrared aerial surveys were conducted on the ground at the static fissure area (O-A1) and the dynamic fissure area (O-A2) of the working face. The temperature evolution patterns of fissures, sand and plants in the infrared images were analysed. The relationship between overburden fractures and surface fissure temperature was revealed, and the influence range and temperature self-healing period of the surface affected by underground mining were determined. The results indicated that underground mining could lead to a decrease in the ground temperature above the working face. The surface temperature evolution can be divided into three zones: a temperature stabilization zone before mining, a temperature cooling zone during mining, and a temperature recovery zone after mining. The temperature of sand and plants above the working face exhibited quadratic curve changes in O-A1 and O-A2, respectively. The length of the temperature reduction zone affected by mining is 40 m in O-A2, and 46.8 m in O-A1. The temperature recovery periods of ground fissures in O-A1 and O-A2 were 4.0 and 4.6 d, respectively. These findings could provide a basis for evaluating mining ground damage.

Improvement of Coal Mining-Induced Subsidence-Affected (MISA) Zone Irregular Boundary Delineation by MT-InSAR Techniques, UAV Photogrammetry, and Field Investigation

Coal mining-induced ground subsidence is a severe hazard that can damage property, infrastructure, and the environment in the vicinity when the deformation is not negligible. The boundary of a mining-induced subsidence-affected zone refers to the area beyond which the ground subsidence is less concerned. Accurately measuring mining-induced ground deformation is essential for delineating the irregular boundary of the impacted area. This study employs multitemporal interferometric synthetic aperture radar (MT-InSAR) techniques, including differential InSAR (DInSAR), InSAR stacking, and interferometric point target analysis (IPTA), to analyze coal mine subsidence and delineate the boundaries of the mining-impacted zones. DInSAR accurately reconstructs, locates, and detects the trend in mining-induced subsidence and correlates well with documented mining operations. The InSAR stacking method maps the spatial variation of the ground’s average line-of-sight (LOS) velocity over the mining area, delineating the boundary of the impacted zone. IPTA analysis combining multilook and single-pixel phases achieves millimeter-level surface measurement above tunnel alignments and measures unevenly distributed deformation fields. This study considers an average of 4 cm per year of surface deformation in the LOS direction as the subsidence threshold value for delineating the boundary of the mining-induced subsidence-affected (MISA) zone during the active coal mining stage. Interestingly, there are twin transportation tunnels near the mining area. The twin tunnels completed before the coal mining activities started were functioning well, but damage was observed after the mining began. Our study reveals the tunnels are located within the InSAR-derived MISA zone, although the tunnels approach the MISA boundary. As direct signs of subsidence, ground fissures have been identified near the tunnels via field investigations and UAV photogrammetry. Furthermore, the derived distribution of ground fissures validates and verifies InSAR measurements. The integrated approach of MT-InSAR, UVA photogrammetry, and field investigation developed in this study can be applied to delineate the irregular boundary of the MISA zone and study the accumulating effects of mining-induced subsidence on the performance of infrastructure in areas proximate to coal mining activities.

The Influence of the Morphological Characteristics of Mining-Induced Ground Fissures on the Spatiotemporal Distribution of Soil Moisture

In order to study the influence of fissure morphology on soil moisture-content changes under different fissure types, this study established HYDRUS 2.0 numerical models of stepped fissures and planar fissures with different fissure widths and depths based on the experimental condition parameters obtained from physical simulation tests. Then, we simulated the spatial and temporal variation rules of soil moisture around the fissures. The results showed a high level of agreement between the HYDRUS numerical simulations and actual measurements, indicating that the model accurately reflects the movement of soil moisture near fissures. The study found that ground fissures affected the spatial distribution of soil moisture, leading to an increased rate of moisture loss in the deep soil near the fissure walls. Moreover, larger fissures had greater horizontal and vertical effects on soil moisture. The soil moisture content is lower closer to the fissure walls. As the soil depth increased, the influence of the fissures gradually diminished. For planar fissure with a depth of 50 cm, the soil moisture content was 30.6%, 17.8%, and 8.4% lower at depths of 10, 30, and 50 cm, respectively, compared to a fissure with a depth of 10 cm. For a stepped fissure with a depth of 50 cm, the soil moisture content was 29.2%, 20.9%, and 13.9% lower at depths of 10, 30, and 50 cm, respectively, compared to a fissure with a depth of 10 cm. Under the same conditions of fissure width and depth, stepped fissures exhibit faster moisture loss, and the larger the fissure, the more significant the additional moisture loss compared to planar fissures.

Failure characteristics of buried pipelines in subsidence areas under the influence of multi-adjustable factors during coal mining: A case study of Ordos, China

Coal mining-induced ground subsidence often causes buried oil-gas pipeline failure. Insight the evolution of pipeline failure length and inflection points under the influence of adjustable factors (the distance between the panel pipe, panel width, internal pressure, and burial depth) has become increasingly essential for pipeline maintenance and operation. At present, the pipeline's failure length, failure time series, and inflection point distribution in subsidence areas are vague, which is not perfect in terms of specificity and clarity. Thus, a novel method to distinguish local failure and inflection points of pipelines is proposed by combining its moment and volume strain. Taking Panel 22102 of Ordos in western China as an example, the pipeline failure length and time series characteristics, as well as the inflection point spacing (IPS) are analyzed under the influence of adjustable factors by numerical simulation. The results show that (ⅰ) By increasing the distance between the panel pipe, and reducing the panel width, burial depth, and internal pressure, we can effectively mitigate or prevent pipe failures. For Panel 22102, the distance between the panel pipe should be less than 120 m to prevent failure. When it is unavoidable for the panel to pass underneath the pipeline, the width of the panel needs to be reduced to less than 120 m. (ⅱ) The pipeline failure length decreases by 2.9% for every 10 m reduction in the panel-to-pipeline distance. For every 10 m reduction in panel width, the pipeline failure length decreases by 5.7%. For every 0.1 m decrease in the burial depth, the pipeline failure length decreases by 2.16%. For each 1 MPa increase in internal pressure, the pipeline failure length increased by 0.48%. (ⅲ) The IPS is proportional to the panel width, burial depth, and internal pressure while exhibiting an exponential relationship with the distance between the panel and pipe. (ⅳ) The failure first spreads from the pipeline's subsidence center towards both ends, followed by spreading from both ends and the center towards inflection points simultaneously. (ⅴ) A multi-level and multi-faceted resilient management and collaborative operating pattern is established for the gas-coal integrated mining field. The research results provide scenario guidance and decision support for managers to develop adjusting measures to maintain pipelines, and also promote the coordinated mining of gas and coal resources.

Mapping mining-induced ground fissures and their evolution using UAV photogrammetry

Due to its unique geomorphological characteristics, the loess gully region is easy to produce ground fissures under the action of coal mining, destroy the ground infrastructures, induce geological disasters, and threaten the safety of people’s lives and property. Therefore, it is particularly important to accurately obtain information about the development of mining-induced ground fissures and study their spatial-temporal evolution mechanism. Based on the 1212 working face of a mining area in Yulin City, Shaanxi Province, this paper studies the extraction method and spatial-temporal evolution mechanism of ground fissures by combining remote sensing images and field survey data. The study shows that this proposed method significantly reduces noise points and mis-extraction, and the accuracy is more than 80%, improving the extraction accuracy of ground fissures and making the process more automated. By comparing the extraction accuracy of ground fissures at different flight altitudes, we determine that the optimal flight altitude for the research area is 60 m. At the beginning of the working face mining stage, the proportion of low-density areas of ground fissures continues to increase. Some low-density areas transition into high-density areas, which is consistent with the progress of the working face advancement. After the end of the working face retreat, the width of the ground fissures tends to be evenly distributed. The mining-induced ground fissures in the Loess gully and ravine region have good self-similarity. A dynamic development model of ground fissures is constructed to reveal its formation mechanism. The research conclusions can provide a technical support for geological disaster monitoring and land ecological restoration in mining areas.

Long-Term Impact of Ground Deformation on Vegetation in an Underground Mining Area: Its Mechanism and Suggestions for Revegetation

Ground deformation is one of the most common geological disasters arising in underground mining areas, and mining-induced environmental impacts have resulted in numerous concerns, especially the impacts on the surface vegetation. The evaluation of mining-induced impacts on vegetation is beneficial to revegetation in mining areas; however, the impacts of ground deformation have seldom been systematically evaluated and explained on long time scales despite the long-term existence of ground deformation in underground mining areas. To address this, in this study a vegetation-soil-climate (VSC) model was developed to evaluate the long-term impacts of ground deformation on vegetation, and to reveal its mechanism. The results revealed that the long-term impacts of ground deformation on vegetation result from the degradation of the vegetation and soil when ground deformation occurs, which thereby limits the growth and succession of plants after the ground deformation has occurred. The intensity of the long-term impacts is determined by the severity of the ground deformation, but the duration, climate factors, the substrate conditions of the vegetation and soil before the deformation, and the natural change coefficient of the vegetation and soil are also relevant. Furthermore, the characteristics of the long-term impacts on vegetation were analyzed, and a framework for implementing revegetation and suggestions for the supervision of revegetation in underground mining areas are presented based on the characteristics. The results of this study provide insights into the impacts of mining-induced ground deformation on vegetation on long time scales, considering the comprehensive interactions between the vegetation and other environmental factors, and provide theoretical support for revegetation in underground mining areas.

Identification of Ground Deformation Patterns in Coal Mining Areas via Rapid Topographical Analysis

Coal mining inevitably brings some negative impacts, such as surface subsidence, aquifer breakage, and land degradation, to the eco-geological environment in the mining area. Among these impacts, coal mining-induced ground deformation is the most serious and has threatened the geological, ecological, and human settlement securities of mining areas. Efforts existing in the literature apply to ground deformation identification in mined-out areas at the meso-/micro and short-time scales. However, when looking back at coal mining history, there are few ways to quickly and accurately quantify ground deformation at the regional and long-time scales. In this context, we propose a method for identifying ground deformation patterns in coal mining areas using historical high-precision digital elevation models (DEMs), including data preprocessing, DEM subtraction operations, interpretation, and fitting correction. This method was applied to the Yulin National Energy and Chemical Base and successfully identified the ground deformation characteristics of the Yulin coal mining area from 2015 to 2019. By determining surface subsidence displacement, excavation depth, stacking height, and the position of the goaf suspended roof area, the objective situation of ground deformation in Yulin mining area was obtained, and the mining methods and distribution characteristics of different surface deformations were analyzed and determined. The research results are of great significance for the development of mineral resources in mining areas, reducing geological disaster risks, protecting the ecological environment, and achieving the goal of coordinated development in mining areas.

Detecting long-term effects of mining-induced ground deformation on plant succession in semi-arid areas using a cellular automata model

Mining-induced ground deformation affects various plant communities in different ways. However, little is known about the effects of ground deformation on plant succession; no known quantitative approach currently exists to detecting the long-term effects. To address this issue, a plant community succession model based on cellular automata was developed. Plant succession over 30 years within a subsidence area in the Yungang mining area in China was simulated and compared under mining and non-mining scenarios, including under two sets of initial conditions (vegetated and bare). The normalized mean square error was applied to test the accuracy of the plant community succession model and to reveal the effects of ground deformation at the patch scale, which was 0.06–0.59 for simulated and observed plant patterns. Landscape indicators including contagion, patch cohesion, interspersion and juxtaposition, Shannon’s diversity, Shannon’s evenness, and aggregation indices were calculated and compared to reveal the effects of mine subsidence at the landscape scale. The results showed that the interspersion and juxtaposition, Shannon’s diversity, Shannon’s evenness, and aggregation indices were significantly influenced by ground deformation (P < 0.05) under vegetated conditions, indicating that ground deformation resulted in a loose, isolated, and mixed pattern of vegetation. In terms of the shrub and tree communities, the normalized mean square errors fluctuated at a high level under bare conditions, especially at the patch scale of 10 × 10 m, where it remained at greater than 0.5. Overall, mining-induced ground deformation had long-term effects on plant succession by limiting tree communities and promoting shrub communities, as well as by leading to a heterogenous vegetation pattern. Ground deformation altered the topography of the previously mined area, influencing hydrological processes such as rainfall, infiltration, and evaporation, which were closely related to plant succession. Although these long-term effects were not directly a result of ground deformation, changes in the topography of a subsidence area would interfere with the spontaneous succession of plant communities. Therefore, the long-term effects of mining-induced ground deformation should be considered during the ecological restoration of a mining area, which can promote the application of nature-based solutions and the natural regeneration of plant communities.

Ground Response of Non-Coal Pillar Mining Panel

The mining-induced ground response (MIGR) has a critical impact on safety management, the mining plan, and entry support. A clear understanding of the characteristics is the foundation of the MIGRs scientific control. This study is the result of the MIGRs development of the non-pillar mining panel with gob-side entry by roof cutting (GSERC). Comprehensive research of the in situ measurements, numerical simulation, and theoretical analysis to determine the ground response characteristics, including mining panel and GSERC, were implemented. The results indicate that the MIGR presents the characteristic of asymmetric development and that the ground response near the non-roof cutting side is more significant than that near the roof cutting side. The development stage of the entry convergence of GESRC can be divided into seven stages; the primary rapid development stage should be paid more attention to in the support process. The entry convergence rapidly increases to 275 mm, 380 mm, 410 mm, and 525 mm, respectively, for the roof cutting rib to the virgin coal rib, the roof near the virgin coal side, the roof of the middle section, and the roof near the cutting side. The hydraulic support end cycle resistance at the roof cutting side and the middle section of the mining panel with the value of more than 30.8 MPa is greater than that at the non-roof cutting side with the value of less than 26 MPa, which presents the asymmetric feature. The numerical simulation results regarding vertical stress development, vertical displacement, and horizontal displacement also presents the asymmetric feature. The MIGR division is divided into five divisions. Division II (the middle section of the panel) and division IV (the entry range near the roof cutting side) should be paid more attention to in the panel mining process. The results of this study can provide technical guidance and theoretical reference for similar engineering practices.

Stochastic differential equation modeling of time-series mining induced ground subsidence

Mining-induced ground subsidence is a commonly observed geo-hazard that leads to loss of life, property damage, and economic disruption. Monitoring subsidence over time is essential for predicting related geo-risks and mitigating future disasters. Machine-learning algorithms have been applied to develop predictive models to quantify future ground subsidence. However, machine-learning approaches are often difficult to interpret and reproduce, as they are largely used as “black-box” functions. In contrast, stochastic differential equations offer a more reliable and interpretable solution to this problem. In this study, we propose a stochastic differential equation modeling approach to predict short-term subsidence in the temporal domain. Mining-induced time-series data collected from the Global Navigation Satellite System (GNSS) in our case study area were utilized to conduct the analysis. Here, the mining-induced time-series data collected from GNSS system regarding our case study area in Miyi County, Sichuan Province, China between June 2019 and February 2022 has been utilized to conduct the case study. The proposed approach is capable of extracting the time-dependent structure of monitored subsidence data and deriving short-term subsidence forecasts. The predictive outcome and time-path trajectories were obtained by characterizing the parameters within the stochastic differential equations. Comparative analysis against the persistent model, autoregressive model, and other improved autoregressive time-series models is conducted in this study. The computational results validate the effectiveness and accuracy of the proposed approach.

Study on the Development Law of Mining-Induced Ground Cracks under Gully Terrain

Coal seam mining in the gully area easily causes ground cracks and even induces landslides, which endanger the safety of mining areas. In this paper, combined with the mining conditions of a mining area in southern Shanxi Province, China, ground crack mapping, crack width dynamic monitoring, and the numerical simulation method are used to study the static and dynamic evolution law and the formation mechanism of ground cracks in the gully area. The research shows that ground cracks mainly include dynamic in-plane cracks and boundary cracks. The dynamic in-plane cracks show the characteristics of “opening first and closing later”. The boundary cracks show the characteristics of “only opening and not closing”. It is found that the closure of the dynamic in-plane cracks will decrease (compared with plain areas). The development of ground cracks experiences three stages: the initial formation stage, the dynamic development stage, and the gradually stable stage. The “goaf–surface” structure model and force chain arch structure model are established to more intuitively analyze the formation mechanism of ground cracks. The research results have a specific reference value for preventing ground disasters caused by underground coal mining and land ecological restoration.

Detection of hidden mining-induced ground fissures via unmanned aerial vehicle infrared system and ground-penetrating radar

We propose a new combined detection method for the hidden ground fissures using unmanned aerial vehicle (UAV) with infrared camera and ground-penetrating radar (GPR) and applied it in the panel No. 12203 of the Daliuta coal mine. Subsequently, the extensive UAV aerial photography was taken to obtain the ground surface temperature of the entire longwall panel. The GPR detections along three survey lines in the selected ground surface zone of interest were carried out to find the positions of hidden ground fissures induced by underground mining. Based on the temperature measurement and analysis, the temperature of the surface above the hidden ground fissure is higher than that of the surface in non-fissure zone. The location of the hidden ground fissure can be determined by selecting the zone with a surface temperature higher than the temperature threshold, which is equal to the maximum average temperature of each surface zone. The similar track of hidden fissures can be drawn by GPR detection. The hidden ground fissure, with longitudinal lengths of 1–5 m and staggering horizontal lengths of 1–3.5 m, is mainly distributed 20–50 m in front of the working face, and between the step-like fissures. As the working face advances, the hidden ground fissure is recoverable with a cyclic evolution of formation, longitudinal development, and pinch-out. The optimal period for fissure detection is 9:20 a.m. to 11:30 a.m. at the environmental condition of this study, during which the open fissure has the lowest temperature range compared with the ground surface and vegetation. The results show that the proposed synergistic method can efficiently and accurately locate the hidden ground fissures and explain the distribution mechanism of ground temperature values in the mining area.

Temporal Analysis of Ground Movement at a Metal Mine in China

Mining-induced ground movement is a complicated nonlinear process and a regional geological hazard. Time series in Earth sciences are often characterized as self-affine, long-range persistent, where the power spectra exhibit a power-law dependence on frequency. Whether there exists a periodic signal and a fundamental frequency in the time series is significant in analyzing ground-movement patterns. To evaluate whether a power law describes the power spectra of a ground-movement time series and whether a fundamental frequency exists, GPS monitoring records taken over 14.5 years describing ground movement in the Jinchuan Nickel Mine, China, were analyzed. The data sets consisted of 500 randomly selected GPS monitoring points, spanning the April 2001–October 2015 time period. Whether a periodic signal in the ground movements existed was determined through the autocorrelation function. The power spectra of the ground-movement time series were found to display power-law behavior over vastly different timescales. The spectral exponents of the horizontal and vertical displacements ranged from 0.47 to 3.58 and from 0.43 to 3.37, with mean values of 2.05 and 1.79, respectively. The ground movements of minefields No.1 and No.2 had 1.1-month and 1.4-month fundamental periods, respectively. Together with a discussion of the underlying mechanisms of power-law behavior and relevant influencing factors, these results indicate that ground-movement time series are a type of self-affine time series that exhibit long-range persistence and scale invariance and show a complex periodicity. These conclusions provide a basis for predicting land subsidence in the study area over a timescale.

Impacts of Ground Fissures on Soil Properties in an Underground Mining Area on the Loess Plateau, China

Mining-induced ground fissures are the main type of geological disasters found on the Loess Plateau, China, and cause great impacts on the soil properties around ground fissures. However, little research has been conducted on the quantitative relationship between ground fissures and changes in soil properties. To address this, 40 ground fissures in the Yungang mining area, Datong City, Shanxi Province, China, were investigated, and changes in soil properties (soil organic matter, soil moisture, field capacity, bulk density, soil porosity, and grain compositions) were revealed by the difference in soil properties between the edge and contrast points around ground fissures. Redundancy analyses were used to illustrate the relationships between the value (Si_DV) and percentage (Si_DP) of the difference in soil properties between the edge and contrast points, as well as the ground fissures. The characteristics of ground fissures that had a significant correlation according to Pearson correlation analysis with Si_DP were selected and analyzed via multivariate linear fitting model, random forest model, and Back Propagation (BP) neural network model, respectively. Results show that soil organic matter, soil moisture content, bulk density, field capacity, and the content of clay at the edge points were significantly less than those at the contrast points; conversely, soil porosity at the edge points was significantly greater. The average percentage of the difference between the edge points and contrast points of ground fissures in these six properties was 15.27%, while soil moisture content showed the greatest change (20.65%). The Si_DP was significantly correlated with the width, slope, and vegetation coverage of ground fissures; however, the vegetation coverage was the determining factor. BP neural network model had the greatest performance in revealing the relationships between ground fissures and changes in soil properties. The model for soil organic matter had the highest accuracy (R2 = 0.89), and all others were above 0.5. This research provides insights into the quantitative relationship between ground fissures and their impacts on soil physical properties, which can be used in conjunction with remote sensing images to rapidly assess soil erosion risks caused by mining on a large scale, given that soil physical properties are closely related to topsoil stability.

Mathematical Evaluation on the Control of Mining-Induced Ground Subsidence in Thick Loose Strata.

Coal mining under thick loose strata in North China leads to ground subsidence, which is a natural result of hydromechanical coupling (fluid flow coupled with solid deformation). Therefore, the land surrounding the mining areas is greatly damaged. In this study, the combined weight (CW) method and the fuzzy matter-element analysis (FMEA) method were used to analyze and evaluate the control effect of subsiding land. Overall, 20 sets of geological samples were collected from this area. The influencing factors and the corresponding weights for the control effect of subsiding land were comprehensively analyzed, and an FMEA model was built to predict and verify the results. The results showed that (1) the two evaluation indicators with the most significant impact on land reclamation were the degree of integration and the economic and social benefits and (2) among the 20 sets of samples selected, the predicted conclusions of 17 sets were consistent with the actual engineering situations, which led to an accuracy of 85%. In other words, the CW-FMEA model showed good reliability for evaluating the control effect of subsiding land, which can provide scientific references for control and quality evaluations of land subsidence due to coal mining.

Study of Ground Movement in a Mining Area with Geological Faults Using FDM Analysis and a Stacking InSAR Method

Underground coal mining activities and ground movement are directly correlated, and coal mining-induced ground movement can cause damage to property and resources, thus its monitoring is essential for the safety and economics of a city. Fangezhuang coal mine is one of the largest coalfields in operation in Tangshan, China. The enormous amount of coal extraction has resulted in significant ground movement over the years. These phenomena have produced severe damages to the local infrastructure. This paper uses the finite difference method (FDM) 3D model and the stacking interferometric synthetic aperture radar (InSAR) method to monitor the ground movement in Fangezhuang coalfield during 2016. The FDM 3D model used calibrated Fangezhuang geological parameters and the satellite InSAR analysis involved the use of ascending C-band Sentinel-1A interferometric wide (IW) data for 2016. The results show that the most prominent subsidence signal occurs in mining panel 2553N and the area between panel 2553N and fault F0 with subsidence up to 57 cm. The subsidence observed for the FDM 3D model and stacking InSAR to monitor land deformation under the influence of fault are in close agreement and were verified using a two-sample t-test. It was observed that the maximum subsidence point shifted towards the fault location from the centre of the mining panel. The tectonic fault F0 was found to be reactivated by the coal mining and controls the spatial extent of the observed ground movement. The impact of dominant geological faults on local subsidence boundaries is investigated in details. It is concluded that ground movement in the study area was mainly induced by mining activities, with its spatial pattern being controlled by geological faults. These results highlight that the two methods are capable of measuring mining induced ground movement in fault dominated areas. The study will improve the understanding of subsidence control, and aid in developing preventive measures in Fangezhuang coalfield with fault reactivation.

Using Improved Edge Detection Method to Detect Mining-Induced Ground Fissures Identified by Unmanned Aerial Vehicle Remote Sensing

Information on the ground fissures induced by coal mining is important to the safety of coal mine production and the management of environment in the mining area. In order to identify these fissures timely and accurately, a new method was proposed in the present paper, which is based on an unmanned aerial vehicle (UAV) equipped with a visible light camera and an infrared camera. According to such equipment, edge detection technology was used to detect mining-induced ground fissures. Field experiments show high efficiency of the UAV in monitoring the mining-induced ground fissures. Furthermore, a reasonable time period between 3:00 am and 5:00 am under the studied conditions helps UAV infrared remote sensing identify fissures preferably. The Roberts operator, Sobel operator, Prewitt operator, Canny operator and Laplacian operator were tested to detect the fissures in the visible image, infrared image and fused image. An improved edge detection method was proposed which based on the Laplacian of Gaussian, Canny and mathematical morphology operators. The peak signal-to-noise rate, effective edge rate, Pratt’s figure of merit and F-measure indicated that the proposed method was superior to the other methods. In addition, the fissures in infrared images at different times can be accurately detected by the proposed method except at 7:00 am, 1:00 pm and 3:00 pm.

Identification of mining induced ground fissures using UAV and infrared thermal imager: Temperature variation and fissure evolution

The identification and treatment of mining-induced ground fissures are of great significance to mine safety and ecological and environmental protection. In this study, a novel method for ground fissure identification and exploration by infrared remote sensing onboard an unmanned aerial vehicle (UAV) was proposed. Using this method, a region of interest (ROI) that includes ground fissures directly above the middle of a long wall face, No. 12401 in the Shangwan coal mine, was monitored continuously during the day and night. Direct field measurements of ground fissure properties were also conducted to provide a calibration dataset for UAV measurements. Using the direct visible image at 5:00 pm as a reference, the average errors of the length and maximum width of Fissure I obtained from infrared images from 9:00 pm to 5:00 am on the next day, were estimated to be 1.8% and 6.5%, respectively. The diurnal variation of the fissure temperature is sinusoidal, and the range of temperature variation in the fissure decreases with the increase in depth. There is an apparent difference between the two common types of fissures depending on whether the fissure has a direct connection to an aquifer or a goaf. In this study, UAV, infrared thermal imager, and visible light camera data were successfully employed to effectively identify mining-induced ground fissures. In addition, the fissure detection error was validated, and the appropriate time for utilizing this method was obtained. Our results show that to identify the two aforementioned types of fissures, monitoring should be conducted between 3:00 am and 5:00 am. This study lays a foundation for the study and application of UAV and infrared thermal imagers for the identification of ground fissures induced by underground mining in large areas.

Searching for possible precursors of mining-induced ground collapse using long-term geodetic monitoring data

The problem of the ground collapses is common for the regions affected by the underground mining, as well as for the areas prone to the sinkholes of natural or human genesis. This paper describes the case of the ground surface collapse occurred in 2013 above the active Saranovsky chromite ore underground mine that has been operating for over eighty years. The results of pre- and post-failure high-precision levelling of the ground surface are presented. The monitoring network includes more than one hundred surveying points covering the area of about 1 km2 and since 2006 geodetic measurements have been conducted on an annual basis. The analysis pointed to a complex deformation process, manifested in the cyclic succession of subsidence and uplift of the surface. A local zone of continuous surface subsidence was identified immediately above the site of the future collapse. The deformations started several years before the failure. The extent of the subsiding area increased gradually, approximately approaching the size of the collapse (over 7000 m2). During the three-year period preceding the collapse, this area expanded by over a factor of ten, and the cumulated subsidence rate doubled. However, since the monitoring points located within the sinkhole area were lost, the data of the geodetic campaign carried out before the collapse were insufficient to estimate the value of the subsidence preceding the failure. Our results demonstrate, that in hard rocks mining-induced deformations can develop in utterly localized way. The progression of the subsidence was detected generally within the area of the future failure and did not extend significantly beyond its contours. In this paper, we highlight the importance of further development of the monitoring techniques and justification of hazardous deformation criteria for the early warning systems in mining regions and sinkhole-prone areas.