scholarly journals Slope ranking and geohazards correlation analysis for combined open-underground mining area

2018 ◽  
Author(s):  
Zhang Jin
Keyword(s):  
Correlation Analysis ◽  
Water Conservation ◽  
Laser Scanning ◽  
Underground Mining ◽  
Mining Area ◽  
Open Pit ◽  
Ground Subsidence ◽  
Data Sets ◽  
Mining Areas ◽  
Factor Data

Geohazards in mining areas are mainly ground subsidence, slope landslides and ground cracks, surface cover degradation and environmental ecological pattern destruction. The classification and rank of terrain slope and the feature area extraction of the slope are the important content for the correlation analysis with the geohazards. The slope classification and rank index system for soil and water conservation, land use and man-made ground disasters was analyzed. According to the characteristics of open pit and underground associated mining area, we comprehensively analyzed the spatial correlation between different ground disaster and terrain features and landform types, and propose a new slope ranking index, dividing slope zones and forming slope classification map. Especially slope area of 35-45 degrees and more than 45 degrees was extracted, and the relationship between regional geohazards and slope zone was analyzed. The application of terrestrial laser scanning technology to establish open-pit high precision digital elevation model, extraction of slope, slope type, gully density characteristic factor, topography factor data sets are established, and correlation analysis, to enhance disaster information content.

scholarly journals Slope ranking and geohazards correlation analysis for combined open-underground mining area

2018 ◽  
Author(s):  
Zhang Jin
Keyword(s):  
Correlation Analysis ◽  
Water Conservation ◽  
Laser Scanning ◽  
Underground Mining ◽  
Mining Area ◽  
Open Pit ◽  
Ground Subsidence ◽  
Data Sets ◽  
Mining Areas ◽  
Factor Data

Geohazards in mining areas are mainly ground subsidence, slope landslides and ground cracks, surface cover degradation and environmental ecological pattern destruction. The classification and rank of terrain slope and the feature area extraction of the slope are the important content for the correlation analysis with the geohazards. The slope classification and rank index system for soil and water conservation, land use and man-made ground disasters was analyzed. According to the characteristics of open pit and underground associated mining area, we comprehensively analyzed the spatial correlation between different ground disaster and terrain features and landform types, and propose a new slope ranking index, dividing slope zones and forming slope classification map. Especially slope area of 35-45 degrees and more than 45 degrees was extracted, and the relationship between regional geohazards and slope zone was analyzed. The application of terrestrial laser scanning technology to establish open-pit high precision digital elevation model, extraction of slope, slope type, gully density characteristic factor, topography factor data sets are established, and correlation analysis, to enhance disaster information content.

scholarly journals INSAR COLLABORATIVE MONITORING MODE AND MULTI-MODE COMPUTING SERVICES FOR GEOHAZARDS IDENTIFICATION IN OPEN-PIT MINING AREA

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 241-247
Author(s):  
J. Zhang
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Underground Mining ◽  
Mining Area ◽  
Deformation Monitoring ◽  
High Density ◽  
Open Pit ◽  
Open Pit Mining ◽  
Mining Areas ◽  
Wide Range

Abstract. InSAR has developed a variety of methods, such as D-InSAR, PS-InSAR, MBAS, CT, SqueeSAR, POT, etc., which have been widely used in land subsidence monitoring. For open pit mining areas, there are usually mining activity, complex terrain features, low coherence, and local large deformation gradients, which makes it difficult for time series InSAR technology to obtain high-density surface deformation information in open pit mining areas. Traditional methods usually only monitor the linear deformation of the surface caused by the mining of a few working zone above the underground mining area, and the temporal and spatial resolution is lower. How to obtain high-precision, high-density, and time-sensitive deformation information is the main difficulty of InSAR monitoring in open pit mining areas. Make full use of the geosensor network monitoring system, optimize monitoring mode of collaborated satellite-to-ground based InSAR, further realize whole calculation and geographic information services, to achieve early identification and discovery of abnormal in large-area macro-monitoring, and accurate monitoring of local areas in real-time early warning, which is the development direction of ground deformation monitoring of mining areas. The study area is Pingshuo open pit mining area. we fully study the application mode and services of InSAR monitoring for geohazards in open-pit mining area, through the establishment of satellite InSAR technology system for large-scale macro-monitoring and forecasting, and GBSAR and GSN for local precision monitoring. The effective mode of InSAR monitoring of geohazard in open-pit mines is summarized. A combination of D-InSAR, POT (Pixel offset tracking), Time Series-InSAR and GB-SAR is used in a wide range, and high-resolution optical images are used to identify localized changes in subsidence areas and open-pit mining areas.

scholarly journals Dust Dispersion and Its Effect on Vegetation Spectra at Canopy and Pixel Scales in an Open-Pit Mining Area

2020 ◽  
Vol 12 (22) ◽  
pp. 3759
Author(s):  
Baodong Ma ◽  
Xuexin Li ◽  
Ziwei Jiang ◽  
Ruiliang Pu ◽  
Aiman Liang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mining Area ◽  
Open Pit ◽  
Open Pit Mining ◽  
Vegetation Canopy ◽  
Dust Pollution ◽  
Mining Areas ◽  
Dust Effect ◽  
Dust Dispersion ◽  
Pixel Scale

Dust pollution is severe in some mining areas in China due to rapid industrial development. Dust deposited on the vegetation canopy may change its spectra. However, a relationship between canopy spectra and dust amount has not been quantitatively studied, and a pixel-scale condition for remote sensing application has not been considered yet. In this study, the dust dispersion characteristics in an iron mining area were investigated using the American Meteorological Society (AMS) and the U.S. Environmental Protection Agency (EPA) regulatory model (AERMOD). Further, based on the three-dimensional discrete anisotropic radiative transfer (DART) model, the spectral characteristics of vegetation canopy under the dusty condition were simulated, and the influence of dustfall on vegetation canopy spectra was studied. Finally, the dust effect on vegetation spectra at the canopy scale was extended to a pixel scale, and the response of dust effect on vegetation spectra at the pixel scale was determined under different fractional vegetation covers (FVCs). The experimental results show that the dust pollution along a haul road was more severe and extensive than that in a stope. Taking dust dispersion along the road as an example, the variation of vegetation canopy spectra increased with the height of dust deposited on the vegetation canopy. At the pixel scale, a lower vegetation FVC would weaken the influence of dust on the spectra. The results derived from simulation spectral data were tested using satellite remote sensing images. The tested result indicates that the influence of dust retention on the pixel spectra with different FVCs was consistent with that created with the simulated data. The finding could be beneficial for those making decisions on monitoring vegetation under dusty conditions and reducing dust pollution in mining areas using remote sensing technology.

Tracking the Land Use/Land Cover Change in an Area with Underground Mining and Reforestation via Continuous Landsat Classification

2019 ◽  
Vol 11 (14) ◽  
pp. 1719 ◽  
Author(s):  
Jiaxin Mi ◽  
Yongjun Yang ◽  
Shaoliang Zhang ◽  
Shi An ◽  
Huping Hou ◽  
...  
Keyword(s):  
Land Use ◽  
Random Forest ◽  
Land Cover ◽  
Large Scale ◽  
Underground Mining ◽  
Mining Area ◽  
Random Forest Classifier ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Mining Areas

Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas.

Analysis on Ground Subsidence in Underground Mining

2011 ◽  
Vol 383-390 ◽  
pp. 2201-2205
Author(s):  
Xin Xi Liu ◽  
Xue Zhi Wang
Keyword(s):  
Underground Mining ◽  
Ground Deformation ◽  
Coal Pillar ◽  
Mining Area ◽  
Ground Subsidence ◽  
Recovery Coefficient ◽  
Mining Width ◽  
Movement And Deformation ◽  
Relationship Of ◽  
The Relationship

Analysis on the characters of ground subsidence of Yangjiaping mining area, with same excavation depth and recovery coefficient, the numerical simulations to nonlinear large deformation using finite-difference method(FLAC) are achieved on the different strip extraction schemes that adopted different mining and reservation width. The result indicates that the subsidence values and horizontal deformation increases with the increasing of the strip extraction width on condition of the same recovery rate. Based on probability density function (PDF) method, the relationship of the coal pillar width, the mining width and ground deformation is acquired, which is some useful reference for using the strip extraction method to control the surface movement and deformation.

scholarly journals Two-Dimensional Modeling of the Influence of Underground Mining Direction on Slope Stability in Coordinated Open-Pit and Underground Mining

2021 ◽  
Author(s):  
Bowen Liu ◽  
Zhenwei Wang ◽  
Xinpin Ding ◽  
Zhitao Wang ◽  
Bin Li
Keyword(s):  
Rock Mass ◽  
Slope Stability ◽  
Underground Mining ◽  
Mining Area ◽  
Two Dimensions ◽  
Open Pit ◽  
Engineering Practice ◽  
Inverse Slope ◽  
Coal Wall ◽  
Mining Face

Abstract Under a background of coordinated open-pit and underground mining engineering practice in the Pingshuo mining area, a combination of numerical simulations and similar-model experiments was used to study the influence of the underground mining direction on slope deformation in two dimensions. The results show that the disturbance caused by inverse-slope mining is more obvious than that caused by along-slope mining. Underground mining presents an asymmetric influence on the open-pit slope; the slope rock mass on the open-off cut side is disturbed more than that on the coal-wall side. Compared with the slope in front of the advancing direction of the underground mining face, the degree of rock-mass damage and stress concentration of the slope of the open-off cut side are more serious. As such, in coordinated open-pit and underground mining practice, an along-slope mining direction is recommended to reduce adverse effects on slope stability and improve the recovery rate of coal resources.

scholarly journals Determination of the Ultimate Underground Mining Depth considering the Effect of Granular Rock and the Range of Surface Caving

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Rongxing He ◽  
Jing Zhang ◽  
Yang Liu ◽  
Delin Song ◽  
Fengyu Ren
Keyword(s):  
Numerical Simulation ◽  
Rock Mass ◽  
Mechanical Model ◽  
Surface Deformation ◽  
Underground Mining ◽  
Mining Area ◽  
Open Pit ◽  
Open Pit Mining ◽  
Mining Depth

Continuous mining of metal deposits leads the overlying strata to move, deform, and collapse, which is particularly obvious when open-pit mining and underground mining are adjacent. Once the mining depth of the adjacent open-pit lags severely behind the underground, the ultimate underground mining depth needs to be studied before the surface deformation extends to the open-pit mining area. The numerical simulation and the mechanical model are applied to research the ultimate underground mining depth of the southeast mining area in the Gongchangling Iron mine. In the numerical simulation, the effect of granular rock is considered and the granular rock in the collapse pit is simplified as the degraded rock mass. The ultimate underground mining depth can be obtained by the values of the indicators of surface movement and deformation. In the mechanical model, the modified mechanical model for the progressive hanging wall caving is established based on Hoke’s conclusion, which considers the lateral pressure of the granular rock. Using the limiting equilibrium analysis, the relationship of the ultimate underground mining depth and the range of surface caving can be derived. The results show that the ultimate underground mining depth obtained by the numerical simulation is greater than the theoretical calculation of the modified mechanical model. The reason for this difference may be related to the assumption of the granular rock in the numerical simulation, which increases the resistance of granular rock to the deformation of rock mass. Therefore, the ultimate underground mining depth obtained by the theoretical calculation is suggested. Meanwhile, the surface displacement monitoring is implemented to verify the reasonability of the ultimate underground mining depth. Monitoring results show that the indicators of surface deformation are below the critical value of dangerous movement when the underground is mined to the ultimate mining depth. The practice proves that the determination of the ultimate underground mining depth in this work can ensure the safety of the open-pit and underground synergetic mining.

scholarly journals InSAR monitoring surface deformation induced by underground mining using Sentinel-1 images

2020 ◽  
Vol 382 ◽  
pp. 237-240
Author(s):  
Ling Zhang ◽  
Daqing Ge ◽  
Xiaofang Guo ◽  
Bin Liu ◽  
Man Li ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Surface Deformation ◽  
Underground Mining ◽  
Deformation Gradient ◽  
Mining Area ◽  
Interferometric Synthetic Aperture Radar ◽  
Mining Areas ◽  
Temporal Decorrelation ◽  
Land Deformation ◽  
Small Baseline

Abstract. Land subsidence can be caused by underground mining activities. Interferometric Synthetic Aperture Radar (InSAR) has became an economic, effective and accurate technique for land deformation survey and monitoring. In mining areas, there may be several factors to overcome for the succsessful application of InSAR, such as temporal decorrelation and detectable deformation gradient, that limit the ability of InSAR to monitoring rapid land subsidence. In this paper, images obtained by the Sentinel-1 satellite with 6 or 12 d revisiting time are used to improve the ability to detect a deformation gradient, and reduce the influence of temporal decorrelation. By combining Small Baseline Subsets (SBAS) and Interferometric Point Target Analysis (IPTA) methods, using the Nanhu mining area in Tangshan as an example, the spatial continuous results of land subsidence in this mining area are obtained with a 70 cm per year maximum rate, which clearly characterizes the deformation field and its deformation process. The results show that InSAR is a useful way to monitor land subsidence in a mining area and provides further data for environment mine restoration.

Analysis of the Relative Position of the Slope and Underground Mining Area and its Influence Properties

2013 ◽  
Vol 634-638 ◽  
pp. 3277-3281 ◽  
Author(s):  
Shi Guo Sun ◽  
Hong Yang ◽  
Chun Sheng Li ◽  
Bao Lin Zhang ◽  
Jia Wang ◽  
...  
Keyword(s):  
Slope Stability ◽  
Underground Mining ◽  
Mining Area ◽  
Open Pit ◽  
Stability Factor ◽  
Mining Depth ◽  
Extracellular Region ◽  
Geological Conditions ◽  
Slope Rock ◽  
The Stability

The stability state of slope rock mass is relating to each other’s relative location during the transformation from open-pit to underground mining, it’s the most disadvantageous influence on the slope stability when the underground mining area is located in the toe of slope, and it’s the best influence as in the slope extracellular region. Slope stability factor changes with the geometric dimensions of underground mining increased, but not in direct proportion. Under the condition of constant geometric dimensions of mining area, the influence on slope stability is changing with the mining depth increased. Thus indicating that the influence on slope stability by underground mining has its spatial property, and to determine the specific influence value requires a combination of many factors, such as the relationship of relative spatial position, the geometric dimensions of mining area, engineering geological conditions and so on.

scholarly journals Mapping Annual Land Disturbance and Reclamation in a Surface Coal Mining Region Using Google Earth Engine and the LandTrendr Algorithm: A Case Study of the Shengli Coalfield in Inner Mongolia, China

2020 ◽  
Vol 12 (10) ◽  
pp. 1612 ◽  
Author(s):  
Wu Xiao ◽  
Xinyu Deng ◽  
Tingting He ◽  
Wenqi Chen
Keyword(s):  
Inner Mongolia ◽  
Land Reclamation ◽  
Underground Mining ◽  
Surface Mining ◽  
Mining Area ◽  
Google Earth ◽  
Open Pit ◽  
Open Pit Mining ◽  
Landsat Images ◽  
Google Earth Engine

The development and utilization of mining resources are basic requirements for social and economic development. Both open-pit mining and underground mining have impacts on land, ecology, and the environment. Of these, open-pit mining is considered to have the greatest impact due to the drastic changes wrought on the original landform and the disturbance to vegetation. As awareness of environmental protection has grown, land reclamation has been included in the mining process. In this study, we used the Shengli Coalfield in the eastern steppe region of Inner Mongolia to demonstrate a mining and reclamation monitoring process. We combined the Google Earth Engine platform with time series Landsat images and the LandTrendr algorithm to identify and monitor mining disturbances to grassland and land reclamation in open-pit mining areas of the coalfield between 2003 and 2019. Pixel-based trajectories were used to reconstruct the temporal evolution of vegetation, and sequential Landsat archive data were used to achieve accurate measures of disturbances to vegetation. The results show that: (1) the proposed method can be used to determine the years in which vegetation disturbance and recovery occurred with accuracies of 86.53% and 78.57%, respectively; (2) mining in the Shengli mining area resulted in the conversion of 89.98 km2 of land from grassland, water, etc., to barren earth, and only 23.54 km2 was reclaimed, for a reclamation rate of 26.16%; and (3) the method proposed in this paper can achieve fast, efficient identification of surface mining land disturbances and reclamation, and has the potential to be applied to other similar areas.

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