scholarly journals Inversion and Analysis of Mining Subsidence by Integrating DInSAR, Offset Tracking, and PIM Technology

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xiaobo Xu ◽  
Chao Ma ◽  
Dajun Lian ◽  
Dezheng Zhao
Keyword(s):  
Large Amplitude ◽  
Underground Mining ◽  
Field Investigation ◽  
Shaanxi Province ◽  
Phase Gradient ◽  
Mine Subsidence ◽  
Mining Areas ◽  
Probability Integral Method ◽  
Subsidence Monitoring ◽  
Offset Tracking

High-intensity underground mining generates considerable surface subsidence in mining areas, including ground cracks and collapse pits on roads and farmland, threatening the safety of buildings. Large-amplitude subsidence (e.g., >2 m) is usually characterized by a large phase gradient in interferograms, leading to severe phase decorrelation and unwrapping errors. Therefore, the subsidence on the surface cannot be well derived simply using conventional differential interferometric synthetic aperture radar (DInSAR) or other geodetic measurements. We propose a new method that combines both DInSAR and subpixel offset-tracking technology to improve mine subsidence monitoring over large areas. We utilize their respective advantages to extract both the spatial boundaries and the amplitude of displacements. Using high-resolution RADARSAT-2 SAR images (5 m) acquired on February 13, 2012, and November 27, 2012, in the Shendong Coalfield located at the border between Shaanxi Province and Inner Mongolia Province, China, we obtain the subcentimetre-level subsidence of the mine boundary by DInSAR and resolve the metre-level mine subsidence centre based on subpixel offset tracking. The whole subsidence field is obtained by combining and analyzing the subcentimetre-level and the metre-level subsidence. We use the probability integral method (PIM) function model to fit the boundary and central mine subsidence to reconstruct the spatial distribution of the mine subsidence. Our results show that the maximum central subsidence reaches ~4.0 m (beyond the monitoring capabilities of DInSAR), which is generally in agreement with the maximum subsidence of ~4.0-5.0 m from field investigation. We also model the boundary and the central subsidence (the final fitting coefficient is 0.978). Our findings indicate that the offset-tracking method can compensate for the deficiency of DInSAR in large-amplitude subsidence extraction, and the inclusion of the PIM technique helps reconstruct the whole subsidence field in mining areas.

scholarly journals Assesment Work Fatigue To Workers In Environment Underground Mining Areas Based On Fatigue Assesment Scale Questionnaires

2020 ◽  
Vol 202 ◽  
pp. 05013
Author(s):  
Siti Rachmawati ◽  
Miftaqul Aktsari ◽  
Anis Suryaningsih ◽  
Hashfi Hawali Abdul Matin ◽  
Iwan Suryadi
Keyword(s):  
Rating Scale ◽  
Underground Mining ◽  
Sleep Time ◽  
Type Ii ◽  
Work Time ◽  
Fatigue Assessment ◽  
Mining Areas ◽  
Hours Of Work ◽  
Fatigue Evaluation ◽  
Descriptive Method

Fatigue is recognized as a high potential risk for accidents and therefore an assessment of work fatigue is required. The purpose of this study is to describe the overall work fatigue assessment and based on work fatigue factors using questionnaires for the fatigue rating scale for workers in underground mining areas. This study used a descriptive method to describe the overall assessment of work fatigue and assessment of work fatigue based on factors related to fatigue using questionnaire scale fatigue assessment of workers in underground mining areas at PT. Y. Overall fatigue assessment based on fatigue evaluation questionnaire results obtained 54.55% of workers who experience fatigue. Fatigue assessment based on factors related to work fatigue shows that workers who tend to experience fatigue are> 45 years of age, <7 hours of sleep,> 5 years of work, 12 hours of work, supervisor type II / jumbo operator drill, jumbo drill operator, LHD operator, and service crew / helper jumbo drill, work climate> NAB (> 29.00 C) and noise> NAB (> 85 dB A). Underground mining workers tend to experience fatigue. The older the worker's age, the less sleep time, the longer the work period, the longer work time, the heavier the type of work, the hotter the working climate and the noisier it tends to experience fatigue.

Mine Subsidence Monitoring Using Multi-source Satellite SAR Images

2007 ◽  
Vol 73 (3) ◽  
pp. 259-266 ◽  
Author(s):  
Linlin Ge ◽  
Hsing-Chung Chang ◽  
Chris Rizos
Keyword(s):  
Sar Images ◽  
Mine Subsidence ◽  
Subsidence Monitoring

scholarly journals Hydrological Characteristics of Ordovician Karst Top in a Deep Region and Evaluation of Its Threat to Coal Mining: A Case Study for the Weibei Coalfield in Shaanxi Province, China

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Tao Li ◽  
Jiarui Zhang ◽  
Ying Gao ◽  
Xinqi Cao ◽  
Hongyang Liu ◽  
...  
Keyword(s):  
Coal Mining ◽  
North China ◽  
Water Pressure ◽  
Water Inrush ◽  
Drainage Water ◽  
Shaanxi Province ◽  
Water Drainage ◽  
Mining Areas ◽  
Hydrogeological Characteristics ◽  
In Situ Experiments

Widely distributed in North China, Ordovician karst is characterized by having high thickness, nonuniform aquosity, and significant water pressure-bearing properties. Deep mining in North China is threatened by associated water hazards; hence, research on the hydrogeological characteristics of deep Ordovician karst is needed. In this study, the Weibei coalfield in Shaanxi Province, China, was selected as the study area, especially mines in the Hancheng and Chenghe mining areas. In situ experiments, including water pumping, water drainage, water injecting and water pressure, and laboratory experiments, were conducted to study the hydrogeological characteristics of the Ordovician karst top in the study area. A comprehensive analysis was conducted on controlling factors for the development of the Ordovician karst top in the study area, and a method for evaluating the water inrush risk in coal mining areas based on karst hydrogeological characteristics was proposed. The research results indicated that the Ordovician karst top in the study area was characterized by heterogeneity, vertical zonation, and partially filled properties, which were mainly controlled by two factors: sedimentation and tectonism. The hydrogeological conditions of the Ordovician karst could be divided into three types: nonfilled and nonsignificant tectonism, filled and nonsignificant tectonism, and significant tectonism. Among them, the filled and nonsignificant tectonism type Ordovician karst top type had a filling thickness of 20 m. Based on karst hydrogeological characteristics, the methods were proposed to evaluate the water inrush risk in the coal mining floor. The practical tests verified the methods.

scholarly journals Retrieving 3-D Large Displacements of Mining Areas from a Single Amplitude Pair of SAR Using Offset Tracking

2017 ◽  
Vol 9 (4) ◽  
pp. 338 ◽  
Author(s):  
Zefa Yang ◽  
Zhiwei Li ◽  
Jianjun Zhu ◽  
Axel Preusse ◽  
Huiwei Yi ◽  
...  
Keyword(s):  
Large Displacements ◽  
Mining Areas ◽  
Offset Tracking

scholarly journals NUMERICAL MODELLING FOR UNDERGROUND MINING RELATED GEOTECHNICAL ISSUES

2013 ◽  
Vol 35 (3) ◽  
pp. 13-24
Author(s):  
L. Florkowska
Keyword(s):  
Numerical Modeling ◽  
Numerical Modelling ◽  
Continuous Monitoring ◽  
Underground Mining ◽  
Mining Areas ◽  
Geotechnical Problems ◽  
Mathematical And Numerical Modeling

Abstract Issues presented in this work relate to geotechnical problems that are specific to the mining areas. The paper discusses the methodology of mathematical and numerical modeling of these problems. Examples contained in the paper include: predicting the influence of mining exploitation on a detached building and evaluating the effectiveness of the building protection with the trench. Possible applications of numerical modeling as a tool to aid the continuous monitoring of the building state during the exploitation have also been discussed

scholarly journals Landscape Sustainability Evaluation of Ecologically Fragile Areas Based on Boltzmann Entropy

2020 ◽  
Vol 9 (2) ◽  
pp. 77 ◽  
Author(s):  
Jingyi Xu ◽  
Xiaoying Liang ◽  
Hai Chen
Keyword(s):  
Configurational Entropy ◽  
Remote Sensing Data ◽  
Quantitative Relationship ◽  
Field Investigation ◽  
Shaanxi Province ◽  
Landscape Sustainability ◽  
Boltzmann Entropy ◽  
Digital Elevation ◽  
Elevation Model ◽  
Evaluation Matrix

From the perspective of landscape, it is important to evaluate the landscape sustainability of ecologically fragile areas and explore temporal and spatial evolution laws to promote their sustainable development. Presently, most studies on the analysis of landscape Boltzmann entropy (also called configurational entropy) are based on a single landscape, and most of these studies are theoretical discussions. However, there are few case studies on landscape ecology. The main objectives of this paper are to explore a quantitative relationship between Boltzmann entropy and landscape sustainability, to propose a method for evaluating landscape sustainability based on Boltzmann entropy, and to evaluate the sustainability of diverse landscapes in Mizhi County, Shaanxi Province, China. This article uses digital elevation model (DEM) data with a spatial resolution of 30 m in Mizhi County. The remote sensing data on Mizhi County from 2000 were obtained by the Landsat Enhanced Thematic Mapper (ETM) + sensor, and the high-resolution image of Mizhi County from 2015 was obtained by the Gaofen-1 satellite. In this article, the subbasins are taken as the evaluation unit, and the Boltzmann entropy of Mizhi County is calculated based on the experts’ scoring of landscape sustainability in the study area. Through the analysis of landscape sustainability results from 216 subbasins in Mizhi County in 2000 and 2015, the following conclusions are drawn: (1) the evaluation matrix proposed in this paper is effective, and the Boltzmann entropy obtained by this method can directly reflect the level of landscape sustainability; (2) during the research period, the landscape sustainability of Mizhi County showed a good trend overall, especially the three townships of Taozhen, Shadian, and Shigou, which were significantly improved, and these findings were consistent with the field investigation; (3) on the spatial level, the landscape sustainability of mid-eastern Mizhi County is relatively poor compared to that in other regions, but the sustainability is also slowly increasing.

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.

High-rate GNSS positioning for tracing anthropogenic seismic activity

2020 ◽  
Author(s):  
Iwona Kudłacik ◽  
Jan Kapłon ◽  
Grzegorz Lizurek ◽  
Mattia Crespi ◽  
Grzegorz Kurpiński
Keyword(s):  
Seismic Activity ◽  
Underground Mining ◽  
High Rate ◽  
Anthropogenic Activity ◽  
Mining Areas ◽  
Seismological Data ◽  
Band Pass ◽  
Mining Tremors ◽  
Natural Earthquakes ◽  
First Time

&lt;p&gt;High-rate GNSS observations are usually related to earthquake analysis and structural monitoring. The sampling frequency is in the range of 1-100 Hz and observations are processed in the kinematic mode. Most of the research on short-term dynamic deformations is limited to natural earthquakes with magnitudes exceeding 5 and amplitudes of at least several centimetres up to even meters. The high frequency GNSS stations positions monitoring is particularly important on mining areas due to the mining damages. On the underground mining areas the seismic tremors are regular and there are several hundreds of events annually of magnitude over 2 with maximum magnitudes of 4. As mining tremors are shallow and very frequent, they cause mining damages on infrastructure.&lt;/p&gt;&lt;p&gt;Here, we presented the application of GNSS-seismology to the analysis of anthropogenic seismic activity, where the event magnitude and amplitude of displacements significantly lower. We examined the capacity to detect mining tremors with high-rate GPS observations and demonstrated, for the first time to our knowledge that even subcentimeter ground vibrations caused by anthropogenic activity can be measured this way with a very good agreement with seismological data. One of the most-felt mining shocks in Poland in recent years occurred on January 29, 2019 (12:53:44 UTC) M3.7 event in the area of Legnica-G&amp;#322;og&amp;#243;w Copper District and was successfully registered by high-rate GNSS stations co-located with seismic stations. In this mining tremor the peak ground displacements reached 2-16 &amp;#160;mm and show the Pearson&amp;#8217;s correlation value in range of 0.61 to 0.94 for band-pass filtered horizontal displacements.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document