scholarly journals Mine Geological Environment Monitoring and Risk Assessment in Arid and Semiarid Areas

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jiaqi Jin ◽  
Chicheng Yan ◽  
Yixuan Tang ◽  
Yilong Yin
Keyword(s):  
Coal Mining ◽  
Ecological Restoration ◽  
Surface Deformation ◽  
Yellow River ◽  
Mining Area ◽  
Deformation Monitoring ◽  
Surface Subsidence ◽  
Mining Areas ◽  
Coal Mining Area ◽  
Arid And Semiarid

Along with the accelerated shift of coal mining to the ecologically fragile west, the contradiction between coal resource development and ecological protection in the western arid and semiarid coal mining areas is rapidly intensifying. Based on the above background, this thesis takes the coal mining area in the arid and semiarid regions as an example; applies the theories of ecology, coal mining subsidence, geodesy, and ecological restoration; uses remote sensing in synthetic aperture radar (SAR), geographic information system (GIS), and mathematical modelling to reveal the ecological evolution law of the mining area; measures the ecological damage of the mining area; and then proposes a reasonable ecological restoration strategy. The surface deformation monitoring study in the study area shows that on the whole, some areas in the study area have different degrees of surface subsidence disasters, and the maximum surface subsidence value exceeds 800 mm. From the distribution of surface subsidence in the study area, surface subsidence disasters mainly occur in the eastern and central mountainous areas rich in coal resources, as well as in the mining areas west of the Yellow River, and the subsidence basins are distributed in a series of irregular concentric ovals. In terms of the scale of surface subsidence in the study area, a total of 230.03 km2 of land in the study area showed surface subsidence hazards during the monitoring period, accounting for 13.78% of the total area of the study area, of which the area of severe subsidence was 44.98 km2 (2.69%). The area of more serious subsidence area is 101.33 km2 (6.07%), and the area affected by subsidence is 83.72 km2 (5.01%).

Slow surface subsidence and its impact on shallow loess landslides in a coal mining area

CATENA ◽  
2022 ◽  
Vol 209 ◽  
pp. 105830
Author(s):  
Dongdong Yang ◽  
Haijun Qiu ◽  
Shuyue Ma ◽  
Zijing Liu ◽  
Chi Du ◽  
...  
Keyword(s):  
Coal Mining ◽  
Mining Area ◽  
Surface Subsidence ◽  
Coal Mining Area ◽  
Slow Surface ◽  
Loess Landslides

Ecological Risk Assessment of Yulin Coal Mining Area: Based on the PETAR Method

2013 ◽  
Vol 726-731 ◽  
pp. 1115-1120 ◽  
Author(s):  
Li Zhang
Keyword(s):  
Risk Assessment ◽  
Coal Mining ◽  
Qualitative Evaluation ◽  
Mining Area ◽  
Ecological Effects ◽  
Ecological Effect ◽  
Ecological Risks ◽  
Mining Areas ◽  
Coal Mining Area ◽  
Risk Sources

In order to unravel the correlation and causality between multi-stressor sources, multi-risk receptors and multi-type ecological effects of the Yulin Coal Mining Area. Through qualitative evaluation, this study preliminarily described the main stressor sources, risk receptors and the largest ecological effect over the Yulin coal mining area and progressive and conductive relation among the stressor sources, risk receptors and ecological effects using the Procedure for Ecological Tiered Assessment of Risk method (PETAR). The PETAR method seems to be operable and effective in evaluating coal mining areas ecological risks with multiple risk sources, risk receptors and multi-type ecological effects.

scholarly journals Research on Surface Deformation of Ordos Coal Mining Area by Integrating Multitemporal D-InSAR and Offset Tracking Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jiaming Yao ◽  
Xin Yao ◽  
Zuoqi Wu ◽  
Xinghong Liu
Keyword(s):  
High Resolution ◽  
Large Deformation ◽  
Coal Mining ◽  
Surface Deformation ◽  
Mining Area ◽  
Deformation Field ◽  
Coal Mining Area ◽  
Working Face ◽  
Offset Tracking ◽  
Tracking Technology

Underground mining in coal mining areas will induce large-scale, large-gradient surface deformation, threatening the safety of people’s lives and property in nearby areas. Due to mining-related subsidence is characterized by fast displacement and high nonlinearity, monitoring this process by using traditional and single interferometric synthetic aperture radar (InSAR) technology is very challenging, and it cannot accurately and quantitatively calculate the deformation of the mining area. In this paper, we proposed a new method that combines both multitemporal consecutive D-InSAR and offset tracking technology to construct a complete deformation field of the coal mining area. Taking into account the accuracy of multitemporal consecutive D-InSAR in calculating small deformation areas and the ability of offset tracking to measure large deformation areas, we utilized their respective advantages to extract the surface influence range and applied an adaptive spatial filtering method to integrate their respective results for inversion of the deformation field. 12 ascending high-resolution TerraSAR-X images (2 m) from September 3, 2018, to October 26, 2019, and 39 descending Sentinel-1 TOPS SAR images from August 5, 2018, to November 4, 2019, in the Ordos Coalfield located at Inner Mongolia, China, were utilized to obtain the whole subsidence field of the working faces F6211 and F6207 during the 454-day mining period. The GPS monitoring station located in the direction of the mining surface is used to verify the accuracy of the above method; at the same time, to a certain extent, the difference between the unmanned aerial vehicle’s DSM data acquired after coal mining and the Shuttle Radar Topography Mission (STRM) DEM can qualitatively verify the accuracy of the results. Our results show that the results of TerraSAR are basically consistent with the deformation trend of GPS data, and that of Sentinel-1 have large errors compared with GPS. The maximum central subsidence reaches ~12 m in the working face F6211 and ~4 m in the working face F6207. In the working face F6207, the good agreement between GPS and TerraSAR results indicated that the method above using high-resolution SAR data could be reliable for monitoring the large deformation area in the mining field.

scholarly journals Deformation Monitoring in an Alpine Mining Area in the Tianshan Mountains Based on SBAS-InSAR Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Qingsong Du ◽  
Guoyu Li ◽  
Yu Zhou ◽  
Mingtang Chai ◽  
Dun Chen ◽  
...  
Keyword(s):  
Mining Area ◽  
Deformation Monitoring ◽  
Tianshan Mountains ◽  
Surface Subsidence ◽  
Mining Activities ◽  
Study Region ◽  
Mining Site ◽  
Maximum Settlement ◽  
Mining Areas ◽  
Sbas Insar

The fragile habitat of alpine mining areas can be greatly affected by surface disturbances caused by mining activities, particularly open-pit mining activities, which greatly affect the periglacial environment. SBAS-InSAR technology enables the processing of SAR images to obtain highly accurate surface deformation information. This paper applied SBAS-InSAR technology to obtain three years of surface subsidence information based on the 89-scene Sentinel-1A SLC products, covering a mining area (tailings and active areas) in the Tianshan Mountains and its surroundings from 25th December 2017 to 2nd January 2021. The data were adopted to analyze the characteristics of deformation in the study region and the mining areas, and the subsidence accumulation was compared with field GNSS observation results to verify its accuracy. The results showed that the study area settled significantly, with a maximum settlement rate of −44.80 mm/a and a maximum uplift rate of 28.04 mm/a. The maximum settlement and accumulation of the whole study area over the three-year period were −129.39 mm and 60.49 mm, respectively. The mining area had a settlement value of over 80 mm over the three years. Significantly, the settlement rates of the tailings and active areas were −35 mm/a and −40 mm/a, respectively. Debris accumulation in the eastern portion of the tailings and active areas near the mountain was serious, with accumulation rates of 25 mm/a and 20 mm/a, respectively, and both had accumulation amounts of around 70 mm. For mine tailing pile areas with river flows, the pile locations and environmental restoration should be appropriately adjusted at a later stage. For gravel pile areas, regular cleaning should be carried out, especially around the mining site and at the tunnel entrances and exits, and long-term deformation monitoring of these areas should be carried out to ensure safe operation of the mining site. The SBAS-InSAR measurements were able to yield deformations with high accuracies over a wide area and cost less human and financial resources than the GNSS measurement method. Furthermore, the measurement results were more macroscopic, with great application value for surface subsidence monitoring in alpine areas.

scholarly journals THE GROWTH OF LOCAL TREE SPECIES ON POST-COAL MINING AREAS IN EAST KALIMANTAN

2020 ◽  
Vol 7 (2) ◽  
pp. 83-97
Author(s):  
Burhanuddin Adman ◽  
Ardiyanto Wahyu Nugroho ◽  
Ishak Yassir
Keyword(s):  
Coal Mining ◽  
Tree Species ◽  
Extreme Temperature ◽  
Mining Area ◽  
High Survival ◽  
Mining Areas ◽  
Coal Mining Area ◽  
East Kalimantan ◽  
Survival And Growth ◽  
Made In

Post-coal mining areas need rehabilitation to restore its functionality. Not all plants could grow well on bare ex-coal mining area because of the excessive light intensity and extreme temperature fluctuations. This study is aimed to determine suitable local tree species for rehabilitating mined areas. Planting was carried out in November 2012, and observations were made in November 2015. The study site was in the district of Samboja, Kutai Kartanegara, East Kalimantan Province, Indonesia. Research results revealed that seven tree species survived well in the ex-coal mining land, i.e., Vitex pinnata L., Syzygium scortechinii (Merr.) Merr. & Perry, Syzygium polyanthum (Wight) Walp., Shorea balangeran (Korth.) Burck, Macaranga motleyana (Mull.Arg.) Mull.Arg., Cleistanthus myrianthus (Hassk.) Kurz and Syzygium lineatum (DC.) Merr. & L.M. Perry. From the seven species V. pinnata, Sy. scortechinii and Sy. polyanthum performed best in both survival and growth rates. This study suggests those three species are excellent local tree species for ex-coal mining rehabilitation, not only because of their high survival rate (≥80%) and fast-growing but also they produce favourable fruits and flowers for wildlife.

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.

Information Required for Estimating The Indicator of Forest Reclamation Success in Ex Coal-Mining Area

2016 ◽  
Vol 3 (1) ◽  
pp. 182
Author(s):  
Hasriani Muis ◽  
I Nengah Surati Jaya ◽  
Muhammad Buce Saleh ◽  
Kukuh Murtilakono
Keyword(s):  
Discriminant Analysis ◽  
Coal Mining ◽  
Basal Area ◽  
Mining Area ◽  
Site Quality ◽  
Mining Areas ◽  
Coal Mining Area ◽  
Key Indicator ◽  
Forest Reclamation ◽  
Key Indicators

<p>This paper describes how the information of the key indicators for assessing the degree of forest reclamation success in ex coal-mining area was identified. Those indicators were analyzed using the descriptive statistic as well as the discriminant analysis on the basis of biophysical data representing age class of vegetation after reclamation. The main objective of the study was to find out the predominant key indicator that determines the success of forest reclamation in ex coal-mining areas. This study found that the variance of basal area, green biomass and increment was relatively high between young plantation and old plantation. The study confirmed that the variation of the success of reclamation was strongly influenced by site quality. . The study concluded that the best indicators to be used for assessing the success of forest reclamation was the increment providing accuracy more than 79.6% either for indicator five or three classes.</p>

Detecting surface subsidence in coal mining area based on DInSAR technique

2013 ◽  
Vol 24 (3) ◽  
pp. 449-456 ◽  
Author(s):  
Shaochun Dong ◽  
Hongwei Yin ◽  
Suping Yao ◽  
Fei Zhang
Keyword(s):  
Coal Mining ◽  
Mining Area ◽  
Surface Subsidence ◽  
Coal Mining Area
Sign in / Sign up

Export Citation Format

Share Document