A coherence estimation method for multi-temporal D-InSAR deformation monitoring in coal mining areas

2005 ◽  
Author(s):  
Junhai Gao ◽  
Daqing Ge ◽  
Linxin Wu ◽  
Zuoru Yin ◽  
Zhiyi Deng ◽  
...  
Keyword(s):  
Coal Mining ◽  
Estimation Method ◽  
Deformation Monitoring ◽  
Mining Areas ◽  
Multi Temporal ◽  
Coherence Estimation

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%).

scholarly journals Time Series InSAR Three-Dimensional Displacement Inversion Model of Coal Mining Areas Based on Symmetrical Features of Mining Subsidence

2021 ◽  
Vol 13 (11) ◽  
pp. 2143
Author(s):  
Longkai Dong ◽  
Chao Wang ◽  
Yixian Tang ◽  
Fuquan Tang ◽  
Hong Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Three Dimensional ◽  
Mining Area ◽  
Deformation Monitoring ◽  
Mining Subsidence ◽  
Surface Movement ◽  
Mining Areas ◽  
Multi Temporal ◽  
Movement Parameters ◽  
Mean Square Errors

The three-dimensional (3-D) displacements of mining areas is the basis of studying the mining subsidence law and obtaining surface movement parameters. The traditional multi-temporal interferometry synthetic aperture radar (InSAR) technology can only obtain the surface deformation in line-of-sight (LOS) direction, even if some methods can obtain the 3-D displacements of mining area based on InSAR. However, it has high data requirements for data types, which are not conducive to the inversion of 3-D displacements. In this paper, the symmetry of the surface basin caused by mining subsidence under different mining degrees is analyzed. According to the basic symmetrical features of mining subsidence—that the surface vertical displacement and horizontal displacement in near horizontal coal seam is symmetrical with respect to the main section of the basin, combined with time series InSAR technology (TS-InSAR)—a novel method for retrieving the 3-D displacement results from a single-geometry InSAR dataset based on symmetrical features (hereafter referred to as the SGI-SF method) is proposed. The SGI-SF method first generates multi-temporal observations of LOS displacement from a single-geometry InSAR dataset, and then transforms them into multi-temporal observations of 3-D displacement datasets according to symmetrical features. There is no necessity to obtain the surface movement parameters from the measured data to calculate 3-D displacement fields. Finally, the time series of 3-D displacements are estimated from multi-temporal 3-D displacements using the singular value decomposition (SVD) method. Nine descending Sentinel-1 images from the Yulin mining area of China are used to test the proposed SGI-SF method. The results show that the average root mean square errors (RMSE) in the vertical and horizontal direction of the three-dimensional deformations are approximately 9.28 mm and 13.10 mm, respectively, which are much smaller than mining-induced displacements and can provide support for deformation monitoring in mining areas.

Strategies for follow-up care and utilisation of closing and flooding in European hard coal mining areas

2012 ◽  
Vol 89 ◽  
pp. 51-61 ◽  
Author(s):  
C. Klinger ◽  
A. Charmoille ◽  
J. Bueno ◽  
G. Gzyl ◽  
B. Garzon Súcar
Keyword(s):  
Coal Mining ◽  
Hard Coal ◽  
Mining Areas ◽  
Follow Up Care ◽  
Hard Coal Mining

Laws governing the decline of coal mining areas

2004 ◽  
pp. 973-976
Author(s):  
Guorong Li ◽  
Zhensheng Wang ◽  
Tao Lu
Keyword(s):  
Coal Mining ◽  
Mining Areas
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