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.

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 Deformation monitoring and prediction for residential areas in the Panji mining area based on an InSAR time series analysis and the GM-SVR model

2019 ◽  
Vol 11 (1) ◽  
pp. 738-749
Author(s):  
Jinchao Li ◽  
Fei Gao ◽  
Jiaguo Lu ◽  
Tingye Tao
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Mining Area ◽  
Deformation Monitoring ◽  
Dynamic Monitoring ◽  
Ground Subsidence ◽  
Support Vector ◽  
Residential Areas ◽  
Mining Areas ◽  
Series Analysis

Abstract Underground coal mining activities often cause ground subsidence and damage to surface construction, which seriously threatens the lives and property of residents in mining areas. In this paper, the deformation of the Yang Juzhuang village, which is a residential area in the Huainan mining area (China), was monitored through an interferometric synthetic aperture radar (InSAR) time series analysis. The vertical displacements were detected using thirteen Sentinel-1A images that were acquired between December 2016 and May 2017. The validity and applicability of the method are verified by comparing the acquired images with the GPS measurement results. Because of the deformation characteristics of the mining area, a prediction model that is combined with a grey support vector machine regression (GM-SVR) is proposed, and the practical effects of the model are verified using the deformation monitoring results of the study area. The combination of this model and SBAS-InSAR provides rapid dynamic monitoring and enables the issuance of disaster warnings in the region.

scholarly journals Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas

2021 ◽  
Vol 13 (8) ◽  
pp. 1497
Author(s):  
Mengyao Shi ◽  
Honglei Yang ◽  
Baocun Wang ◽  
Junhuan Peng ◽  
Zhouzheng Gao ◽  
...  
Keyword(s):  
Time Series ◽  
Integral Method ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Mining Subsidence ◽  
Economic Losses ◽  
Mining Areas ◽  
Boundary Constraint ◽  
Probability Integral Method ◽  
Probability Integral

Coal-mining subsidence causes ground fissures and destroys surface structures, which may lead to severe casualties and economic losses. Time series interferometric synthetic aperture radar (TS-InSAR) plays an important role in surface deformation detection and monitoring without the restriction of weather and sunlight conditions. In addition, the probability integral method (PIM) is a surface movement model that is widely used in the field of mining subsidence. In recent years, the integration of TS-InSAR and the PIM has been extensively studied. In this paper, we propose a new method to estimate mining subsidence with the PIM based on TS-InSAR results. This study focuses on the improvement of a boundary constraint and dynamic parameter estimation in the PIM through the inversion of the line-of-sight (LOS) time series deformation derived by TS-InSAR. In addition, 45 Sentinel-1A images from 17 June 2015 to 27 December 2017 of a coal mine in Jiaozuo are utilized to acquire the surface displacement. We apply a time series deformation analysis using small baseline subsets (SBAS) and place the results into an improved PIM to estimate the mining parameters. The simulated mining subsidence is highly consistent with the leveling data, exhibiting an RMSE of 0.0025 m. Compared with the conventional method, the proposed method is more accurate in discovering displacement in mining areas. In the final section of this paper, some sources of error that affect the experiment are discussed.

scholarly journals An Improved Multi-Sensor MTI Time-Series Fusion Method to Monitor the Subsidence of Beijing Subway Network during the Past 15 Years

2020 ◽  
Vol 12 (13) ◽  
pp. 2125
Author(s):  
Li Duan ◽  
Huili Gong ◽  
Beibei Chen ◽  
Chaofan Zhou ◽  
Kunchao Lei ◽  
...  
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Mean Squared Error ◽  
Deformation Monitoring ◽  
Urban Rail Transit ◽  
Stable Operation ◽  
Urban Rail ◽  
Urban Safety ◽  
Multi Temporal ◽  
Beijing Subway

Land subsidence threatens the stable operation of urban rail transit, including subways. Obtaining deformation information during the entire life-cycle of a subway becomes a necessary means to guarantee urban safety. Restricted by sensor life and cost, the single-sensor Multi-temporal Interferometric Synthetic Aperture Radar (MTI) technology has been unable to meet the needs of long-term sequence, high-resolution deformation monitoring, especially of linear objects. The multi-sensor MTI time-series fusion (MMTI-TSF) techniques has been proposed to solve this problem, but rarely mentioned. In this paper, an improved MMTI-TSF is systematically explained and its limitations are discussed. Taking the Beijing Subway Network (BSN) as a case study, through cross-validation and timing verification, we find that the improved MMTI-TSF results have higher accuracy (R2 of 98% and, Root Mean Squared Error (RMSE) of 4mm), and compared with 38 leveling points, the fitting effect of the time series is good. We analyzed the characteristics of deformation along the BSN over a 15-year periods. The results suggest that there is a higher risk of instability in the eastern section of Beijing Subway Line 6 (L6). The land subsidence characteristics along the subway lines are related to its position from the subsidence center, and the edge of the subsidence center presents a segmented feature.

scholarly journals Three-Dimensional Physical Similarity Simulation of the Deformation and Failure of a Gas Extraction Surface Well in a Mining Area

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Junhui Fu ◽  
Haitao Sun ◽  
Guangcai Wen ◽  
Rifu Li
Keyword(s):  
Shear Deformation ◽  
Compressive Strain ◽  
Three Dimensional ◽  
Mining Area ◽  
Gas Extraction ◽  
Horizontal Shear ◽  
Deformation And Failure ◽  
Key Strata ◽  
Mining Areas ◽  
Rock Movement

Surface well deformation and failure in a mining area are a key issue challenging the surface well gas extraction technique. To provide information for the design of gas extraction surface wells in mining areas, the deformation and failure of surface wells with different materials under the influence of mining-induced rock movement were analyzed based on a three-dimensional physical similarity simulation and key strata theory. The research findings reveal that the fractures in the overlying strata had an elliptic-parabolic shape. The stope center was the highest point in the fracture zone. Horizontal shear deformation was most likely to occur in the thick strata (horizontal shear deformation could be larger if they were key strata) with large strength and stiffness near the intersection between the fracture surface of the overlying strata and the surface well. Due to the shear force and bending moment of the key strata, the surface well deformed into an S-shape. In addition, the surface well was vulnerable to shear deformation in the key strata. The surface well deformation did not weaken from bottom to top due to rock movement. Instead, it was subject to the influence of the rupture strength of the key strata. The surface well above the key strata was prone to tensile strain-compressive strain transition. In contrast, an abrupt change in the compressive strain occurred in the surface well below the key strata where tensile failure may occur. Moreover, a mechanical model of the surface well during the movement of the key strata was established according to the characteristics of the surface well deformation. The test results provide important information on the design optimization of surface wells and high-risk area protection in mining areas.

Deriving time-series three-dimensional displacements of mining areas from a single-geometry InSAR dataset

2017 ◽  
Vol 92 (5) ◽  
pp. 529-544 ◽  
Author(s):  
Zefa Yang ◽  
Zhiwei Li ◽  
Jianjun Zhu ◽  
Guangcai Feng ◽  
Qijie Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Three Dimensional ◽  
Mining Areas

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 MONITORING OF TIME-SERIES SOIL MOISTURE BASED ON ADVANCED DINSAR

2021 ◽  
Vol V-3-2021 ◽  
pp. 51-55
Author(s):  
C. H. Yang ◽  
A. Müterthies
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Water Content ◽  
Large Scale ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Organic Soil ◽  
Underground Water ◽  
Multi Temporal ◽  
Mean Square Errors

Abstract. Understanding soil moisture is essential for earth and environmental sciences especially in geology, hydrology, and meteorology. Remote sensing techniques are widely applied to large-scale monitoring tasks. Among them, DInSAR using multi-temporal spaceborne SAR images is able to derive surface movement up to mm level over an area. One of the factors inducing the movement is variation of soil moisture. Based on this, a semi-empirical approach can be tailored to retrieve the underground water content. However, the derived movement is often contaminated with other irrelevant noise. Besides, a time-series analysis could not be simply implemented without additional fusion and calibration. In this paper, we propose a novel modelling based on advanced DInSAR to solve these problems. The irrelevant noise will be removed as parts of the modelled elements in the DInSAR processing. A forward model on a scene is built by regressing the measured soil moisture on the DInSAR-derived movement series. We tested our approach using Sentinel-1 images in the grasslands of organic soil within State of Brandenburg, Germany. The Pearson correlation coefficients between the measured soil moistures and the DInSAR-derived movements are up to 0.91. The mean square errors of the predicted soil moistures compared with the measurements reach 3.03 % (volumetric water content) at best. Our study shows a promising new concept to develop a global monitoring of soil moisture in the future.

Sign in / Sign up

Export Citation Format

Share Document