Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas
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 w...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/8/1497 |
| _version_ | 1797537776938254336 |
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| author | Mengyao Shi Honglei Yang Baocun Wang Junhuan Peng Zhouzheng Gao Bin Zhang |
| author_facet | Mengyao Shi Honglei Yang Baocun Wang Junhuan Peng Zhouzheng Gao Bin Zhang |
| author_sort | Mengyao Shi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T12:21:03Z |
| format | Article |
| id | doaj.art-41b1f317fad94d03b473b234abe5dfb4 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T12:21:03Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-41b1f317fad94d03b473b234abe5dfb42023-11-21T15:28:11ZengMDPI AGRemote Sensing2072-42922021-04-01138149710.3390/rs13081497Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining AreasMengyao Shi0Honglei Yang1Baocun Wang2Junhuan Peng3Zhouzheng Gao4Bin Zhang5School of Land Science and Technology, China University of Geosciences, Beijing 100083, ChinaSchool of Land Science and Technology, China University of Geosciences, Beijing 100083, ChinaInstitute of Surveying Mapping and Geo-Information of Henan Provincial Bureau of Geo-Exploration and Mineral Development, Zhengzhou 450006, ChinaSchool of Land Science and Technology, China University of Geosciences, Beijing 100083, ChinaSchool of Land Science and Technology, China University of Geosciences, Beijing 100083, ChinaSchool of Engineering and Technology, China University of Geosciences, Beijing 100083, ChinaCoal-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.https://www.mdpi.com/2072-4292/13/8/1497SBAS-InSARprobability integral methodmining boundary constraint |
| spellingShingle | Mengyao Shi Honglei Yang Baocun Wang Junhuan Peng Zhouzheng Gao Bin Zhang Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas Remote Sensing SBAS-InSAR probability integral method mining boundary constraint |
| title | Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas |
| title_full | Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas |
| title_fullStr | Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas |
| title_full_unstemmed | Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas |
| title_short | Improving Boundary Constraint of Probability Integral Method in SBAS-InSAR for Deformation Monitoring in Mining Areas |
| title_sort | improving boundary constraint of probability integral method in sbas insar for deformation monitoring in mining areas |
| topic | SBAS-InSAR probability integral method mining boundary constraint |
| url | https://www.mdpi.com/2072-4292/13/8/1497 |
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