Positioning and Mitigating Mining-Induced Phase Gradients for InSAR Phase Unwrapping
Interferometric synthetic aperture radar (SAR) has been widely used for deformation monitoring in mining areas. However, the nonlinear high-phase gradients caused by subsidence funnels are a major source of error in accurate measurements, as they present challenges for phase unwrapping. In this arti...
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10963682/ |
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| author | Xin Tian Xia Wu Hanwen Yu Mi Jiang |
| author_facet | Xin Tian Xia Wu Hanwen Yu Mi Jiang |
| author_sort | Xin Tian |
| collection | DOAJ |
| description | Interferometric synthetic aperture radar (SAR) has been widely used for deformation monitoring in mining areas. However, the nonlinear high-phase gradients caused by subsidence funnels are a major source of error in accurate measurements, as they present challenges for phase unwrapping. In this article, we present a methodology to position and mitigate the mining-induced phase gradients. First, we utilize YOLOv10 to detect subsidence funnels that appear as small targets in SAR interferograms. Second, we model the nonlinear phase gradients by means of generalized Gaussian distribution, followed by minimizing the angular deviation between observed and modelled phase patterns in each detected interferometric patch. After defringing mining-induced phase gradients, we evaluate the impact of nonlinear high phase gradients on phase unwrapping, using synthetic data and Sentinel-1 dataset over Datong mining area, Shanxi Province. Compared to phase unwrapping without defringing, the proposed approach reduced the RMSE by 35.5% in the simulation. For the real data, the average number of unclosed pixels was reduced by 30.7%. |
| format | Article |
| id | doaj-art-207878b8c6e8401d8b1fc83e8a79aee7 |
| institution | OA Journals |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-207878b8c6e8401d8b1fc83e8a79aee72025-08-20T01:52:03ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-0118116611166910.1109/JSTARS.2025.356013910963682Positioning and Mitigating Mining-Induced Phase Gradients for InSAR Phase UnwrappingXin Tian0https://orcid.org/0000-0002-6142-2982Xia Wu1https://orcid.org/0009-0001-9994-4436Hanwen Yu2https://orcid.org/0000-0001-5057-2072Mi Jiang3https://orcid.org/0000-0003-2459-4619School of Transportation, Southeast University, Nanjing, ChinaSchool of Transportation, Southeast University, Nanjing, ChinaSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai, ChinaInterferometric synthetic aperture radar (SAR) has been widely used for deformation monitoring in mining areas. However, the nonlinear high-phase gradients caused by subsidence funnels are a major source of error in accurate measurements, as they present challenges for phase unwrapping. In this article, we present a methodology to position and mitigate the mining-induced phase gradients. First, we utilize YOLOv10 to detect subsidence funnels that appear as small targets in SAR interferograms. Second, we model the nonlinear phase gradients by means of generalized Gaussian distribution, followed by minimizing the angular deviation between observed and modelled phase patterns in each detected interferometric patch. After defringing mining-induced phase gradients, we evaluate the impact of nonlinear high phase gradients on phase unwrapping, using synthetic data and Sentinel-1 dataset over Datong mining area, Shanxi Province. Compared to phase unwrapping without defringing, the proposed approach reduced the RMSE by 35.5% in the simulation. For the real data, the average number of unclosed pixels was reduced by 30.7%.https://ieeexplore.ieee.org/document/10963682/Generalized Gaussian distributionInSARmining subsidencephase gradientunwrappingYOLOv10 |
| spellingShingle | Xin Tian Xia Wu Hanwen Yu Mi Jiang Positioning and Mitigating Mining-Induced Phase Gradients for InSAR Phase Unwrapping IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Generalized Gaussian distribution InSAR mining subsidence phase gradient unwrapping YOLOv10 |
| title | Positioning and Mitigating Mining-Induced Phase Gradients for InSAR Phase Unwrapping |
| title_full | Positioning and Mitigating Mining-Induced Phase Gradients for InSAR Phase Unwrapping |
| title_fullStr | Positioning and Mitigating Mining-Induced Phase Gradients for InSAR Phase Unwrapping |
| title_full_unstemmed | Positioning and Mitigating Mining-Induced Phase Gradients for InSAR Phase Unwrapping |
| title_short | Positioning and Mitigating Mining-Induced Phase Gradients for InSAR Phase Unwrapping |
| title_sort | positioning and mitigating mining induced phase gradients for insar phase unwrapping |
| topic | Generalized Gaussian distribution InSAR mining subsidence phase gradient unwrapping YOLOv10 |
| url | https://ieeexplore.ieee.org/document/10963682/ |
| work_keys_str_mv | AT xintian positioningandmitigatingmininginducedphasegradientsforinsarphaseunwrapping AT xiawu positioningandmitigatingmininginducedphasegradientsforinsarphaseunwrapping AT hanwenyu positioningandmitigatingmininginducedphasegradientsforinsarphaseunwrapping AT mijiang positioningandmitigatingmininginducedphasegradientsforinsarphaseunwrapping |