Land subsidence monitoring and analysis in Qingdao, China using time series InSAR combining PS and DS
With the accelerated urbanization process in Qingdao, urban land subsidence has damaged infrastructure and hindered the sustainable development. To prevent disasters caused by urban land subsidence, large-scale, long-term monitoring, mechanism analysis, and risk assessment are essential. This study...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Geomatics, Natural Hazards & Risk |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2024.2447543 |
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| author | Qiuxiang Tao Xuepeng Li Tengfei Gao Yang Chen Ruixiang Liu Yixin Xiao |
| author_facet | Qiuxiang Tao Xuepeng Li Tengfei Gao Yang Chen Ruixiang Liu Yixin Xiao |
| author_sort | Qiuxiang Tao |
| collection | DOAJ |
| description | With the accelerated urbanization process in Qingdao, urban land subsidence has damaged infrastructure and hindered the sustainable development. To prevent disasters caused by urban land subsidence, large-scale, long-term monitoring, mechanism analysis, and risk assessment are essential. This study proposes an improved time series Interferometric Synthetic Aperture Radar (InSAR) method, extracting Permanent Scatterers (PS) and Distributed Scatterers (DS) based on a two-layer network. Using Sentinel-1 dataset, Qingdao's land subsidence from 2019 to 2024 was monitored. The results were validated using multi-source data, and a comprehensive analysis of the spatiotemporal distribution and causes of subsidence was conducted ,alongside a risk matrix based on the Hurst index. Results show that combining PS and DS increases measurement density. From 2019 to 2024, Qingdao's land was generally stable, with subsidence mainly along Jiaozhou Bay , reaching a maximum rate of −84 mm/year due to urbanization and land reclamation. Two mechanisms were identified at Jiaozhou Bay Bridge: linear and seasonal cyclic subsidence. The urban land risk matrix revealed that most sampling points in seven subsidence areas remain in a dangerous state. This study systematically investigated Qingdao's land subsidence, evaluated urban stability, and provided insights and solutions for subsidence prevention and control. |
| format | Article |
| id | doaj-art-31a228dde1674ec8a6f983f59c6522df |
| institution | Kabale University |
| issn | 1947-5705 1947-5713 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geomatics, Natural Hazards & Risk |
| spelling | doaj-art-31a228dde1674ec8a6f983f59c6522df2025-01-06T17:31:35ZengTaylor & Francis GroupGeomatics, Natural Hazards & Risk1947-57051947-57132025-12-0116110.1080/19475705.2024.2447543Land subsidence monitoring and analysis in Qingdao, China using time series InSAR combining PS and DSQiuxiang Tao0Xuepeng Li1Tengfei Gao2Yang Chen3Ruixiang Liu4Yixin Xiao5College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, ChinaShandong GEO-Surveying & Mapping Institute, Jinan, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, ChinaWith the accelerated urbanization process in Qingdao, urban land subsidence has damaged infrastructure and hindered the sustainable development. To prevent disasters caused by urban land subsidence, large-scale, long-term monitoring, mechanism analysis, and risk assessment are essential. This study proposes an improved time series Interferometric Synthetic Aperture Radar (InSAR) method, extracting Permanent Scatterers (PS) and Distributed Scatterers (DS) based on a two-layer network. Using Sentinel-1 dataset, Qingdao's land subsidence from 2019 to 2024 was monitored. The results were validated using multi-source data, and a comprehensive analysis of the spatiotemporal distribution and causes of subsidence was conducted ,alongside a risk matrix based on the Hurst index. Results show that combining PS and DS increases measurement density. From 2019 to 2024, Qingdao's land was generally stable, with subsidence mainly along Jiaozhou Bay , reaching a maximum rate of −84 mm/year due to urbanization and land reclamation. Two mechanisms were identified at Jiaozhou Bay Bridge: linear and seasonal cyclic subsidence. The urban land risk matrix revealed that most sampling points in seven subsidence areas remain in a dangerous state. This study systematically investigated Qingdao's land subsidence, evaluated urban stability, and provided insights and solutions for subsidence prevention and control.https://www.tandfonline.com/doi/10.1080/19475705.2024.2447543Urban land subsidenceInSARurbanizationland reclamationbridge subsidenceHurst index |
| spellingShingle | Qiuxiang Tao Xuepeng Li Tengfei Gao Yang Chen Ruixiang Liu Yixin Xiao Land subsidence monitoring and analysis in Qingdao, China using time series InSAR combining PS and DS Geomatics, Natural Hazards & Risk Urban land subsidence InSAR urbanization land reclamation bridge subsidence Hurst index |
| title | Land subsidence monitoring and analysis in Qingdao, China using time series InSAR combining PS and DS |
| title_full | Land subsidence monitoring and analysis in Qingdao, China using time series InSAR combining PS and DS |
| title_fullStr | Land subsidence monitoring and analysis in Qingdao, China using time series InSAR combining PS and DS |
| title_full_unstemmed | Land subsidence monitoring and analysis in Qingdao, China using time series InSAR combining PS and DS |
| title_short | Land subsidence monitoring and analysis in Qingdao, China using time series InSAR combining PS and DS |
| title_sort | land subsidence monitoring and analysis in qingdao china using time series insar combining ps and ds |
| topic | Urban land subsidence InSAR urbanization land reclamation bridge subsidence Hurst index |
| url | https://www.tandfonline.com/doi/10.1080/19475705.2024.2447543 |
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