Application of LuTan-1 SAR Data in Railway Subsidence Monitoring
Abstract. InSAR technology is currently a crucial tool for large-scale surface deformation monitoring, particularly excelling in regional subsidence monitoring. In this study, focusing on the Jinan section of the Shandong railway, newly launched LUTAN-1 satellite SAR data was employed. DInSAR and Stacking techniques were applied to analyze the subsidence in response to the long-term operation load of high-speed trains and surrounding human activities. Through the analysis of data from June 2023 to December 2023, regional subsidence was identified in this section, with a subsidence rate reaching 8 cm/year. Comparative analysis between DInSAR technology monitoring results and precise leveling monitoring results showed consistency in the subsidence deformation trend in the region, achieving centimeter-level deformation monitoring in the study area.The LuTan-1 satellite provided robust SAR data support for railway subsidence monitoring, offering substantial reliability and accuracy to deepen the understanding of railway subsidence issues. These research findings hold significant practical implications for adopting timely maintenance and repair measures, ensuring the safety and reliable operation of the railway system.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Application of LuTan-1 SAR Data in Railway Subsidence Monitoring ; volume:XLVIII-1-2024 ; year:2024 ; pages:351-357 ; extent:7
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVIII-1-2024 (2024), 351-357 (gesamt 7)
- Creator
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Li, Wenhao
Li, Tao
Zhou, Xiaoqing
Liu, Xian
- DOI
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10.5194/isprs-archives-XLVIII-1-2024-351-2024
- URN
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urn:nbn:de:101:1-2405160447262.757103275521
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:47 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Li, Wenhao
- Li, Tao
- Zhou, Xiaoqing
- Liu, Xian
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