Evidence map›Paper›PMID 41125611›Full record

ArticleScientific reports2025

Ground subsidence monitoring and analysis of Lairong railway during its entire construction cycle based on SBAS-InSAR.

Feng Sheng, Long Chai, Xingchang Zhang, Jiangtao Wu, Li Ma, Kaisong Geng, Qiming Han, Xiongyao Xie, Xiaoqing Zeng

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Feng ShengSchool of Civil Engineering, Tsinghua University, Beijing, 100084, China.
Long ChaiDepartment of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai, 200092, China.
Xingchang ZhangPowerchina Roadbridge group co.,LTD, Beijing, 100160, China.
Jiangtao WuPowerchina Roadbridge group co.,LTD, Beijing, 100160, China.
Li MaPowerchina Roadbridge group co.,LTD, Beijing, 100160, China.
Kaisong GengPowerchina Roadbridge group co.,LTD, Beijing, 100160, China.
Qiming HanPowerchina Roadbridge group co.,LTD, Beijing, 100160, China.
Xiongyao XieDepartment of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai, 200092, China.
Xiaoqing ZengThe Key Laboratory of Road and Traffic Engineering Ministry of Education, Tongji University, Shanghai, 201804, China. zengxq@tongji.edu.cn.

Funding

Key Technologies for Green and Intelligent Construction of High-Speed Railways kh0160020230946Science and Technology Council of Shanghai 22dz1208500
6 · The paper itself

Abstract

Ground subsidence poses a significant threat to the structural stability and operational safety of railway systems, highlighting the critical need for effective monitoring throughout the construction lifecycle. Subsidence monitoring data along railway alignments can be leveraged to analyze subsidence characteristics across different sections and to track time-series deformation at specific locations. This study proposes a comprehensive framework for the spatio-temporal analysis of subsidence along railway lines, grounded in the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique. To this end, 39 Sentinel-1 A SAR images were processed to derive subsidence data spanning the pre-construction, construction, and post-construction phases of the Lai-Rong Railway, with results validated against ground leveling measurements. Hotspot analysis was employed to identify subsidence clustering zones, while time-series deformation, average cumulative subsidence, and correlation coefficients were utilized to examine spatio-temporal patterns at targeted locations. The findings demonstrate that SBAS-InSAR achieves millimeter-level accuracy in subsidence monitoring, revealing an uneven spatial distribution along the railway. Notably, the DK30 ~ DK50 section exhibited substantially higher subsidence rates, primarily attributed to large-scale crustal deformation. Construction activities, such as ground excavation, leveling, and load introduction, emerged as primary drivers of subsidence, particularly in surface fill soils. To mitigate long-term subsidence risks, thorough compaction of fill layers is recommended, along with increased monitoring frequency in high-risk sections to enhance safety. This study offers valuable insights into the application of SBAS-InSAR for ground subsidence monitoring across the full construction cycle of large-scale railway projects.

Indexed as

Ground subsidenceHigh-speed railwaySBAS-InSARSpatio-temporal analysis

Identifiers

PMID41125611
PMCPMC12546592

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.