Deformation Monitoring Along Beijing Metro Line 22 Using PS-InSAR Technology

The construction of subways exacerbates the non-uniformity of surface deformation, which in turn poses a potential threat to the safe construction and stable operation of urban rail transit systems. Beijing, the city with the most extensive subway network in China, has long been affected by land subsidence. Utilizing data from Envisat ASAR, Radarsat-2, and Sentinel-1 satellites, this study employs PS-InSAR technology to monitor and analyze land subsidence within a 2 km buffer zone along Beijing Metro Line 22 over a span of 20 years (from January 2004 to November 2024). The results indicate that land subsidence at Guanzhuang Station and Yanjiao Station along Metro Line 22 is particularly pronounced, forming two distinct subsidence zones. After 2016, the overall rate of subsidence along the subway line began to stabilize, with noticeable ground rebound emerging around 2020. This study further reveals a strong correlation between land subsidence and confined groundwater levels, while geological structures and building construction also exert a significant influence on subsidence development. These findings provide a crucial scientific foundation for the formulation of effective prevention and mitigation strategies for land subsidence along urban rail transit lines.

Authors

Institutions

Publication Details

Journal
Land
Published
2025-05-18
DOI
https://doi.org/10.3390/land14051098
Citations
2
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
9.99

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deformation Monitoring Along Beijing Metro Line 22 Using PS-InSAR Technology

Mingyuan Lyu, Huan Luo, Fengzhou Wang, Lin Guo et al.
2 citations
Land
Synthetic Aperture Radar (SAR) Applications and Techniques
9.99
article

Deformation Monitoring Along Beijing Metro Line 22 Using PS-InSAR Technology

Mingyuan Lyu, Huan Luo, Fengzhou Wang, Lin Guo, Jiyi Jiang, Xiaojuan Li, Ke Zhang, Fengqian Guo, Lan Wang
article en
2 citations

Abstract

The construction of subways exacerbates the non-uniformity of surface deformation, which in turn poses a potential threat to the safe construction and stable operation of urban rail transit systems. Beijing, the city with the most extensive subway network in China, has long been affected by land subsidence. Utilizing data from Envisat ASAR, Radarsat-2, and Sentinel-1 satellites, this study employs PS-InSAR technology to monitor and analyze land subsidence within a 2 km buffer zone along Beijing Metro Line 22 over a span of 20 years (from January 2004 to November 2024). The results indicate that land subsidence at Guanzhuang Station and Yanjiao Station along Metro Line 22 is particularly pronounced, forming two distinct subsidence zones. After 2016, the overall rate of subsidence along the subway line began to stabilize, with noticeable ground rebound emerging around 2020. This study further reveals a strong correlation between land subsidence and confined groundwater levels, while geological structures and building construction also exert a significant influence on subsidence development. These findings provide a crucial scientific foundation for the formulation of effective prevention and mitigation strategies for land subsidence along urban rail transit lines.

LandVol. 14(5)
Institute of Disaster Prevention (CN), Hebei Seismological Bureau (CN), Beijing Water Science and Technology Institute (CN), Zhejiang University (CN), Capital Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 3%
Synthetic Aperture Radar (SAR) Applications and Techniques
9.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.