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Open AccessArticle
Land-Cover Controls on the Accuracy of PS-InSAR-Derived Concrete Track Settlement Measurements
by
Byung-kyu Kim
Byung-kyu Kim 1,†,
Joonyoung Kim
Joonyoung Kim 2,†
,
Jeongjun Park
Jeongjun Park 3,
Ilwha Lee
Ilwha Lee 1 and
Mintaek Yoo
Mintaek Yoo 4,*
1
Track & Civil Infrastructure Division, Korea Railroad Research Institute, 176, Cheoldobangmulgwan-ro, Uiwang-si 16105, Republic of Korea
2
Department of Artificial Intelligence, Hannam University, 70, Hannam-ro, Daedeok-gu, Daejeon 34430, Republic of Korea
3
Railroad AI Convergence Research Department, Korea Railroad Research Institute, 176 Railroad Museum Road, Uiwang-si 16105, Republic of Korea
4
Department of Civil & Environmental Engineering, Gachon University, 1342, Seongnam-daero, Sujeong-gu, Seongnam-si 13120, Republic of Korea
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Remote Sens. 2025, 17(21), 3537; https://doi.org/10.3390/rs17213537 (registering DOI)
Submission received: 1 September 2025
/
Revised: 22 October 2025
/
Accepted: 23 October 2025
/
Published: 25 October 2025
Abstract
Accurate monitoring of settlement in high-speed railway embankments is critical for operational safety and long-term serviceability. This study investigates the applicability of Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) for quantifying millimeter-scale deformations and emphasizes how surrounding environmental factors influence measurement accuracy. Using 29 TerraSAR-X images acquired between 2016 and 2018, PS-InSAR-derived settlements were compared with precise leveling survey data across twelve representative embankment sections of the Honam High-Speed Railway in South Korea. Temporal and spatial discrepancies between the two datasets were harmonized through preprocessing, allowing robust accuracy assessment using mean absolute error (MAE) and standard deviation (SD). Results demonstrate that PS-InSAR reliably captures settlement trends, with MAE ranging from 1.7 to 4.2 mm across different scenes. However, significant variability in accuracy was observed depending on local land-cover composition. Correlation analysis revealed that vegetation-dominated areas, such as agricultural and forest land, reduce persistent scatterer density and increase measurement variability, whereas high-reflectivity surfaces, including transportation facilities and buildings, enhance measurement stability and precision. These findings confirm that environmental conditions are decisive factors in determining the performance of PS-InSAR. The study highlights the necessity of integrating site-specific land-cover information when designing and interpreting satellite-based monitoring strategies for railway infrastructure management.
Share and Cite
MDPI and ACS Style
Kim, B.-k.; Kim, J.; Park, J.; Lee, I.; Yoo, M.
Land-Cover Controls on the Accuracy of PS-InSAR-Derived Concrete Track Settlement Measurements. Remote Sens. 2025, 17, 3537.
https://doi.org/10.3390/rs17213537
AMA Style
Kim B-k, Kim J, Park J, Lee I, Yoo M.
Land-Cover Controls on the Accuracy of PS-InSAR-Derived Concrete Track Settlement Measurements. Remote Sensing. 2025; 17(21):3537.
https://doi.org/10.3390/rs17213537
Chicago/Turabian Style
Kim, Byung-kyu, Joonyoung Kim, Jeongjun Park, Ilwha Lee, and Mintaek Yoo.
2025. "Land-Cover Controls on the Accuracy of PS-InSAR-Derived Concrete Track Settlement Measurements" Remote Sensing 17, no. 21: 3537.
https://doi.org/10.3390/rs17213537
APA Style
Kim, B.-k., Kim, J., Park, J., Lee, I., & Yoo, M.
(2025). Land-Cover Controls on the Accuracy of PS-InSAR-Derived Concrete Track Settlement Measurements. Remote Sensing, 17(21), 3537.
https://doi.org/10.3390/rs17213537
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