A Metro-InSAR Risk Index for corridor-scale displacement risk diagnosis of urban rail infrastructure

Time-series Interferometric Synthetic Aperture Radar (InSAR) provides dense displacement observations along urban rail corridors, yet converting point-based measurements into corridor-scale diagnostic information remains challenging. This study proposes the Metro-InSAR Risk Index (MIRI), a diagnostic index designed to convert multi-dimensional InSAR-derived displacement characteristics into displacement-related diagnostic levels for urban metro corridors. MIRI integrates displacement rate, cumulative displacement, local displacement heterogeneity, height-related variability, and temporal residual variability, thereby extending conventional velocity-based interpretation toward corridor-scale displacement-risk diagnosis. The framework was applied to the Kunming Metro Network using 198 descending Sentinel-1 images acquired from March 2018 to December 2024. The time-series InSAR results show that the network was generally stable, with line-of-sight (LOS) displacement rates mainly ranging from −6 to 3 mm/yr and 97.21% of coherent scatterers falling within the stable interval of −3 to 3 mm/yr. Localized displacement anomalies were mainly observed near line intersections, curved sections, construction-affected areas, and the Dianchi Lake shoreline. Based on MIRI, 78%, 17%, 4%, and 1% of valid points were classified as Levels D, C, B, and A, respectively, indicating a distribution dominated by lower diagnostic levels, with spatially confined Level-B and Level-A anomalies particularly along Lines 4 and 5 and in lakeside soft-ground areas. Multi-source contextual variables and XGBoost-SHAP analysis were further used to interpret the environmental, anthropogenic, operational, and displacement-gradient information associated with the MIRI-based diagnostic patterns. The results indicate that the spatial variation in MIRI is mainly associated with terrain-related conditions, corridor-scale displacement variation, metro operation, and urban development intensity. By deriving diagnostic levels directly from PSI-based displacement indicators, MIRI provides an InSAR-based screening tool for prioritizing displacement-related anomalies and supporting maintenance of urban rail transit systems.

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Publication Details

Journal
International Journal of Applied Earth Observation and Geoinformation
Published
2026-10-19
DOI
https://doi.org/10.1016/j.jag.2026.105639
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
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article

A Metro-InSAR Risk Index for corridor-scale displacement risk diagnosis of urban rail infrastructure

Mengshi Yang, Jisheng Xia, Hang Yu, Zhifang Zhao et al.
International Journal of Applied Earth Observation and Geoinformation
Synthetic Aperture Radar (SAR) Applications and Techniques
article

A Metro-InSAR Risk Index for corridor-scale displacement risk diagnosis of urban rail infrastructure

Mengshi Yang, Jisheng Xia, Hang Yu, Zhifang Zhao, Ramon F. Hanssen, Hao Wu, Weibin Huang
article en

Abstract

Time-series Interferometric Synthetic Aperture Radar (InSAR) provides dense displacement observations along urban rail corridors, yet converting point-based measurements into corridor-scale diagnostic information remains challenging. This study proposes the Metro-InSAR Risk Index (MIRI), a diagnostic index designed to convert multi-dimensional InSAR-derived displacement characteristics into displacement-related diagnostic levels for urban metro corridors. MIRI integrates displacement rate, cumulative displacement, local displacement heterogeneity, height-related variability, and temporal residual variability, thereby extending conventional velocity-based interpretation toward corridor-scale displacement-risk diagnosis. The framework was applied to the Kunming Metro Network using 198 descending Sentinel-1 images acquired from March 2018 to December 2024. The time-series InSAR results show that the network was generally stable, with line-of-sight (LOS) displacement rates mainly ranging from −6 to 3 mm/yr and 97.21% of coherent scatterers falling within the stable interval of −3 to 3 mm/yr. Localized displacement anomalies were mainly observed near line intersections, curved sections, construction-affected areas, and the Dianchi Lake shoreline. Based on MIRI, 78%, 17%, 4%, and 1% of valid points were classified as Levels D, C, B, and A, respectively, indicating a distribution dominated by lower diagnostic levels, with spatially confined Level-B and Level-A anomalies particularly along Lines 4 and 5 and in lakeside soft-ground areas. Multi-source contextual variables and XGBoost-SHAP analysis were further used to interpret the environmental, anthropogenic, operational, and displacement-gradient information associated with the MIRI-based diagnostic patterns. The results indicate that the spatial variation in MIRI is mainly associated with terrain-related conditions, corridor-scale displacement variation, metro operation, and urban development intensity. By deriving diagnostic levels directly from PSI-based displacement indicators, MIRI provides an InSAR-based screening tool for prioritizing displacement-related anomalies and supporting maintenance of urban rail transit systems.

International Journal of Applied Earth Observation and GeoinformationVol. 154
Yunnan University (CN), Delft University of Technology (NL)
Openalex Percentile: Top 17%
Synthetic Aperture Radar (SAR) Applications and Techniques
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