Evaluating expressway stability using interferometric synthetic aperture radar and measuring its impact on the occurrence of geohazards: a case study of Shanxi Province, China

ABSTRACT

This study designs a coherence-based multi-master-image stacking InSAR workflow as an efficient large-scale expressway stability monitoring method, which can improve the overall coherence and number of interferometric pairs via multi-master-image stacking and an average coherence threshold. The average annual ground deformation rate of Shanxi Province, China, was determined using Sentinel-1A data from 2017 to 2021 with a parallel processing strategy to improve efficiency. Compared to global navigation satellite system data, the InSAR results have a root mean square error of 2.90 mm/year. To evaluate the relationship between different factors and the occurrence of geohazards along the expressway network, we conducted a binary logistic regression analysis. The result shows that the deformation rate, annual precipitation, bedrock hardness, distance to stream, and traffic load are significantly related to the occurrence of geohazards along the expressway network in Shanxi Province, among which the deformation rate has the highest significant value, while the traffic load has the lowest, indicating that using InSAR alone to determine geohazards along expressway network is biased and it takes more than InSAR to conduct a comprehensive yet accurate expressway geohazard vulnerability evaluation. This study provides guidance for the road maintenance to ensure the safe operation of expressway systems.

KEYWORDS:

• Expressway stability
• geohazards
• interferometric synthetic aperture radar
• coherence-based multi-master-image stacking

Acknowledgements

The authors would like to thank the European Space Agency for providing Sentinel-1 data and Qianxun SI for GNSS data. The authors would also like to thank the anonymous reviewers whose comments helped significantly improve this article.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability statement

Sentinel-1 SAR data can be downloaded from https://scihub.copernicus.eu/; Orbit state data can be downloaded from https://s1qc.asf.alaska.edu/aux_poeorb/; And ALOS PRISM DEM data can be downloaded from https://asf.alaska.edu/; The precipitation data is obtained from National Tibetan Plateau Data Center (http://www.ngac.org.cn/); The bedrock hardness and fault map are obtained from the 1:200000 geological map from National geological archives of China (http://www.tpdc.ac.cn/).

Additional information

Funding

This research was funded by the Natural Science Foundation of China projects (NSFC) (No: 41801397), the National Key R&D Program of China (2018YFC0825803).