GIScience & Remote Sensing (Dec 2023)

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

  • Shunyao Wang,
  • Guo Zhang,
  • Zhenwei Chen,
  • Zixing Xu,
  • Yutao Liu,
  • Ruishan Zhao

DOI
https://doi.org/10.1080/15481603.2022.2161200
Journal volume & issue
Vol. 60, no. 1

Abstract

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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.

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