Highway Deformation Monitoring by Multiple InSAR Technology

Author:

Zhao Dan1,Yao Haonan1,Gu Xingyu1

Affiliation:

1. College of Transportation, Southeast University, Nanjing 211100, China

Abstract

Addressing the challenge of large-scale uneven deformation and the complexities of monitoring road conditions, this study focuses on a segment of the G15 Coastal Highway in Jiangsu Province. It employs PS-InSAR, SBAS-InSAR, and DS-InSAR techniques to comprehensively observe deformation. Analysis of 73 image datasets spanning 2018 to 2021 enables separate derivation of deformation data using distinct InSAR methodologies. Results are then interpreted alongside geological and geomorphological features. Findings indicate widespread deformation along the G15 Coastal Highway, notably significant settlement near Guanyun North Hub and uplift near Guhe Bridge. Maximum deformation rates exceeding 10 mm/year are observed in adjacent areas by all three techniques. To assess data consistency across techniques, identical observation points are identified, and correlation and difference analyses are conducted using statistical software. Results reveal a high correlation between the monitoring outcomes of the three techniques, with an average observation difference of less than 2 mm/year. This underscores the feasibility of employing a combination of these InSAR techniques for road deformation monitoring, offering a reliable approach for establishing real-time monitoring systems and serving as a foundation for ongoing road health assessments.

Funder

National Key Research and Development Program of China

Publisher

MDPI AG

Reference24 articles.

1. Highway disaster recognition in central Yunnan area supported by PS-InSAR technology;Li;Sci. Surv. Mapp.,2021

2. Early Detection of Geological Hazards in Longmenshan-Dadu River Area Using Various InSAR Techniques;Wang;Geomat. Inf. Sci. Wuhan Univ.,2020

3. Application of InSAR technology in deformation monitoring of Hefei metro;Yu;Sci. Surv. Mapp.,2022

4. Yan, W. (2019). Subsidence Monitoring along High Speed Railway in Loess Area Based on DS-InSAR Method. [Master’s Thesis, Southwest Jiaotong University].

5. Liu, B., Zhang, Y., Wu, H., Kang, Y., and Jiang, D. (2018). Subsidence Monitoring for Expressway Network in Beijing Based on Time-series InSAR Technique. Bull. Surv. Mapp., 120–125.

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