International conference on construction engineering and project management (국제학술발표논문집)

  • 2024.07a
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  • Pages.102-111
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  • 2024
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  • 2508-9048(eISSN)
Korea Institute of Construction Engineering and Management (한국건설관리학회)
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Monitoring Roadbed Stability to Prevent Cascading Hazards in Daejeon City, South Korea, Using Sentinel-1 SAR Data

  • Manik DAS ADHIKARI (Department of Civil Engineering, Gangneung-Wonju National University) ;
  • Seung-Bin LEE (Department of Civil Engineering, Gangneung-Wonju National University) ;
  • Seong-Wuk KIM (Department of Civil Engineering, Gangneung-Wonju National University) ;
  • Hyeon-Jun KIM (Department of Civil Engineering, Gangneung-Wonju National University) ;
  • Jeremie TUGANISHURI (Department of Civil Engineering, Gangneung-Wonju National University) ;
  • Sang-Guk YUM (Department of Civil Engineering, Gangneung-Wonju National University) ;
  • Ji-Myong KIM (Department of Architectural Engineering, Mokpo National University)
  • Published : 2024.07.29
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Abstract

Roadbed stability is paramount in urban areas as it directly affects public safety and city operations. South Korea's major metropolis has experienced 1127 cases of ground subsidence since 2014, affecting subways, roads, railways, and construction sites. Notably, about 40% of these incidents coincide with heavy summer rainfall, while 60% resulted from utility damage, improper backfill, and groundwater fluctuations. Subsequently, roadbed instability leads to a range of cascading hazards, including sinkholes and road failures, endangering public safety and the economy. Therefore, continuous monitoring of roadbed stability and implementing proactive measures are essential for a resilient transportation infrastructure. However, terrestrial in-situ observations like GPS provide accurate surface's displacement with high temporal accuracy but limited spatial resolution. To address this issue, we used the InSAR permanent scatterer (PSInSAR) technique to process 35 Sentinel-1 SLC datasets acquired between 2017 and 2022 to monitor and prevent cascading hazards in Daejeon City, South Korea. The results revealed an average subsidence rate of -0.88mm/year with a maximum of -7.73 mm/year. Notably, the southern part of the city exhibited significant roadbed instability, with an average and maximum cumulative subsidence of -5.13 mm and -44.95 mm, respectively. The deformation data was then integrated with road geometry to develop a vulnerability map of the city, highlighting the pronounced roadbed deformation in the southern region. Time-series subsidence variations correlated with groundwater fluctuations data from 2017 to 2022, showing a decline in groundwater levels from 4.63m to 9.9m in the southern region. Furthermore, a comparison between subsidence rates and effective shear wave velocity (Vs30) revealed that most subsidence events were associated with Vs30 values below 420 m/sec, indicating a clear lithological influence on the spatial distribution of roadbed instability. Thus, the integrated geotechnical and hydrogeological data with PSInSAR monitoring can better understand the processes responsible for roadbed instability in areas with small-scale variations.

Keywords

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education ((NRF-2021R1C1C2003316). The SARPROZ team is acknowledged (https://www.sarproz.com/) for providing the MT-InSAR processing program upon request. The authors would also acknowledge the European Space Agency (ESA) for providing satellite images free of charge.

References

  1. K. Lee, J. Nam, J. Park, G. Hong, "Numerical Analysis of Factors Influencing the Ground Surface Settlement above a Cavity", Materials, vol.15, no. 23, pp. 8301, 2022. 
  2. S. Lee, J. Kang, J. Kim, "Prediction Modeling of Ground Subsidence Risk Based on Machine Learning Using the Attribute Information of Underground Utilities in Urban Areas in Korea" Applied Sciences, vol. 13, no. 9, pp. 5566, 2023. 
  3. H. R. Vignisdottir, B. Ebrahimi, G. K. Booto, R. O'Born, H. Brattebo, H. Wallbaum, R. A. Bohne, "A review of environmental impacts of winter road maintenance", Cold Regions Science and Technology, vol. 158, pp. 143-153, 2019. 
  4. D. Kim, J. Jeon, D. Kim, "Predictive Modeling of Pavement Damage Using Machine Learning and Big Data Processing", Journal of the Korean Society of Hazard Mitigation, vol. 19, no. 1, pp. 95-107, 2019. 
  5. Q. Zhang, Y. Li, J. Zhang, Y. Luo, "InSAR technique applied to the monitoring of the Qinghai-Tibet Railway", Natural Hazards and Earth System Sciences, vol. 19, no. 10, pp. 2229-2240, 2019. 
  6. D. Perissin, Z. Wang, H. Lin, "Shanghai subway tunnels and highways monitoring through Cosmo-SkyMed Persistent Scatterers" ISPRS Journal of Photogrammetry and Remote Sensing, vol. 73, pp. 58-67, 2012. 
  7. F. Orellana, J. M. Delgado Blasco, M. Foumelis, P. J. D'Aranno, M. A. Marsella, P. Di Mascio, "Dinsar for road infrastructure monitoring: Case study highway network of Rome metropolitan (Italy)", Remote Sensing, vol. 12, no. 22, pp. 3697, 2020. 
  8. L. Bianchini Ciampoli, V. Gagliardi, A. Benedetto, A. Alani, F. Tosti, "InSAR analysis of C-band data for transport infrastructure monitoring", 11th International Conference on the Bearing Capacity of Roads, Railways and Airfields, vol. 2, pp. 301-310, 2022. 
  9. R. A. Ramirez, G. J. Lee, S. K. Choi, T. H. Kwon, Y. C. Kim, H. H. Ryu, S. Kim, C. Hyun, "Monitoring of construction-induced urban ground deformations using Sentinel-1 PS-InSAR: The case study of tunneling in Dangjin, Korea", International Journal of Applied Earth Observation and Geoinformation, vol.108, pp.102721, 2022. 
  10. S. K. Chough, S. T. Kwon, J. H. Ree, D. K. Choi, "Tectonic and sedimentary evolution of the Korean peninsula: a review and new view", Earth-Science Reviews, vol. 52, no.1-3, pp. 175-235, 2000. 
  11. H. S. Kim, C. G. Sun, M. Kim, H. I. Cho, M. G. Lee, "GIS-based optimum geospatial characterization for seismic site effect assessment in an inland urban area, South Korea", Applied Sciences, vol.10, no. 21, pp.7443, 2020. 
  12. H. Y. Lee, C. H. Oh, E. S. Kim, Y. W. Son, K. S. Park, "The Vegetation and Soil Characteristics of Urban Forest as Geological Location in Daejeon, Korea", Korean Journal of Environment and Ecology, vol. 24, no. 5, pp. 566-574, 2010. 
  13. B. Kim, T. K. Hong , "A national Vs30 model for South Korea to combine nationwide dense borehole measurements with ambient seismic noise analysis", Earth and Space Science, vol. 9, no. 1, pp. e2021EA002066, 2022. 
  14. M. A. Hussain, Z. Chen, Y. Zheng, M. Shoaib, J. Ma, I. Ahmad, A. Asghar, J. Khan, "PS-InSAR Based Monitoring of Land Subsidence by Groundwater Extraction for Lahore Metropolitan City, Pakistan" Remote Sensing, vol. 14, no. 16, pp. 3950, 2022. 
  15. D. Perissin, Z. Wang, T. Wang, "The SARPROZ InSAR tool for urban subsidence/man-made structure stability monitoring in China", Proceedings of the ISRSE, Sidney, Australia, isrse-34, 1015, 2011. 
  16. A. Ferretti, C. Prati, F. Rocca, "Permanent scatterers in SAR interferometry", IEEE Transactions on geoscience and remote sensing, vol. 39, no. 1, pp. 8-20, 2001. 
  17. M. Khoshlahjeh Azar, A. Hamedpour, Y. Maghsoudi, D. Perissin, "Analysis of the deformation behavior and sinkhole risk in Kerdabad, Iran using the PS-InSAR method", Remote Sensing, vol. 13, no. 14, pp. 2696, 2021. 
  18. A. Hooper, "A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches", Geophysical Research Letters, vol. 35, no.16, pp. 2008. 
  19. W. F. Chen, H. L. Gong, B. B. Chen, K. S. Liu, M. Gao, C. F. Zhou, "Spatiotemporal evolution of land subsidence around a subway using InSAR time-series and the entropy method", GIScience & Remote Sensing, vol. 54, no. 1, pp. 78-94, 2017. 
  20. BSSC, "NEHRP recommended provisions for seismic regulations for new buildings and other structures", FEMA 450 and Building Seismic Safety Council, 2003. 
  21. H. B. Kim, H. S. Yoon, M. K. Youm, W. E. Lee, "Land Subsidence Analysis for the High-speed Railway Line of Honam using D-InSAR Technique", Journal of the Korean Society for Geospatial Information Science, vol. 25, no.3, pp. 35-41, 2017. 
  22. R. Wang, T. Yang, M. Yang, M. Liao, J. Lin, "A safety analysis of elevated highways in Shanghai linked to dynamic load using long-term time-series of InSAR stacks" Remote Sensing Letters, vol. 10, no.12, pp. 1133-1142, 2019.