LIU Shanwei, LIANG Chengjia, WAN Wei, ZHANG Jie, MA Wang. A New GNSS-IR Method to Monitor Permafrost Freeze-Thaw Deformation Considering the Terrain Effect[J]. Geomatics and Information Science of Wuhan University, 2024, 49(1): 77-89. DOI: 10.13203/j.whugis20230460
Citation: LIU Shanwei, LIANG Chengjia, WAN Wei, ZHANG Jie, MA Wang. A New GNSS-IR Method to Monitor Permafrost Freeze-Thaw Deformation Considering the Terrain Effect[J]. Geomatics and Information Science of Wuhan University, 2024, 49(1): 77-89. DOI: 10.13203/j.whugis20230460

A New GNSS-IR Method to Monitor Permafrost Freeze-Thaw Deformation Considering the Terrain Effect

  • Objectives The seasonal subsidence and uplift of the surface elevation in permafrost area occur due to the annual melting and freezing of active layer, which has an important impact on the safety of engineering construction, the balance of ecological environment, and global climate change. Using global navigation satellite system-interferometric reflectometry (GNSS-IR) to monitor frozen soil deformation is a new technique. Aiming at the terrain influence caused by the non-daily-repeatable orbits of GLONASS and Galileo satellites, this paper proposes a new method to calculate the freeze-thaw deformation of permafrost using these GNSS data.
    Methods By introducing the inclination angle of reflector surface, the effects of terrain changes are eliminated, and the seasonal freeze-thaw deformation closer to the actual situation is obtained. The GNSS signal-to-noise ratio data of 2018 and 2019 snow-free days at SG27 site in northern Alaska are used for experiments and compared with the results obtained by existing retrieval methods to verify the effectiveness of this method in monitoring permafrost deformation.
    Results The results show that compared with the methods without considering the terrain effect, the surface elevation changes obtained by GLONASS and Galileo have smaller discreteness and smaller uncertainty, and the fitting consistency and determination coefficient R2 of the composite model have been improved. The total average standard deviations are reduced by about 28.9 % and 36.9 %, and the total average R2 are increased by about 0.23 and 0.24, respectively. The total average increases of daily data utilization rate of non-repetitive orbits are about 19.6 % and 22.8 %.
    Conclusions This study provides a valuable reference for monitoring permafrost freeze-thaw deformation, and expands the application of GNSS-IR in GNSS system for permafrost freeze-thaw monitoring.
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