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Objectives: The Sichuan Tibet Railway crosses the Jinsha River specifically the section from Xiongsong Town to Shadong Town, Gongjue County, Tibet Autonomous Region, in which exist strong topography variations and many potential geohazards, and hence it urgent to detect the potential geohazards in this region to ensure the railway safety. Methods: In this paper, 61 Sentinel -1 ascending, 53 Sentinel -1 descending and 7 advanced land observing satellite 2 (ALOS 2) ascending images are used to derive the annual mean deformation rates in the satellite radar line of sight (LOS) with two advanced InSAR (interferometric synthetic aperture radar) approaches, namely generic atmospheric correction online service for InSAR (GACOS) assisted InSAR Stacking and LiCSBAS. The three LOS annual mean deformation rate maps are then used to determine 2D surface movements (one along the slope and the other perpendicular to the slope) in the study region. Results: The comparison between GACOS assisted InSAR Stacking and LiCSBAS results show that they agree with each other with correlation coefficients over 0.92 for the LOS deformation rates and over 0.85 for the 2D deformation rates, suggesting the reliability of GACOS assisted InSAR Stacking. The maximum annual deformation rate of 163 mm/a can be observed in the slope direction and seven landslides (A, B, C, D, E, F, G) can be clearly identified, which in turn lays the foundation for future real-time monitoring. Based on the detailed analysis of the seven regions by using InSAR and optical interpretation results, it is found that the seven landslides had relatively obvious deformation. Landslides A, B, C and D are active landslides, which might cause the result of river blocking due to overall instability. At present, landslides E, F and G are still in the stage of slow deformation. Conclusions: This study also find that GACOS assisted InSAR Stacking can effectively remove long band and topographic related atmospheric delay error with the help of GACOS, which has the advantages of being simple, effective, fast, and easy to popularize and apply. GACOS assisted InSAR Stacking technology can be used to quickly identify potential landslide hazards. [ABSTRACT FROM AUTHOR]

The pre-failure evolution of landslides is of great value for the analysis of landslide triggering factors and post-disaster stability assessment. At present, optical images are commonly employed to ana⁃ lyze the pre-failure evolution, but it is well-known that their data availability could be highly limited due to the presence of clouds. With the advance in radar remote sensing and interferometric synthetic aperture radar(InSAR), it could provide a new technical approach for landslide pre-failure detection. In this paper, the 2018 Nanyu landslide in Gansu Province is utilized to demonstrate the capability of InSAR to trace its pre-failure surface displacements using European Space Agency’s Sentinel-1 radar data with a temporal interval of 12 days in different tracks. The results show that the landslide began to deform in June of 2017, and the maximum cumulative deformation reached up to 77 mm in the 13 months before the occurrence of the landslide. The time series InSAR derive displacements and the rainfall data is consistent, suggesting that the rainfall should be one of the triggering factors for the landslide. The study demonstrates the potential of radar interferometry for landslide detection, which can provide insights on landslide triggering factors, landslide disaster prevention and mitigation, and even landslide monitoring and early warning work in the future. [ABSTRACT FROM AUTHOR]