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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 cliff coastline of the central region of Asturias (N Spain) is severely affected by terrain instabilities, causing considerable damage to properties and infrastructures every year. In this study, we applied the A-DInSAR technique based on Sentinel-1 imagery to map and monitor active slopes in an emblematic rocky area of the Asturian coast: the Peñas Cape. The A-DInSAR dataset analysis has been focused at regional and local scales. For the local scale assessment, six areas were selected based on previous work and the landslide database of the Principality of Asturias region (BAPA-Base de datos de Argayos del Principado de Asturias), created by the University of Oviedo. The processing of the data has been performed using two independent sets of processing tools: the PSIG software tools, a professional tool and, the GEP service, an unsupervised platform. The dataset consisted of 113 SAR IW-SLC images acquired by the Sentinel-1 A/B satellites between January 2018 and February 2020. LOS mean deformation velocity maps (mm year−1) and deformation time series (mm) were obtained by PSIG and GEP software, allowing coastal areas with landslide incidence and other terrain movements to be distinguished. Deformation motion has been estimated from PSIG VLOS rates to be from −17.1 to 37.4 mm year−1 and GEP VLOS rates from −23.0–38.3 mm year−1. According to deformation time series (mm), the minimum and maximum accumulated displacements are −68.5–78.8 and −48.8–77.0 mm by means of PSIG and GEP, respectively. These ground motions could be associated with coastal instabilities related to marine activity and coastal retreat, both at regional and local study scales. The main contributions of this work are: (1) the demonstration of the potential of A-DInSAR techniques to evaluate coastal instabilities in a coastal retreat context and (2) the comparison of the results provided by the two sets of tools, which allowed the ground motion to be assessed by using an unsupervised approach vs. a contrasted one (robust software). This study increases the knowledge about coastal instabilities and other ground movements along the rocky coast and cliffs of Central Asturias. As a conclusion for the future, we believe that this work highlights the evaluated methods as significant tools to support the management of coastal territories with jagged and rocky coastlines. [ABSTRACT FROM AUTHOR]