The increase in temperatures and changing precipitation patterns resulting from climate change are accelerating the occurrence and development of landslides in cold regions, especially in permafrost environments. Although the boundary regions between permafrost and seasonally frozen ground are very sensitive to climate warming, slope failures and their kinematics remain barely characterized or understood in these regions. Here, we apply multisource remote sensing and field investigation to study the activity and kinematics of two adjacent landslides (hereafter referred to as twin landslides) along the Datong River in the Qilian Mountains of the Qinghai-Tibet Plateau. After failure, there is no obvious change in the area corresponding to the twin landslides. Based on InSAR measurements derived from ALOS PALSAR-1 and -2, we observe significant downslope movements of up to 15 mm/day within the twin landslides and up to 5 mm/day in their surrounding slopes. We show that the downslope movements exhibit distinct seasonality; during the late thaw and early freeze season, a mean velocity of about 4 mm/day is observed, while during the late freeze and early thaw season the downslope velocity is nearly inactive. The pronounced seasonality of downslope movements during both pre- and post-failure stages suggest that the occurrence and development of the twin landslide are strongly influenced by freeze-thaw processes. Based on meteorological data, we infer that the occurrence of twin landslides are related to extensive precipitation and warm winters. Based on risk assessment, InSAR measurements, and field investigation, we infer that new slope failure or collapse may occur in the near future, which will probably block the Datong River and cause catastrophic disasters. Our study provides new insight into the failure mechanisms of slopes at the boundaries of permafrost and seasonally frozen ground.

As one of the best indicators of the periglacial environment, ice-wedge polygons (IWPs) are important for arctic landscapes, hydrology, engineering, and ecosystems. Thus, a better understanding of the spatiotemporal dynamics and evolution of IWPs is key to evaluating the hydrothermal state and carbon budgets of the arctic permafrost environment. In this paper, the dynamics of ground surface deformation (GSD) in IWP zones (2018-2019) and their influencing factors over the last 20 years in Saskylakh, northwestern Yakutia, Russia were investigated using the Interferometric Synthetic Aperture Radar (InSAR) and Google Earth Engine (GEE). The results show an annual ground surface deformation rate (AGSDR) in Saskylakh at -49.73 to 45.97 mm/a during the period from 1 June 2018 to 3 May 2019. All the selected GSD regions indicate that the relationship between GSD and land surface temperature (LST) is positive (upheaving) for regions with larger AGSDR, and negative (subsidence) for regions with lower AGSDR. The most drastic deformation was observed at the Aeroport regions with GSDs rates of -37.06 mm/a at tower and 35.45 mm/a at runway. The GSDs are negatively correlated with the LST of most low-centered polygons (LCPs) and high-centered polygons (HCPs). Specifically, the higher the vegetation cover, the higher the LST and the thicker the active layer. An evident permafrost degradation has been observed in Saskylakh as reflected in higher ground temperatures, lusher vegetation, greater active layer thickness, and fluctuant numbers and areal extents of thermokarst lakes and ponds.

Under the influence of climate change, permafrost landforms are sensitive to seasonal heave and contraction, thus exacerbating surface instability and fostering landslides as a consequence. In the pastureland of Zhimei on the Qinghai-Tibet Plateau (QTP), a typical earthflow has drawn significant attention through social media. However, detailed knowledge of the deformation characteristics, internal hydrothermal regime, and structure is still scarce. In this study, we aim to enhance traditional satellite synthetic aperture radar interferometry to divide ground deformation into the seasonal oscillation and slope deformation components and identify the magnitude and spatial distribution of unstable slopes in frozen regions. Then, the use of unmanned aerial vehicles (UAVs) was combined with geophysical monitoring techniques to recognise the deformation dynamics from the pre- to post-failure stages. Sentinel-1 images, covering almost five years, highlighted that obvious creep behaviour dominated at the pre-failure stage, while a seasonal deformation pattern characterised by a piecewise distribution associated with the hydrothermal regime was observed at the post-failure stage. Fast retrogressive erosion on the head scarps at the post-failure stage was clearly identified by multidifferential digital surface models from the UAV observations. To better understand the internal structure, both electrical resistivity tomography and ground-penetrating radar were combined to determine the seasonal frozen thickness, underlying thawing materials, and vertical cracks, which controlled the kinematic evolution from the initial creep to the narrow and long oversaturated flow that represented the terminal portion of the landslide. Finally, by comparing in situ monitoring data with field investigations, the main driving factors controlling the movement mechanism are discussed. Our results highlight the specific kinematic behaviour of an earthflow and can provide a reference for slope destabilisation on the QTP under the influence of climate change.

The Qinghai-Tibet Railway (QTR) is the highest plateau artificial facility, connecting Lhasa and Golmud over Qinghai-Tibet Plateau. Climate change and anthropogenic activities are changing the condition of plateau, with potential influences on the stabilities of QTR. Synthetic aperture radar interferometry (InSAR) technique could retrieve ground millimeter scale deformation utilizing phase information from SAR images. In this study, the structure and deformation features of QTR are retrieved and analyzed using time-series interferometry with Sentinel-1A and TerraSAR-X images. The backscattering and coherence features of QTR are analyzed in medium and very high-resolution SAR images. Then, the deformation results from different SAR datasets are estimated and analyzed. Experimental results show that some of the QTR sections undergo serious deformation, with the maximum deformation rate of -20 mm/year. Moreover, the detailed deformation feature in the Beiluhe has been analyzed as well as the effects of different cooling measurements underline QTR embankment. It is also found that embankment-bridge transition along QTR is prone to undergo deformation. Our study demonstrates the application potential of high-resolution InSAR in deformation monitoring of QTR.

Qinghai-Tibet plateau (QTP) is closely related to global climate change, and it has undergone serious permafrost degradation due to global warming in the last decades. It is crucial to measure the active layer thickness (ALT) for characterizing and monitoring the permafrost degradation of QTP. In this paper, an ALT retrieval model based on ground subsidence derived from synthetic aperture radar interferometry (InSAR), land cover types, and groundwater information is proposed. In particular, the surface subsidence is retrieved using the time-series InSAR technique with TerraSAR-X ST mode images. Moreover, groundwater content models with different land covers are constructed based on multilayered assumptions and in situ data. By taking into account the groundwater content profile and land cover types, the ALT is retrieved from deformation with the full season cycle derived by InSAR technique. The experimental results in Beiluhe indicate that the estimated ALT is consistent with field-measured data. The estimated ALT map shows the difference between the alpine meadow and alpine desert areas, with mean ALT of approximately 1.5 m in alpine meadow area and approximately 3 m in alpine desert area. Our results demonstrate that the InSAR technique with high-resolution SAR images can be of great importance for the study of permafrost environments.