Based on ascending and descending orbit SAR data from 2017-2025, this study analyzes the long time-series deformation monitoring and slip pattern of an active-layer detachment thaw slump, a typical active-layer detachment thaw slump in the permafrost zone of the Qinghai-Tibetan Plateau, by using the small baseline subset InSAR (SBAS-InSAR) technique. In addition, a three-dimensional displacement deformation field was constructed with the help of ascending and descending orbit data fusion technology to reveal the transportation characteristics of the thaw slump. The results show that the thaw slump shows an overall trend of south to north movement, and that the cumulative surface deformation is mainly characterized by subsidence, with deformation ranging from -199.5 mm to 55.9 mm. The deformation shows significant spatial heterogeneity, with its magnitudes generally decreasing from the headwall area (southern part) towards the depositional toe (northern part). In addition, the multifactorial driving mechanism of the thaw slump was further explored by combining geological investigation and geotechnical tests. The analysis reveals that the thaw slump's evolution is primarily driven by temperature, with precipitation acting as a conditional co-factor, its influence being modulated by the slump's developmental stage and local soil properties. The active layer thickness constitutes the basic geological condition of instability, and its spatial heterogeneity contributes to differential settlement patterns. Freeze-thaw cycles affect the shear strength of soils in the permafrost zone through multiple pathways, and thus trigger the occurrence of thaw slumps. Unlike single sudden landslides in non-permafrost zones, thaw slump is a continuous development process that occurs until the ice content is obviously reduced or disappears in the lower part. This study systematically elucidates the spatiotemporal deformation patterns and driving mechanisms of an active-layer detachment thaw slump by integrating multi-temporal InSAR remote sensing with geological and geotechnical data, offering valuable insights for understanding and monitoring thaw-induced hazards in permafrost regions.

Ongoing climate warming and increased human activities have led to significant permafrost degradation on the Qinghai-Tibet Plateau (QTP). Mapping the distribution of active layer thickness (ALT) can provide essential information for understanding this degradation. Over the past decade, InSAR (Interferometric synthetic aperture radar) technology has been utilized to estimate ALT based on remotely-sensed surface deformation information. However, these methods are generally limited by their ability to accurate extract seasonal deformation and model subsurface water content of active layer. In this paper, an ALT inversion method considering both seasonal deformation from InSAR and smoothly multilayer soil moisture from ERA5 is proposed. Firstly, we introduce a ground seasonal deformation extraction model combining RobustSTL and InSAR, and the deformation extraction accuracy by considering the deformation characteristics of permafrost are evaluated, proving the effectiveness of RobustSTL in extracting seasonal deformation of permafrost. Then, using ERA5 soil moisture products, a smoothed multilayer soil moisture model for ALT inversion is established. Finally, integrating the seasonal deformation and multilayer soil moisture, the ALT can be estimated. The proposed model is applied to the Yellow River source region (YRSR) with Sentinel-1A images acquired from 2017 to 2021, and the ALT retrieval accuracy is validated with measured data. Experimental results show that the vertical deformation rate of the study area generally ranges from -30 mm/year to 20 mm/year, with seasonal deformation amplitude ranging from 2 mm to 30 mm. The RobustSTL method has the highest accuracy in extracting seasonal deformation of permafrost, with an RMSE (root mean square error) of 0.69 mm, and is capable of capturing the freeze-thaw characteristics of the active layer. The estimated ALT of the YRSR ranges from 49 cm to 450 cm, with an average value of 145 cm. Compared to the measured data, the proposed method has an average error of 37.5 cm, which represents a 21 % improvement in accuracy over existing methods.

Introduction Surface deformation in the Three Gorges Reservoir area poses significant threats to infrastructure and safety due to complex geological and hydrological factors. Despite existing studies, systematic exploration of long-term deformation characteristics and their driving mechanisms remains limited. This study combines SBAS-InSAR technology and machine learning to analyze and predict surface deformation in Fengjie County, Chongqing, China, between 2020 and 2022, focusing on riverside urban ground, riverside road slopes, and ancient landslides in the reservoir area.Methods SBAS-InSAR technology was applied to 36 Sentinel-1A images to monitor surface deformation, complemented by hydrological and meteorological data. Machine learning models-Random Forest (RF), Extremely Randomized Trees (ERT), Gradient Boosting Decision Tree (GBDT), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM)-were evaluated using six metrics, including RMSE, R2, and SMAPE, to assess their predictive performance across diverse geological settings.Results Deformation rates for riverside urban ground, road slopes, and ancient landslides were -3.48 +/- 2.91 mm/yr, -5.19 +/- 3.62 mm/yr, and -6.02 +/- 4.55 mm/yr, respectively, with ancient landslides exhibiting the most pronounced deformation. A negative correlation was observed between reservoir water level decline and subsidence, highlighting the influence of seasonal hydrological adjustments. Urbanization and infrastructure development further exacerbated deformation processes. Among the models, LSTM demonstrated superior predictive accuracy but showed overestimation trends in ancient landslide areas.Discussion Reservoir water level adjustments emerged as a critical driver of subsidence, with rapid water level declines leading to increased pore pressure and soil compression. Seasonal effects were particularly evident, with higher subsidence rates during and after the rainy season. Human activities, including urbanization and road construction, significantly intensified deformation, disrupting natural geological conditions. Progressive slope failure linked to road expansion underscored the long-term impacts of engineering activities. For ancient landslides, accelerated deformation patterns were linked to prolonged drought and reservoir-induced hydrological changes. While LSTM models showed high accuracy, their limitations in complex geological settings highlight the need for hybrid approaches combining machine learning with physical models. Future research should emphasize developing integrated frameworks for long-term risk assessment and mitigation strategies in reservoir environments.Conclusions This study provides new insights into the complex surface dynamics in the Three Gorges Reservoir area, emphasizing the interplay of hydrological, geological, and anthropogenic factors. The findings highlight the need for adaptive management strategies and improved predictive models to mitigate subsidence risks.

The freeze-thaw (F-T) cycle of the active layer (AL) causes the frost heave and thaw settlement deformation of the terrain surface. Accurately identifying its amplitude and time characteristics is important for climate, hydrology, and ecology research in permafrost regions. We used Sentinel-1 SAR data and small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology to obtain the characteristics of F-T cycles in the Zonag Lake-Yanhu Lake permafrost-affected endorheic basin on the Qinghai-Tibet Plateau from 2017 to 2019. The results show that the seasonal deformation amplitude (SDA) in the study area mainly ranges from 0 to 60 mm, with an average value of 19 mm. The date of maximum frost heave (MFH) occurred between November 27th and March 21st of the following year, averaged in date of the year (DOY) 37. The maximum thaw settlement (MTS) occurred between July 25th and September 21st, averaged in DOY 225. The thawing duration is the thawing process lasting about 193 days. The spatial distribution differences in SDA, the date of MFH, and the date of MTS are relatively significant, but there is no apparent spatial difference in thawing duration. Although the SDA in the study area is mainly affected by the thermal state of permafrost, it still has the most apparent relationship with vegetation cover, the soil water content in AL, and active layer thickness. SDA has an apparent negative and positive correlation with the date of MFH and the date of MTS. In addition, due to the influence of soil texture and seasonal rivers, the seasonal deformation characteristics of the alluvial-diluvial area are different from those of the surrounding areas. This study provides a method for analyzing the F-T cycle of the AL using multi-temporal InSAR technology.

The Qilian Mountains, located on the northeastern edge of the Qinghai-Tibet Plateau, are characterized by unique high-altitude and cold-climate terrain, where permafrost and seasonally frozen ground are extensively distributed. In recent years, with global warming and increasing precipitation on the Qinghai-Tibet Plateau, permafrost degradation has become severe, further exacerbating the fragility of the ecological environment. Therefore, timely research on surface deformation and the freeze-thaw patterns of alpine permafrost in the Qilian Mountains is imperative. This study employs Sentinel-1A SAR data and the SBAS-InSAR technique to monitor surface deformation in the alpine permafrost regions of the Qilian Mountains from 2017 to 2023. A method for spatiotemporal interpolation of ascending and descending orbit results is proposed to calculate two-dimensional surface deformation fields further. Moreover, by constructing a dynamic periodic deformation model, the study more accurately summarizes the regular changes in permafrost freeze-thaw and the trends in seasonal deformation amplitudes. The results indicate that the surface deformation time series in both vertical and east-west directions obtained using this method show significant improvements in accuracy over the initial data, allowing for a more precise reflection of the dynamic processes of surface deformation in the study area. Subsidence is predominant in permafrost areas, while uplift mainly occurs in seasonally frozen ground areas near lakes and streams. The average vertical deformation rate is 1.56 mm/a, with seasonal amplitudes reaching 35 mm. Topographical (elevation; slope gradient; aspect) and climatic factors (temperature; soil moisture; precipitation) play key roles in deformation patterns. The deformation of permafrost follows five distinct phases: summer thawing; warm-season stability; frost heave; winter cooling; and spring thawing. This study enhances our understanding of permafrost deformation characteristics in high-latitude and high-altitude regions, providing a reference for preventing geological disasters in the Qinghai-Tibet Plateau area and offering theoretical guidance for regional ecological environmental protection and infrastructure safety.

Under the interference of climate warming and human engineering activities, the degradation of permafrost causes the frequent occurrence of geological disasters such as uneven foundation settlement and landslides, which brings great challenges to the construction and operational safety of road projects. In this paper, the spatial and temporal evolution of surface deformations along the Beihei Highway was investigated by combining the SBAS-InSAR technique and the surface frost number model after considering the vegetation factor with multi-source remote sensing observation data. After comprehensively considering factors such as climate change, permafrost degradation, anthropogenic disturbance, and vegetation disturbance, the surface uneven settlement and landslide processes were analyzed in conjunction with site surveys and ground data. The results show that the average deformation rate is approximately -16 mm/a over the 22 km of the study area. The rate of surface deformation on the pavement is related to topography, and the rate of surface subsidence on the pavement is more pronounced in areas with high topographic relief and a sunny aspect. Permafrost along the roads in the study area showed an insignificant degradation trend, and at landslides with large surface deformation, permafrost showed a significant degradation trend. Meteorological monitoring data indicate that the annual minimum mean temperature in the study area is increasing rapidly at a rate of 1.266 degrees C/10a during the last 40 years. The occurrence of landslides is associated with precipitation and freeze-thaw cycles. There are interactions between permafrost degradation, landslides, and vegetation degradation, and permafrost and vegetation are important influences on uneven surface settlement. Focusing on the spatial and temporal evolution process of surface deformation in the permafrost zone can help to deeply understand the mechanism of climate change impact on road hazards in the permafrost zone.

Abandoned soil disposal in China has become increasingly challenging, which may pose significant safety hazards such as soil settlement and landslides. Interferometry Synthetic Aperture Radar (InSAR) is effective in surface deformation monitoring and Small Baseline Subset-InSAR (SBAS-InSAR) can obtain sufficient coherent point density from the bare soil surface. This study investigated Chishi soil dump in the Shenzhen-Shanwei Special Cooperation Zone (SSSCZ), and a total of 91 Sentinel-1 images from 2019 to 2022 was processed. Accordingly, an improved SBAS-InSAR method was utilized to analyze the soil dump's time-series deformation, and multi-source remote sensing data were used for auxiliary interpretation. Our results indicate that precipitation, high temperature, and construction vibrations may cause instability of the soil dump. Therefore, a depthintegrated continuous medium model was introduced to analyze the potential landslide risk of the soil dump, which demonstrate that a landslide will likely occur, harm personnel, and damage the buildings surrounding the Chishi soil dump when it was saturated (lambda >= 0.50). This research can provide a vital case reference for the analysis, interpretation, disaster prevention, and control evaluation of similar soil dumps.

Constructing hydraulic engineering ensures agricultural development and improves salinization environments. However, in seasonally frozen salinization regions, hydraulic engineering is prone to deformation failure. Leakage from canal raises the regional groundwater level, triggering secondary salinization environmental is-sues. Exploring the instability mechanisms is thus necessary for hydraulic engineering. Traditional deformation monitoring techniques and soil experiments are constrained by observation scale and timeliness. In this study, Sentinel-1B data from November 2017 to August 2019 were acquired. The small baseline subset (SBAS) InSAR approach was employed to interpret the seasonal deformation characteristics in both the vertical and slope di-rections of a damaged canal segment in Songyuan, Northeast China. The mechanical properties of saline-alkali soil under varying water contents were quantified by integrating unconfined compression experiment (UCE). In May, as the soil thawed downward, a frozen lenses with poor permeability formed at a depth of approximately 100 cm, causing the accumulation of meltwater and infiltrated precipitation between the frozen layer and the melting layer in the canal. The soil water content at a depth of 80 to 140 cm exceeded 22 %, reaching a threshold for rapid reduction in unconfined compression strength (UCS). Consequently, in spring, the low soil strength between the frozen layer and the melting layer resulted in interface sliding, with a displacement of-133.88 mm in the canal slope direction. Furthermore, the differential projection of freeze-thaw deformation in the slope direction caused continuous creep of the canal towards the free face, with a value of-23.27 mm, exacerbating the formation of the late spring landslide. Integrating InSAR and engineering geological analysis is beneficial for addressing deformation issues in hydraulic engineering. Ensuring the sustainable operation of hydraulic engi-neering holds important implications for mitigating the salinization process.

In this study, we applied small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) to monitor the ground surface deformation from 2017 to 2020 in the permafrost region within an ~400 km x 230 km area covering the northern and southern slopes of Mt. Geladandong, Tanggula Mountains on the Tibetan Plateau. During SBAS-InSAR processing, we inverted the network of interferograms into a deformation time series using a weighted least square estimator without a preset deformation model. The deformation curves of various permafrost states in the Tanggula Mountain region were revealed in detail for the first time. The study region undergoes significant subsidence. Over the subsiding terrain, the average subsidence rate was 9.1 mm/a; 68.1% of its area had a subsidence rate between 5 and 20 mm/a, while just 0.7% of its area had a subsidence rate larger than 30 mm/a. The average peak-to-peak seasonal deformation was 19.7 mm. There is a weak positive relationship (~0.3) between seasonal amplitude (water storage in the active layer) and long-term deformation velocity (ground ice melting). By examining the deformation time series of subsiding terrain with different subsidence levels, we also found that thaw subsidence was not restricted to the summer and autumn thawing times but could last until the following winter, and in this circumstance, the winter uplift was greatly weakened. Two import indices for indicating permafrost deformation properties, i.e., long-term deformation trend and seasonal deformation magnitude, were extracted by direct calculation and model approximations of deformation time series and compared with each other. The comparisons showed that the long-term velocity by different calculations was highly consistent, but the intra-annual deformation magnitudes by the model approximations were larger than those of the intra-annual highest-lowest elevation difference. The findings improve the understanding of deformation properties in the degrading permafrost environment.

As global warming, permafrost has degraded seriously. The ecological security of many regions has faced a serious threat to their ecological environment, especially the Tianshan mountain regions, which is one of the five major animal husbandry production bases. At present, in these regions, most studies focus on glacier analysis and few pieces of research about permafrost measure. According to 39 ENVISAT ASAR imagines, covered form 2003 June 17th to 2010 June 15th, surface deformation in permafrost region was monitored by SBAS-InSAR method. In this paper, the principles of deformation algorithm were introduced first. When generating the connection graph of the single look complex image of ASAR dataset, there was 126 differential interferogram based on 500 m and 550 days for temporal and spatial baseline respectively. Because of Spatio-temporal baselines and the Doppler centroid difference, 6 ASAR imagines were not generated the connection graph. Then using STRM V4 DEM, 52 low-quality pair of interferogram were eliminated, after the processes of interferograms flattening, adaptive filter, coherence generation and unwrapping. The ground deformation results of the study area were calculated by external ground control points, refinement and re-flattening, estimation of displacement velocity and residual deformation, coherence threshold control, SVD, spatially low-path filtering and temporally high-path filtering. There were 33 results of ground deformation, which covered from 2004 to 2010. According to the deformation results, there were different subsidence and uplift phenomenon in study areas. The deformation rate of the overall study area was no more than +/- 5 cm . yr(-1), and its average deformation rate was < 0. 07 +/- 3. 38) mm . yr(-1). It is indicating that there is a slight subsidence phenomenon in the study area. With the altitude of 3 000 m, the deformation changing mechanism were excavated for the plains and mountain areas distributed by seasonal frozen ground and permafrost respectively. From the research results, deformations in the plain region were uplift except for deformations in the area near cities were subsidence largely. In the mountainous region, the deformations were very scattered than them in the plain region. The overall trend of deformations of the mountain was dominated by subsidence, and subsidence and uplift in the western and eastern regions respectively. There were 15 198 deformation points, which altitude were more than 3 000 m. The annual variation mechanisms of temperature and precipitation about overall deformation points and different deformation intervals points were demonstrated by temperature and precipitation dataset. The results showed that both trends of them have a gradual warming phenomenon. The numbers of deformation rate points about different intervals were 6 364, 6 449 and 2 385 for rates lower than -2. 0 cm . yr(-1), from -2. 0 to 2. 0 cm . yr(-1)( )and higher than 2. 0 cm . yr(-1) in the study mountainous region respectively. Points with negative values were more than points with positive values in the mountainous region, which reflected that subsidence positions were more than uplift positions. This result was also consistent with that global warming cause permafrost degradation then ground subsided. In this paper, the ground deformation results of the study area were successfully calculated by ASAR dataset which was active microwave spectrum. Meanwhile, the deformation results were discussed and prospected in the respects of space, time and the time lag of the permafrost deformation. The study results could provide a new way and reference for the monitoring of permafrost deformation in the Tianshan mountain region.