Highlights What are the main findings? A density-based Freeze-Thaw Disturbance Index (FTDI) was proposed to quantify the spatial clustering of disturbance features. Higher FTDI values indicate a greater likelihood of surface thawing processes triggered by rising temperatures. What are the implications of the main findings? Regions with relatively high FTDI values often contain substantial amounts of organic carbon and may experience delayed vegetation green-up despite general warming trends. FTDI reflects the impact of potential freeze-thaw dynamic phase changes on the geomorphology and offers a new perspective for monitoring permafrost degradation.Highlights What are the main findings? A density-based Freeze-Thaw Disturbance Index (FTDI) was proposed to quantify the spatial clustering of disturbance features. Higher FTDI values indicate a greater likelihood of surface thawing processes triggered by rising temperatures. What are the implications of the main findings? Regions with relatively high FTDI values often contain substantial amounts of organic carbon and may experience delayed vegetation green-up despite general warming trends. FTDI reflects the impact of potential freeze-thaw dynamic phase changes on the geomorphology and offers a new perspective for monitoring permafrost degradation.Abstract The soil freeze-thaw process is a dominant disturbance in the seasonally frozen ground and the active layer of permafrost, which plays a crucial role in the surface energy balance, water cycle, and carbon exchange and has a pronounced influence on vegetation phenology. This study proposes a novel density-based Freeze-Thaw Disturbance Index (FTDI) based on the identification of the freeze-thaw disturbance region (FTDR) over the Qinghai-Tibet Plateau (QTP). FTDI is defined as an areal density metric based on geomorphic disturbances, i.e., the proportion of FTDRs within a given region, with higher values indicating greater areal densities of disturbance. As a measure of landform clustering, FTDI complements existing freeze-thaw process indicators and provides a means to assess the geomorphic impacts of climate-driven freeze-thaw changes during permafrost degradation. The main conclusions are as follows: the FTDR results that are identified by the random forest model are reliable and highly consistent with ground observations; the FTDRs cover 8.85% of the total area of the QTP, and mainly in the central and eastern regions, characterized by prolonged freezing durations and the average annual ground temperature (MAGT) is close to 0 degrees C, making the soil in these regions highly susceptible to warming-induced disturbances. Most of the plateau exhibits low or negligible FTDI values. As a geomorphic indicator, FTDI reflects the impact of potential freeze-thaw dynamic phase changes on the surface. Higher FTDI values indicate a greater likelihood of surface thawing processes triggered by rising temperatures, which impact surface processes. Regions with relatively high FTDI values often contain substantial amounts of organic carbon, and may experience delayed vegetation green-up despite general warming trends. This study introduces the FTDI derived from the FTDR as a novel index, offering fresh insights into the study of freeze-thaw processes in the context of climate change.

Highlights What are the main findings? Permafrost in the Muri area responded to human disturbance without significant spatial expansion during 2000-2024. The semi-arid climate, rough terrain, thin root zone and gappy vertical structure underneath were the major factors. What are the implications of the main findings? Annual ALT estimated from 2000 to 2024 filled the data gap of high-resolution ALT in the Muri area. Knowledge was provided for a better understanding of alpine permafrost development.Highlights What are the main findings? Permafrost in the Muri area responded to human disturbance without significant spatial expansion during 2000-2024. The semi-arid climate, rough terrain, thin root zone and gappy vertical structure underneath were the major factors. What are the implications of the main findings? Annual ALT estimated from 2000 to 2024 filled the data gap of high-resolution ALT in the Muri area. Knowledge was provided for a better understanding of alpine permafrost development.Abstract Alpine permafrost plays a vital role in regional hydrology and ecology. Alpine permafrost is highly sensitive to climate change and human disturbance. The Muri area, which is located in the headwaters of the Datong River, northeast of the Tibetan Plateau, has undergone decadal mining, and the permafrost stability there has attracted substantial concerns. In order to decipher how and to what extent the permafrost in the Muri area has responded to the decadal mining in the context of climate change, daily MODIS land surface temperatures (LSTs) acquired during 2000-2024 were downscaled to 30 m x 30 m. The active layer thickness (ALT)-ground thaw index (DDT) coefficient was derived from in situ ALT measurements. An annual ALT of 30 m x 30 m spatial resolution was subsequently estimated from the downscaled LST for the Muri area using the Stefan equation. Validation of the LST and ALT showed that the root of mean squared error (RMSE) and the mean absolute error (MAE) of the downscaled LST were 3.64 degrees C and -0.1 degrees C, respectively. The RMSE and MAE of the ALT estimated in this study were 0.5 m and -0.25 m, respectively. Spatiotemporal analysis of the downscaled LST and ALT found that (1) during 2000-2024, the downscaled LST and estimated ALT delineated the spatial extent and time of human disturbance to permafrost in the Muri area; (2) human disturbance (i.e., mining and replantation) caused ALT increase without significant spatial expansion; and (3) the semi-arid climate, rough terrain, thin root zone and gappy vertical structure beneath were the major controlling factors of ALT variations. ALT, estimated in this study with a high resolution and accuracy, filled the data gaps of this kind for the Muri area. The ALT variations depicted in this study provide references for understanding alpine permafrost evolution in other areas that have been subject to human disturbance and climate change.

Highlights What are the main findings? Variations in hazard-prone environments dominate the spatial heterogeneity of multi-hazard distribution. Thermal hazard susceptibility is expected to increase greatly by the end of the century due to permafrost degradation. What is the implication of the main findings? Segmented assessment can effectively improve evaluation accuracy and model interpretability. Thermal hazards exhibit significant sensitivity to climate change, while gravity hazards do not.Highlights What are the main findings? Variations in hazard-prone environments dominate the spatial heterogeneity of multi-hazard distribution. Thermal hazard susceptibility is expected to increase greatly by the end of the century due to permafrost degradation. What is the implication of the main findings? Segmented assessment can effectively improve evaluation accuracy and model interpretability. Thermal hazards exhibit significant sensitivity to climate change, while gravity hazards do not.Abstract With climate change, the Qinghai-Tibet Highway (QTH) is facing increasingly severe risks of natural hazards, posing a significant threat to its normal operation. However, the types, distribution, and future risks of hazards along the QTH are still unclear. In this study, we established an inventory of multi-hazards along the QTH by remote sensing interpretation and field validation, including landslides, debris flows, thaw slumps, and thermokarst lakes. The QTH was segmented into three sections based on hazard distribution and environmental factors. Susceptibility modelling was performed for each hazard within each using machine learning models, followed by further evaluation of hazard susceptibility under future climate change scenarios. The results show that, at present, approximately 15.50% of the area along the QTH exhibits high susceptibility to multi-hazards, with this proportion projected to increase to 20.85% and 23.32% under the representative concentration pathways (RCP) 4.5 and RCP 8.5 distant future scenarios, respectively. Variations in hazard-prone environments dominate the spatial heterogeneity of multi-hazard distribution. Gravity hazards demonstrate limited sensitivity to climate change, whereas thermal hazards exhibit a more pronounced response. Our geomorphology-based segmented assessment framework effectively enhances evaluation accuracy and model interpretability. The results can provide critical insights for the operation, maintenance, and hazard risk management of the QTH.

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0-40 cm) with a satisfactory accuracy (R-2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.

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.

Permafrost is one of the crucial components of the cryosphere, covering about 25% of the global continental area. The active layer thickness (ALT), as the main site for heat and water exchange between permafrost and the external atmosphere, its changes significantly impact the carbon cycle, hydrological processes, ecosystems, and the safety of engineering structures in cold regions. This study constructs a Stefan CatBoost-ET (SCE) model through machine learning and Blending integration, leveraging multi-source remote sensing data, the Stefan equation, and measured ALT data to focus on the ALT in the Qinghai-Tibet Plateau (QTP). Additionally, the SCE model was verified via ten-fold cross-validation (MAE: 20.713 cm, RMSE: 32.680 cm, R2: 0.873, and MAPE: 0.104), and its inversion of QTP's ALT data from 1958 to 2022 revealed 1998 as a key turning point with a slow growth rate of 0.25 cm/a before 1998 and a significantly increased rate of 1.26 cm/a afterward. Finally, based on multiple model input factor analysis methods (SHAP, Pearson correlation, and Random Forest Importance), the study analyzed the ranking of key factors influencing ALT changes. Meanwhile, the importance of Stefan equation results in SCE model is verified. The research results of this paper have positive implications for eco-hydrology in the QTP region, and also provide valuable references for simulating the ALT of permafrost.

Previous lunar missions, such as Surveyor, Apollo, and the Lunar Atmosphere and Dust Environment Explorer (LADEE), have played a pivotal role in advancing our understanding of the lunar exosphere's dynamics and its relationship with solar wind flux. The insights gained from these missions have laid a strong foundation for our current knowledge. However, due to insufficient near-surface observations, the scientific community has faced challenges in interpreting the phenomena of lunar dust lofting and levitation. This paper introduces the concept of signals of opportunity (SoOP), which utilizes radio occultation (RO) to retrieve the near-surface dust density profile on the Moon. Gravity Recovery and Interior Laboratory (GRAIL) radio science beacon (RSB) signals are used to demonstrate this method. By mapping the concentration of lunar near-surface dust using RO, we aim to enhance our understanding of how charged lunar dust interacts with surrounding plasma, thereby contributing to future research in this field and supporting human exploration of the Moon. Additionally, the introduced SoOP will be able to provide observational constraints to physical model development related to lunar surface particle sputtering and the reactions of near-surface dust in the presence of solar wind and electrostatically charged dust grains.

The degradation of subarctic peatland ecosystems under climate change impacts surrounding landscapes, carbon balance, and biogeochemical cycles. To assess these ecosystems' responses to climate change, it is essential to consider not only the active-layer thickness but also its thermo-hydraulic conditions. Ground-penetrating radar is one of the leading methods for studying the active layer, and this paper proposes systematically investigating its potential to determine the thermal properties of the active layer. Collected experimental data confirm temperature hysteresis in peat linked to changes in water and ice content, which GPR may detect. Using palsa mires of the Kola Peninsula (NW Russia) as a case study, we analyze relationships between peat parameters in the active layer and search for thermal gradient responses in GPR signal attributes. The results reveal that frequency-dependent GPR attributes can delineate thermal intervals of +/- 1 degrees C through disperse waveguides. However, further verification is needed to clarify the conditions under which GPR can reliably detect temperature variations in peat, considering factors such as moisture content and peat structure. In conclusion, our study discusses the potential of GPR for remotely monitoring freeze-thaw processes and moisture distribution in frozen peatlands and its role as a valuable tool for studying peat thermal properties in terms of permafrost stability prediction.

Influenced by a warm and humid climate, the permafrost on the Qinghai-Tibet Plateau is undergoing significant degradation, leading to the occurrence of extensive thermokarst landforms. Among the most typical landforms in permafrost areas is thaw slump. This study, based on three periods of data from keyhole images of 1968-1970, the fractional images of 2006-2009 and the Gaofen (GF) images of 2018-2019, combined with field surveys for validation, investigates the distribution characteristics and spatiotemporal variation trends of thaw slumps in the Hoh Xil area and evaluates the susceptibility to thaw slumping in this area. The results from 1968 to 2019 indicate a threefold increase in the number and a twofold increase in total area of thaw slumps. Approximately 70% of the thaw slumps had areas less than 2 x 104 m2. When divided into a grid of 3 km x 3 km, about 1.3% (128 grids) of the Hoh Xil region experienced thaw slumping from 1968 to 1970, while 4.4% (420 grids) showed such occurrences from 2018 to 2019. According to the simulation results obtained using the informativeness method, the area classified as very highly susceptible to thaw slumping covers approximately 26% of the Hoh Xil area, while the highly susceptible area covers about 36%. In the Hoh Xil, 61% of the thaw slump areas had an annual warming rate ranging from 0.18 to 0.25 degrees C/10a, with 70% of the thaw slump areas experiencing a precipitation increase rate exceeding 12 mm/10a. Future assessments of thaw slump development suggest a possible minimum of 41 and a maximum of 405 thaw slumps occurrences annually in the Hoh Xil region. Under rapidly changing climatic conditions, apart from environmental risks, there also exist substantial potential risks associated with thaw slumping, such as the triggering of large-scale landslides and debris flows. Therefore, it is imperative to conduct simulated assessments of thaw slumping throughout the entire plateau to address regional risks in the future.

The permanently shadowed regions of the lunar South Pole have become a key target for international lunar exploration due to their unique scientific value and engineering challenges. In order to effectively screen suitable landing zones near the lunar South Pole, this research proposes a comprehensive evaluation method based on a self-organizing map (SOM). Using multi-source remote sensing data, the method classifies and analyzes candidate landing zones by combining scientific purposes (such as hydrogen abundance, iron oxide abundance, gravity anomalies, water ice distance analysis, and geological features) and engineering constraints (such as Sun visibility, Earth visibility, slope, and roughness). Through automatic clustering, the SOM model finds the important regions. Subsequently, it integrates with a supervised learning model, a random forest, to determine the feature importance weights in more detail. The results from the research indicate the following: the areas suitable for landing account for 9.05%, 5.95%, and 5.08% in the engineering, scientific, and synthesized perspectives, respectively. In the weighting analysis of the comprehensive data, the weights of Earth visibility, hydrogen abundance, kilometer-scale roughness, and slope data all account for more than 10%, and these are thought to be the four most important factors in the automated site selection process. Furthermore, the kilometer-scale roughness data are more important in the comprehensive weighting, which is in line with the finding that the kilometer-scale roughness data represent both surface roughness from an engineering perspective and bedrock geology from a scientific one. In this study, a local examination of typical impact craters is performed, and it is confirmed that all 10 possible landing sites suggested by earlier authors are within the appropriate landing range. The findings demonstrate that the SOM-model-based analysis approach can successfully assess lunar South Pole landing areas while taking multiple constraints into account, uncovering spatial distribution features of the region, and offering a rationale for choosing desired landing locations.