Search Results (212)

Talus slopes and scree deposits connect rockwall sediment supply, gravitational transport, footslope storage, hydrothermal conditions, and mountain hazards, yet their literature is distributed across several disciplines. This study develops a manually refined bibliometric dataset to clarify the knowledge structure and thematic evolution of talus slope geomorphology. We retrieved 971 records from the Web of Science (WoS) Core Collection, including the Science Citation Index-Expanded (SCI-EXPANDED) and Social Science Citation Index (SSCI) databases, manually screened their geomorphic relevance, excluded records from the incomplete publication year 2026, and analyzed 548 articles and reviews published during 1966–2025. Bibliometrix and Biblioshiny analyses show sustained publication growth, especially after 2006, and an intellectual base combining slope-process geomorphology, paraglacial and periglacial research, geophysical investigation, and hazard studies. Standardized Author Keywords indicate increasing attention to permafrost environment, subsurface detection, multi-source monitoring, and slope hazards. These indexed patterns support a synthesis of talus slopes as dynamic source-transport-storage systems, while the WoS-only coverage and manual refinement steps define the study’s evidential limits. Full article

Rock glaciers are important ice-debris landforms in high-mountain permafrost environments, but the development, knowledge base, and emerging directions of this research field remain insufficiently synthesized. This study retrieved English-language article and article/data paper records from the Science Citation Index Expanded database of the Web of Science Core Collection using the query TS = (“rock glacier*” OR “rock glacier*”). After document-type filtering and manual screening, 1125 valid records published between 1910 and 2025 were analyzed. Descriptive bibliometrics were used to characterize scientific production and collaboration patterns, Reference Publication Year Spectroscopy (RPYS) was used to identify historically influential publication years and foundational references, and keyword co-occurrence networks, thematic mapping, and thematic evolution analysis were used to trace associations among research topics. A Logistic life-cycle model was used only as a diagnostic tool for the current publication stage, not as a deterministic forecast. The results indicate that global rock glacier research remains in an active growth stage, although model-derived saturation values should be interpreted cautiously because bibliometric trajectories are affected by database coverage, indexing practices, research funding, technological change, and policy demand. RPYS shows that the knowledge base evolved from geomorphological description, classification, and genetic debate toward permafrost creep, internal structure, thermo-mechanical response, and hydrological significance. Keyword and thematic analyses show increasing attention to climate change, mountain permafrost, InSAR, ground-penetrating radar, hydrological processes, and multi-source monitoring. Because the dataset is restricted to English-language SCI-Expanded records, the results should be interpreted as a map of indexed international literature rather than a complete inventory of all rock glacier knowledge. Full article

Petroleum hydrocarbon contamination of soils remains a persistent environmental problem in Arctic and sub-Arctic regions, where oil extraction, pipeline transportation, fuel storage, industrial legacy sites, and diesel-dependent infrastructure coexist with fragile cold-climate ecosystems. Remediation in these regions is constrained by low temperatures, short thaw seasons, permafrost, waterlogged active layers, slow vegetation recovery, limited infrastructure, and high mobilization costs, which limit the direct transferability of conventional temperate-zone technologies. This study presents a structured narrative review of international and Russian evidence on petroleum-contaminated soil management in cold regions, focusing on monitoring as a basis for remediation decision-making. Peer-reviewed studies, technical guidance documents, regulatory frameworks, and regional case studies were analyzed across key domains, including environmental constraints, hydrocarbon behavior, monitoring methodologies, and remediation technologies. Particular attention is given to chemical analysis, hydrocarbon fractionation, bioavailability-oriented methods, ecotoxicological bioassays, and microbial indicators as tools linking contamination assessment with remediation strategy selection. Reliance on total petroleum hydrocarbon (TPH) concentration as a primary endpoint is shown to be insufficient, especially in cold-region soils where strong sorption and limited mass transfer decouple concentration from biological exposure. Multi-endpoint monitoring systems provide a more reliable basis for assessing contaminant risk, treatment effectiveness, and soil recovery. For the Russian Arctic, the integration of national recultivation frameworks with risk-based assessment and ecotoxicological monitoring is identified as a key pathway for improving remediation outcomes. A decision-oriented framework is proposed that links environmental conditions, contaminant properties, and monitoring data to support the selection and optimization of remediation strategies. This study supports a transition from concentration-based cleanup toward risk-informed and ecosystem-oriented management of petroleum-contaminated soils in Arctic and sub-Arctic environments. Full article

Near-surface air temperature is the main atmospheric forcing of frozen-ground systems in maritime Antarctica, yet most studies have emphasized mean annual or seasonal trends rather than thermal-regime evolution. This study analyzes hourly air-temperature records from eight PERMATHERMAL monitoring stations on Livingston and Deception Islands (South Shetland Islands, Antarctica) for 2000–2022 to evaluate changes in mean conditions, daily thermal regimes, degree-day forcing, and their implications for frozen ground. Hourly data were aggregated to daily, monthly, annual, and thermal-year scales, and valid days were classified into six thermal regimes (F1, F2, IS, FT, T2, and T1). FDD, TDD, annual degree-day balance (BDD), and freezing and thawing season duration were also calculated. Recent warming is expressed not only as higher mean annual air temperature, but also as a reorganization of the annual thermal regime, with fewer cold days, more thaw-related conditions, and less negative BDD values at most stations. These changes are consistent with previously reported GST evolution and indicate a shift in atmospheric forcing toward weaker freezing dominance and more thaw-favorable conditions. However, their implications for active-layer thickness and permafrost stability should be interpreted as climatic indications rather than as the direct evidence of ground thermal change. Full article

Permafrost extent and active layer thickness (ALT) have implications for polar-region infrastructure and communities. Much of the world’s permafrost is rich in ground ice and can become highly unstable during seasonal freeze–thaw cycling. Monitoring these dynamics is critical for quantifying infrastructure risk, informing new construction, and prioritizing essential repairs of existing infrastructure. Fiber optic distributed acoustic sensing (DAS) offers an alternative, providing high-resolution monitoring over large distances. This proof-of-concept study evaluates a surface-deployed DAS cable as a rapid, nondestructive tool for observing seasonal thaw in discontinuous permafrost in Fox, Alaska. During three field campaigns (May 2024, September 2024, and June 2025), a surface laid cable recorded active source sledgehammer strikes. Dispersion curves extracted from the surface wave data were aligned with theoretical curves using a simplified two-layer forward model, representing a seasonally thawed layer overlying hard frozen ground. Based on best fit estimates derived from this model, the active layer thickness was calculated at approximately 0.8 m in May 2024, thickening to 1.9 m in September 2024, and 0.65 m in June 2025. These results demonstrate that surface-deployed DAS can effectively observe changes in permafrost seasonal thaw. This technique could be used prior-to and/or in-addition-to performing more invasive, time-consuming subsurface investigation. Full article

Interior Alaska’s rapidly thawing permafrost poses risks to environmental systems and infrastructure, challenging municipal planning. As part of a larger project examining frozen commons, McGrath, Alaska, officials and tribal council members requested a permafrost map. This paper presents ground thermal monitoring (October 2023 to March 2025) and imagery-derived land cover and permafrost/seasonal freezing maps developed after testing machine learning and contextual feature methods. Over the two years of observation, ground temperature warmed 0.26 °C year⁻¹ at 1.5 m depth. A high-accuracy land cover classification was generated to project ground thermal conditions across the community. Several supervised machine learning algorithms were compared with and without contextual features on a Satellite Pour l’Observation de la Terre (SPOT) scene in ArcGIS Pro. Per-pixel classification performed better given the contiguous spectral features, and contextual features did not improve overall accuracy. Instead, a random forest classifier that yielded the highest overall accuracy was used to generate a 1.5 m resolution permafrost/seasonal freezing map. Maps and thermal data can inform community frozen commons decision-making, and methods can be repeated to monitor regional change. Discussion of results highlights potential permafrost mapping applications, particularly of Gabor and mean contextual features with object segmentation. Full article

Accurate prediction of embankment settlement and evaluation of its serviceability in permafrost regions are significantly challenged by scarce monitoring data and dynamic, non-stationary settlement processes. To address this, an integrated framework combining change-point detection with a novel dynamic prediction model is proposed. Analysis of long-term monitoring data from the Qinghai–Tibet Railway using the Pettitt test revealed a key change point around 2015, indicating a transition towards stabilization. Subsequently, an SAA-GRU-LSTM hybrid model, employing a dynamic compensation prediction strategy, was developed. The model successfully utilized only early-stage data to forecast future settlement trends, demonstrating robust performance in adapting to the identified abrupt change. Furthermore, by applying established engineering serviceability criteria to both historical and predicted data, the framework enables a dynamic and prospective serviceability assessment. This methodology provides a practical tool for the maintenance and risk management of infrastructure in permafrost environments under conditions of data scarcity and process uncertainty. Full article

Arctic–boreal wetlands and lakes are among the most significant and most uncertain natural sources of atmospheric methane. Rapid Arctic amplification, permafrost thaw, hydrological change, and increasing ecosystem productivity are expected to intensify methane emissions from high-latitude landscapes. Yet, significant uncertainties persist in quantifying their magnitude, seasonality, and spatial distribution. This review synthesizes the current state of the art in monitoring methane emissions from Arctic–boreal wetlands and lakes through complementary bottom-up and top-down approaches. We examine Earth observation (EO) capabilities, including optical, thermal infrared (TIR), and synthetic aperture radar (SAR) missions, as well as new emerging satellite platforms. We also assess in situ measurement networks, wetland and lake inventories, empirical and process-based models, and atmospheric inversion frameworks. Key gaps remain in representing small waterbodies, shoreline heterogeneity, winter emissions, inventory harmonization, and integration between atmospheric retrievals and surface-based flux models. Moreover, advances in multi-sensor data fusion, explainable artificial intelligence (XAI), physics-informed inversion methods, and geospatial foundation models offer strong potential to reduce these uncertainties. A coordinated integration of satellite observations, field measurements, and transparent modeling frameworks is essential to improve Arctic–boreal methane budgets and strengthen projections of climate feedback in a rapidly warming region. Full article

Emerging contaminants (ECs) comprise diverse pollutant classes that are increasingly detected in remote environments due to their persistence and long-range transport potential. In cold regions, atmospheric cold-trapping processes favour their accumulation in high-altitude and high-latitude snow and ice, which act as sensitive archives and secondary sources of contamination. While previous studies have addressed individual environmental compartments (e.g., snowpack, glacier ice, meltwater), focusing on specific contaminant classes, a systematic review integrating the occurrence, behaviour and impacts of major EC groups in polar and alpine snow and ice is still lacking. To fill this gap, this work synthesised current knowledge on the environmental fate of three key EC categories in the cryosphere: metals and metalloids (MMs), industrial chemicals and by-products (ICBs), and pharmaceuticals and personal care products (PPCPs). PRISMA guidelines were accurately followed for research, which was based on a Google Scholar search combining keywords on cryospheric matrices (snow, firn, ice cores), geographical regions (Arctic, Antarctic, Alps, high mountains), and contaminant classes. Of 350 records initially identified, 300 met the eligibility criteria (post-industrial snow, firn, or ice cores studies) after excluding studies focused on aerosol or meltwater-only, method-focused papers, pre-industrial datasets, urban-only investigations, and duplicates. Risk of bias was qualitatively assessed through manual screening, evaluating matrix eligibility, temporal consistency, analytical methods, detection limits, and duplicate data, with particular attention to inconsistencies in ECs classification. Strict operational definitions were therefore applied to ensure methodological coherence. Concentration data were harmonised into a standardised database, and findings were synthesised through a structured narrative supported by tabulated datasets organised by matrix and site. Overall, the evidence indicates widespread occurrence of ECs in the global cryosphere, with spatial variability linked to emission sources, long-range transport pathways, and snow physicochemical properties. Climate-change-driven alterations of snow dynamics, glacier retreat and permafrost thaw are expected to modify partitioning equilibria and enhance the secondary release of legacy and contemporary contaminants. However, significant limitations persist, including geographical gaps, variability in analytical sensitivity, lack of long-term monitoring for certain EC classes, and inconsistencies in contaminant classification frameworks. Despite these constraints, the synthesis highlights consistent emerging patterns and underscores the need to strengthen existing environmental protocols to mitigate potential risks to ecosystems and human health. Full article

Rock glaciers are key indicators of mountain permafrost and act as climatically resilient water reservoirs in arid mountains. This study presents the first inventory and kinematic classification of rock glaciers in Western Tien Shan (Kazakhstan and Kyrgyzstan), combining geomorphological mapping with InSAR time-series analysis. Using high-resolution optical imagery (Google Earth Pro (version 7.3.6.10441), Bing Maps, SAS Planet (version 200606.10075), digital elevation models, and Small Baseline Subset InSAR processing, 741 rock glaciers covering more than 70.5 km² were identified. Activity classification revealed 232 transitional and 509 active forms, with mean seasonal displacement rates of ~15 cm yr⁻¹ calculated based on August and September observations. Spatial analysis showed a strong rock glacier concentration on north-facing slopes (>66% of total area) with reduced potential incoming solar radiation. Rock glaciers mainly occur between 2800 and 3800 m a.s.l., with a mean elevation of 3340 m a.s.l. However, their kinematic activity varies across mid-altitudinal ranges, underscoring the influence of slope, aspect, shading, and local topography. Integration with the Global Permafrost Zonation Index (PZI) indicated a lower permafrost boundary at ~1922 m a.s.l., with the largest and most active glaciers occurring at intermediate PZI values (0.5–0.7). This first rock glacier inventory for the Western Tien Shan establishes a benchmark dataset that supports the validation and refinement of global models at a regional scale, guides priorities for permafrost monitoring, and provides a replicable framework for inventory development in other data-scarce mountain regions. Full article

Despite the ecological sensitivity of the Yangtze River Source Region (YRSR), the current research critically lacks a quantified assessment of the spatial occurrence probability of Retrogressive Thaw Slumps (RTSs) in this specific high-altitude terrain. This study aims to bridge this knowledge gap by establishing a robust susceptibility assessment framework to accurately model the spatial distribution and risk levels of RTSs. The innovations of this research include (i) the construction of a complete and up-to-date 2024 RTS inventory for the entire YRSR based on high-resolution optical remote sensing; (ii) the integration of time-series spectral features (e.g., vegetation and moisture trends) alongside static topographic variables to enhance the physical interpretability of machine learning models; and (iii) the application of advanced ensemble learning algorithms combined with SHAP analysis to establish a comprehensive RTS susceptibility zonation. The results reveal a rapid intensification of instability, evidenced by an 83.5% surge in RTS abundance, with the CatBoost model achieving exceptional accuracy (AUC = 0.994), and identifying that specific static topographic factors (particularly elevations between 4693 and 4812 m and north-to-east aspect) and dynamic spectral anomalies (indicated by declining vegetation vigor and increasing surface wetness) are the dominant drivers controlling RTS distribution. This study provides essential baseline data and spatial guidance for ecological conservation and engineering maintenance in the Asian Water Tower, demonstrating a highly effective paradigm for monitoring permafrost hazards under climate warming. Full article

Changes in vegetation coverage reflect the status and dynamic processes of ecosystems and serve as a crucial foundation for regional ecological protection. Using Landsat-5 and Sentinel-2 data, this study calculated the vegetation coverage in the Three-River Headwaters (TRH) region from 1990 to 2022 with the pixel dichotomy model, identified land cover changes over the past three decades via a deep neural network, and analyzed the primary influencing factors behind vegetation coverage dynamics. The results indicate that vegetation coverage in TRH has generally increased, as very high vegetation coverage expanded by 10.3%, while very low and low vegetation coverage decreased by 4.2%. Extensive bare land in the western region decreased and transformed into grassland, while the areas of shrubland and forest in the central and eastern TRH areas increased. The areas of grassland, shrubland, and forest increased by 3.7 × 10⁴ km², 2.1 × 10⁴ km², and 4.7 × 10³ km², respectively. Precipitation, elevation, and temperature are the main factors influencing the spatial variation in vegetation coverage. We found that the contributions of the permafrost active layer thickness and precipitation to changes in vegetation coverage are high. Finally, we provide a detailed and timely analysis of recent vegetation distribution and type changes on the Tibetan Plateau, offering a strengthened scientific foundation for monitoring, assessment, and ecological conservation efforts aimed at supporting ecosystem restoration in the region. Full article

The permafrost in forest regions of Northeast China is very sensitive to the disturbance of subgrade construction, which will aggravate the degradation of the permafrost upper limit, leading to freeze–thaw deformation of the permafrost subgrade. Based on the road construction project of Highway 332 in forest regions in Northeast China, through theoretical analysis, indoor experiments, on-site monitoring, and numerical simulation methods, a thermo-hydro-mechanical coupling numerical model of the permafrost subgrade was established. A “two-step” construction countermeasure for freeze–thaw deformation of permafrost subgrade based on rubble stone subgrade structure was proposed. The study indicates that the addition of rubble stones to the subgrade structure has a significant cooling effect. The optimal thickness for filling rubble stones is 1 m. The optimal construction timing for subgrade is a two-step construction across the year. The stamping construction of the rubble stones is in November. The filling construction of rubble stones and gravel is in April and May of the next year. Based on the proposed construction countermeasure for permafrost subgrade, the settlement at the center of the subgrade surface is 12.7 mm in the 5th year, 17.6 mm in the 10th year, 21.1 mm in the 15th year, and 23.5 mm in the 20th year. The settlement deformation of the subgrade tends to stabilize, which can ensure the long-term stability and safety of road operations. Full article

Global climate change is exerting a growing impact on agricultural ecosystems. Accurately assessing the spatiotemporal dynamics of agricultural ecosystem respiration and its response mechanisms to climate has therefore emerged as a critical issue in agricultural carbon cycle research and climate change response. It should be noted that the ‘agro-ecosystem’ referred to in this study covers two major types: one is the farmland agro-ecosystem dominated by crop planting (such as farmland, orchard and other artificial management systems), and the other is the grassland agro-ecosystem dominated by herbaceous plants and managed by humans (such as grazing grassland and mowing grassland). Remote sensing technology provides a new way to break through the limitations of traditional ground observation by virtue of its advantages of large-scale and continuous monitoring. Based on the CiteSpace bibliometric method, this study focused on the key time window of 2021–2025, systematically searched the core collection of Web of Science, and finally included 222 related literature. This period marks the initial stage of the rise and rapid development of this interdisciplinary field, enabling us to capture the formation of its knowledge structure and the evolution of its research paradigm from the source. Through the quantitative analysis of this literature, it aims to reveal the research hotspots, development paths and frontier trends in this field. The results show that China occupies a dominant position in this field (135 articles). The evolution of research shows a three-stage development characterized by “technology-driven-method fusion-system coupling,” which is divided into the initial development period (2021–2022), the rapid growth period (2023–2024) and the deepening development period (2025) (because 2025 has not yet ended, this stage is a preliminary discussion). Keyword clustering analysis identified 13 important research directions, including machine learning (# 0 clustering), permafrost (# 1 clustering) and carbon flux (# 2 clustering). It is found that the deep integration of artificial intelligence and remote sensing data is promoting the transformation of research methods from traditional inversion to intelligent modeling. At the same time, the attention to alpine grassland and other ecosystems also reflects the trend that the research frontier extends to the interaction zone between the agricultural ecosystem and the natural environment. Future research should prioritize three key directions: building multi-scale monitoring networks, developing “grey box” models that integrate mechanisms and data fusion, and evaluating the carbon emission reduction efficiency of agricultural management practices. These efforts will provide a theoretical basis for carbon management and climate adaptation in agricultural ecosystems, as well as scientific and technological support for achieving global agricultural sustainable development goals (specifically, SDG13 on climate action and SDG15 on terrestrial ecosystem conservation). Full article

Thermokarst lakes play a crucial role in regulating hydrological, ecological, and biogeochemical processes in permafrost regions. However, due to the limited spatial resolution of earlier satellite imagery, small thermokarst lakes—highly sensitive to climate change and permafrost degradation—have often been overlooked, hindering accurate spatiotemporal analyses. To address this limitation, five water indices—Modified Normalized Difference Water Index (MNDWI), Multi-Band Water Index (MBWI), Automated Water Extraction Index (AWEI_sh and AWEI_nsh), and Red Edge Water Index (RWI)—were employed based on Sentinel-2 imagery from 2021 to extract thermokarst lakes in the Qinghai–Tibet Highway (QTH) region, China. Visual validation indicated that the Red Edge Water Index (RWI) yielded the best performance, with an error of only 10.21%, significantly lower than other indices (e.g., MNDWI: 41.36%; MBWI: 38.80%). Seasonal comparisons revealed that the applicability of different water indices varies, with autumn months (September to October) being the optimal period for lake extraction due to stable and unfrozen surface conditions. Using the RWI, 56 thermokarst lake drainage events were identified in the study area from 2016 to 2025 (as of September 2025), most occurring after 2019—likely associated with climatic factors—and small lakes were found to be more prone to drainage, accompanied by notable surface subsidence in drained regions. These findings are applicable across the Qinghai–Tibet Plateau (QTP) and provide a scientific basis for monitoring thermokarst lakes, delineating accurate lake boundaries, and exploring drainage mechanisms. Full article