Retrogressive thaw slumps (RTSs) are spectacular landforms that occur due to the thawing of ice-rich permafrost or melting of massive ground ice, often in hillslope terrain. RTSs occur in the Arctic, the subarctic, and high mountain (Qinghai–Tibet Plateau) permafrost regions and are observed to expand in size and number due to climate warming. As the observation of RTSs is receiving more and more attention due to their important role in permafrost thaw; impacts on topography; mobilization of sediment, carbon, nutrients, and contaminants; and their effects on downstream hydrology and water quality, the thematic breadth of studies increases and scientists from different scientific backgrounds and perspectives contribute to new RTS research. At this point, a wide range of terminologies originating from different scientific schools is used, and we identified the need to provide an overview of variable characteristics of RTSs to clarify terminologies and ease the understanding of the literature related to RTS processes, dynamics, and feedbacks. We review the theoretical geomorphological background of RTS formation and landform characteristics to provide an up-to-date understanding of the current views on terminology and underlying processes. The presented overview can be used not only by the international permafrost community but also by scientists working on ecological, hydrological, and biogeochemical consequences of RTS occurrence and by remote-sensing specialists developing automated methods for mapping RTS dynamics. The review will foster a better understanding of the nature and diversity of RTS phenomena and provide a useful base for experts in the field but also ease the introduction to the topic of RTSs for scientists who are new to it.

Deep‐learning (DL) models have become increasingly beneficial for the detection of retrogressive thaw slumps (RTS) in the permafrost domain. However, comparing accuracy metrics is challenging due to unstandardized labeling guidelines. To address this, we conducted an experiment with 12 international domain experts from a broad range of scientific backgrounds. Using 3 m PlanetScope multispectral imagery, they digitized RTS footprints in two sites. We evaluated label uncertainty by comparing manually outlined RTS labels using Intersection‐over‐Union (IoU) and F1 metrics. At the Canadian Peel Plateau site, we see good agreement, particularly in the active parts of RTS. Differences were observed in the interpretation of the debris tongue and the stable vegetated sections of RTS. At the Russian Bykovsky site, we observed a larger mismatch. Here, the same differences were documented, but several participants mistakenly identified non‐RTS features. This emphasizes the importance of site‐specific knowledge for reliable label creation. The experiment highlights the need for standardized labeling procedures and definition of their scientific purpose. The most similar expert labels outperformed the accuracy metrics reported in the literature, highlighting human labeling capabilities with proper training, site knowledge, and clear guidelines. These findings lay the groundwork for DL‐based RTS monitoring in the pan‐Arctic.

Retrogressive thaw slumping (RTS) is a mass-wasting process characterized by upslope backwasting and rapid thawing of ice-rich permafrost. High-resolution digital elevation models (DEMs) from ArcticDEM enable the volumetric and soil organic carbon quantification of medium to large disturbance areas undergoing RTS ( ≥10,000 m²) for the Northern Hemisphere. Using DEM time-series analysis and deep learning, we retrieve a total of 2747 disturbance areas undergoing active RTS with a total volume loss of (317.0 ± 0.3) × 10⁶m³ between 2012 and 2022. Here we show that climatic drivers of RTS activity exhibit latitudinal and regional variations, specifically, the number of precipitation-driven RTS decreases linearly as latitudes increase, whereas temperature-driven RTS increases sharply. Finally, we estimate that 96% of detected RTS thawed ~1.95 × 10^-3 Pg carbon per year, equivalent to ~0.2% of annual gradual thaw emission estimates. Our results highlight the complexity of regional RTS dynamics and the importance of high resolution, long-term monitoring efforts.

Retrogressive Thaw Slumps (RTS) are widespread mass-wasting hillslope failures triggered by thawing permafrost. While regional studies have provided insights into the spatial distribution and dynamics of RTS, a consistent and unbiased quantification and monitoring remains unsolved at pan-arctic scales. We present the Database of AI-detected Arctic RTS footprints (DARTS), comprising ~43,000 individual footprints of active RTS or active areas within larger RTS landforms. DARTS spans ~1.6 million km² from 2018–2023, with at least annual coverage from 2021–2023 across a ~900,000 km² region. The database is freely available in two processing levels: sub-annual and annually aggregated polygon footprints including spatial and tabular metadata. DARTS uses a highly automated workflow based on deep learning segmentation of PlanetScope multi-spectral satellite imagery (3–5 m resolution) and elevation data. Validation against different regional RTS datasets yielded F1 scores ranging from 0.263 to 0.700, with higher accuracy in areas of intense RTS activity. DARTS provides a valuable resource for systematically mapping, quantifying, and analyzing active hillslope thermokarst distribution and changes over time across the circum-arctic permafrost region.

The Arctic zone of West Siberia (Yamal and Gydan peninsulas) is an area with continuous permafrost and tabular ground ice close to the surface, active thermodenudation, and related landforms: retrogressive thaw slumps (RTS); in Russian referred to as thermocirques (TC). The dimensions of most TCs have not been determined so far. We use Sentinel 2 imagery to measure each TC area ranging from 0.55 to 38 ha with a median of 2.5 ha. Around 95% of TCs have an area of less than 10 ha. The largest areas are gained due to the merging of several neighboring TCs. The ArcticDEM is used to determine TC edge elevation and slope angle. In general, the Median TC of the Yamal peninsula has an area of 1.8 ha, an elevation of the edge of 17.7 m, and a slope angle of 2.5°. The Median TC of the Gydan peninsula has an area of 2.6 ha, elevation of the edge of 29.4 m, and slope angle of 3°. TCs of the Gydan peninsula occupy higher positions and slightly steeper slopes compared to TCs of the Yamal peninsula. The ranges of the median and the largest TC areas are consistent with the reported RTS dimensions in North America.

A classification of cryogenic-landslide landforms is developed for mapping their distribution and dynamics. It is based on the previously suggested classification subdividing cryogenic landsliding into two main types: cryogenic translational landslides (or active-layer detachment slides), and cryogenic earth flows (or retrogressive thaw slumps). The increased proportion of retrogressive thaw slumps compared to active layer detachments in the North of West Siberia in the last decade creates the need for an expanded classification of cryogenic earth flows. One of the important issues is separating the process of landsliding and resulting landforms, which in English are covered by one term ‘retrogressive thaw slump’. In dealing with the landforms, we distinguish (1) open and (2) closed ones. Open cryogenic-landslide landforms are those formed by the retreating of the coast bluff due to the thaw of ice or ice-rich deposits with an additional impact from wave or stream action. Closed cryogenic-landslide landforms are those initiated on a slope landward, and thawed material is delivered to the coast or stream through an erosional channel. Morphologically we distinguish thermocirques and thermoterraces depending on the shape of the retreating headwall, crescent or linear, respectively. An important issue is the type of ground ice subjected to thaw: tabular, ice-wedge or constitutional ground ice are distinguished. Landforms can be active, stabilized or ancient. One can find both single landforms and their combination. The classification is based on a significant amount of field studies and interpretation of remote sensing data. Mapping of the cryogenic-landslide landforms is suggested using the proposed classification and indication features. The classification is based on the experience obtained mainly in the north of West Siberia. Applying it to other regions may require additional studies.