Flow velocities were measured on the Plator rock glacier in the Central Italian Alps using a correlation image analysis algorithm on orthophotos acquired by drones between the years 2016 and 2020. The spatial patterns of surface creep were then compared to the Bulk Creep Factor (BCF) spatial variability to interpret the rock glacier dynamics as a function of material properties and geometry. The rock glacier showed different creep rates in the rooting zone (0.40–0.90 m/y) and in the frontal zone (>4.0 m/y). Close to the rock glacier front, the BCF assumed the highest values, reaching values typical of rock glaciers experiencing destabilisation. Conversely, in the rooting zone the small rates corresponded to lowest BCFs, about five times smaller than in the frontal zone. The Plator rock glacier revealed a substantial advancement from 1981 to 2020 and distinct geomorphological features typical of rock glaciers exhibiting destabilising processes. Given the fast-moving phase, the advancement of both the front line and the front toe of the rock glacier, and the contrasting spatial distribution in the BCFs, the Plator could be considered a destabilised rock glacier.

Climate change is reducing the extent of cold aquatic habitats and their unique biodiversity in mountain areas. However, a variety of cold rocky landforms (CRLs) are thermally buffered and feed cold springs (<2 °C) that may represent climate refugia for cold-adapted organisms. These landforms, hitherto overlooked by freshwater research, include rock glaciers, debris-covered glaciers, talus slopes, protalus ramparts, and young moraines. Here, we investigated the warm-season water temperature of 228 springs from clean (ice) glaciers, CRLs, and reference slopes (not sourced by any of these features) in 13 mountain ranges of Europe, South America, and North America. Only springs from glaciers (90%) and CRLs (45%) had average stream temperatures below the thermal optimum for coldwater organisms of 2 °C. Springs fed by CRLs were 3 °C–5 °C (up to 9 °C) colder than those from nearby reference slopes. In general, cold springs were rarer in Mediterranean/semi-arid climates than in temperate and sub-polar climates. Landforms comprising barren and coarse rocky surfaces or ice/rock mix, having a simple or absent soil/vegetation structure, and higher likelihood of permafrost more often supported cold springs. When water temperatures were compared to air temperature, most CRL springs were thermally buffered against warm periods, cumulative heat, and daily temperature fluctuations. With cold conditions maintained in a variety of climates and mountain landscapes, CRL springs in mountains likely have high conservation value. We call for integrated ecological and hydrological research for these ecosystems, aimed at understanding their potential as climate refugia.

As a consequence of atmospheric warming, high-altitude periglacial and glacial environments exhibit clear signs of cryosphere degradation, and the Alps serve as a natural laboratory for studying the primary effects on permafrost-related features. Our research in South Tyrol, northeastern Italy, aimed to develop an updated classification system, based on remote sensing data and statistical models, for rock glacier activity, categorizing it as active, transitional, or relict according to the new Rock Glacier Inventories and Kinematic (RGIK) guidelines. While the current regional inventory includes activity attributes based on morphological observations and differential interferometric synthetic aperture radar (DInSAR) coherence, it lacks a comprehensive classification that also considers climatic drivers, displacement rates, and morphometric parameters. To fill this gap, we utilized the Alaska Satellite Facility's interferometric synthetic aperture radar (InSAR) cloud computing, employing the Small Baseline Subset (SBAS) and Miami InSAR time-series software in Python (MintPy) algorithms to extract velocity data for each rock glacier investigated in this study. Additionally, we analysed geomorphological and climatic maps derived from in situ and remote sensing data to obtain descriptive parameters influencing rock glacier development and activity. From a wide range of potential variables, we selected eight key predictors, representing physical (e.g. temperature), morphological (e.g. roughness), and dynamic attributes (e.g. velocity and coherence indicators). These predictors were integrated in a multiclass generalized additive model (GAM) classifier to categorize the mapped landforms. Applying this model to the entire dataset (achieving an area under the curve (AUC) over 0.9) allowed us to address gaps in previous classification methods and provided activity attributes for previously unclassified rock glaciers, along with associated uncertainty values. Our approach enhanced the previous classification, leaving only 3.5 % of features unclassified compared to 13 % in morphological classification and 18.5 % in the DInSAR-based method. The results revealed a predominance of relict features (∼75 %) and a smaller number of active ones (∼10 %). The result of the distribution of active, transitional, and relict classes suggests that the transition from active to relict states is not direct. Instead, an intermediate transitional phase is commonly observed. This comprehensive approach refines the categorization of mapped features and improves our understanding of the factors influencing rock glacier activity in the alpine environment in South Tyrol.

Time series of rock glaciers (RG) movements in the European Alps indicate an acceleration in permafrost creep in recent decades in relation to an increase in ground temperatures and water content. In this work, we analyse the geomorphological changes of an active RG located in the Western European Alps, in Valtournenche Valley (AO, Italy).Five photogrammetric surveys were realized on the RG between 2015 to 2019, using a senseFly eBee RTK and a DJI Phantom 4 UAVs. During UAV acquisitions, 21 ground control points were placed all over the study area and their coordinates were measured in GNSS RTK mode, for georeferencing each photogrammetric model. The monitoring activity also includes GNSS campaigns, carried out annually since 2012, which provides high accurate surface displacement measurements but limited to 54 points. In addition, in July 2015 two Electrical Resistivity Tomography profiles were performed, with the Wenner-Schlumberger configuration, to identify the internal structure and potential ground ice content inside the main body of the RG.The Structure-from-Motion technique was used to generate orthophotos and digital surface models with a resolution of 5 cm/px. Successively, we estimated the three-dimensional change of the surface displacements (surface lowering and accumulation processes) of the RG comparing pairs of point clouds, using the Multiscale Model to Model Cloud Comparison (M3C2 plug-in). A first evaluation of the horizontal surface velocity was computed identifying corresponding features manually on the orthophotos through time and a second assessment was performed based on repeated GNSS campaigns. Surface velocity obtained by orthophotos manual identifications is validated against repeated GNSS measurements. The analysis shows a good correlation at all magnitudes with a R2 equal to 0.988 and RMSE of 26 cm.The RG shows a clear distinction in creep dynamics between a faster western part (values up to 1.8 m/y) and a slower eastern part, with values below 0.1 m/y in the most upstream part. Considering the period 2012-2020, maximum peak of surface velocity is reached in 2015, followed by a velocity decrease until 2017-2018 when the smallest movements are recorded. However, the following two years (2018-2019 and 2019-2020) are marked by a gradual increase in surface horizontal velocity. The absence of significant of any significant movement in the upstream part is related to the lack of permafrost consecutive to the development and advance of a local glacier during the Little Ice Age. The slower eastern part is almost gently inclined and corresponds to a currently degrading part of the RG, with an ice melt-induced subsidence of up to 5 cm/year. The faster area is also the steepest, where the driving stress is also the largest. The presence of the frozen ground at depth, probably its structure and thermal state, but also the topographical settings are the main factors explaining the current RG flow pattern.

As a consequence of climate warming, high-altitude periglacial and glacial environments exhibit the clearest signs of cryosphere degradation, and the Alps serve as a natural laboratory for studying the primary effects on permafrost-related features. Our research in South Tyrol, North-East Italy, aimed to develop an updated classification system for rock glaciers activity, based on remote sensing data and statistical models, with the aim of categorizing them as active, transitional, or relict according to the recent RGIK guidelines. Since the current regional inventory includes activity attributes based only on morphological observations and differential SAR interferometry (DInSAR) coherence, it lacks a comprehensive definition integrating climatic drivers, displacement rates, and morphometric parameters. To address this, we utilized the Alaska Satellite Facility's InSAR cloud computing, employing small baseline subset (SBAS) approach and MintPy algorithms to extract velocity data for each rock glacier in South Tyrol. Additionally, we analyzed geomorphological and climatic maps derived from in-situ and remote sensing data to obtain descriptive parameters influencing rock glaciers development and activity. From a wide range of potential variables, we selected eight key predictors, representing physical (e.g. temperature), morphological (e.g. roughness), and dynamic (e.g. velocity and coherence indicators) attributes. These predictors were successively integrated in a multiclass generalized additive mixing model (GAM) classifier to categorize the landforms. Applying this model to the entire dataset (achieving an AUC over 0.9) allowed us to address gaps in previous classification methods and provided activity attributes for previously unclassified rock glaciers, along with associated uncertainty values. Our approach improved classification accuracy, leaving only 3.5 % of features unclassified compared to 13 % in morphological classification and 18.5 % in DInSAR-based methods. The results revealed a predominance of relict features (~75 %) and a smaller number of active ones (~10 %). The distribution of active, transitional, and relict classes suggests that the transition from active to relict states is not a direct process. Instead, an intermediate transitional phase is commonly observed. This comprehensive approach refines the categorization of mapped features and improves our understanding of the factors influencing rock glaciers activity in alpine environment.