Glacial lakes (GLs), a vital link between the hydrosphere and the cryosphere, participate in the local hydrological process, and their interannual dynamic evolution is an objective reflection and an indicator of regional climate change. The complex terrain and climatic conditions in mountainous areas where GLs are located make it difficult to employ conventional remote sensing observation means to obtain stable, accurate, and comprehensive observation data. In view of this situation, this study presents an algorithm with a high generalization ability established by optimizing and improving a deep learning (DL) semantic segmentation network model for extracting GL contours from combined synthetic-aperture radar (SAR) amplitude and multispectral imagery data. The aim is to use the high penetrability and all-weather advantages of SAR to reduce the effects of cloud cover as well as to integrate the multiscale and detail-oriented advantages of multispectral data to facilitate accurate, quantitative extraction of GL contours. The accuracy and reliability of the model and algorithm were examined by employing them to extract the contours of GLs in a large region of south-eastern Tibet from Landsat 8 optical remote sensing images and Sentinel-1A amplitude images. In this study, the contours of a total 8262 GLs in south-eastern Tibet were extracted. These GLs were distributed predominantly at altitudes of 4000–5500 m. Only 17.4% of these GLs were greater than 0.1 km2 in size, while a large number of small GLs made up the majority. Through analysis and validation, the proposed method was found highly capable of distinguishing rivers and lakes and able to effectively reduce the misidentification and extraction of rivers. With the DL model based on combined optical and SAR images, the intersection-over-union (IoU) score increased by 0.0212 (to 0.6207) on the validation set and by 0.038 (to 0.6397) on the prediction set. These validation data sufficiently demonstrate the efficacy of the model and algorithm. The technical means employed in this study as well as the results and data obtained can provide a reference for research and application expansion in related fields.

Mechanical processes operating on the slope surface or at depth control the dynamics of alpine landforms and hold critical information of their geomorphological characteristics, yet they often lack systematic quantification and in‐depth interpretation. This study aims to address a long‐standing issue concerning geomorphological classification from a kinematic perspective. A group of periglacial landforms consisting of several lobes were discovered in the East Kunlun Mountains of China 30 years ago but were ambiguously classified as rock glaciers and later as gelifluction deposits. Here, we use satellite Interferometric Synthetic Aperture Radar to quantitatively characterize the spatial and temporal changes of the surface movement of these landforms. We observe that: (1) its 17 lobes show a pattern of landform‐scale and uniform surface movement, especially during May to October; (2) the lobes move at a spatial mean downslope velocity of 10 to 60 cm/yr and a maximum velocity as high as 100 cm/yr in summer; (3) the landforms are nearly inactive from winter to late spring. Based on these observations, we postulate that the movement of the lobes are driven by deep‐seated permafrost creep which typically occurs in rock glaciers. The debris of Lobe No.4 is composed of both boulders and pebbles supported by fine‐grained matrix generated from the in situ weathering process. It develops a talus‐like oversteepened front around 40° and a convex transverse profile perpendicular to the creep direction, which are also characteristic features of a rock glacier. Piecing these observations together, we identify Lobe No.4 as a debris‐mantled‐slope‐connected rock glacier, with the gelifluction process occurring on the surface as small‐scale and discrete events. © 2020 John Wiley & Sons, Ltd.

No abstract

Abstract. Topographic development via paraglacial slope failure (PSF) represents a complex interplay between geological structure, climate, and glacial denudation. Southeastern Tibet has experienced amongst the highest rates of ice mass loss in High Mountain Asia in recent decades, but few studies have focused on the implications of this mass loss on the stability of paraglacial slopes. We used repeat satellite- and unpiloted aerial vehicle (UAV)-derived imagery between 1990 and 2020 as the basis for mapping PSFs from slopes adjacent to Hailuogou Glacier (HLG), a 5 km long monsoon temperate valley glacier in the Mt. Gongga region. We observed recent lowering of the glacier tongue surface at rates of up to 0.88 m a−1 in the period 2000 to 2016, whilst overall paraglacial bare ground area (PBGA) on glacier-adjacent slopes increased from 0.31 ± 0.27 km2 in 1990 to 1.38 ± 0.06 km2 in 2020. Decadal PBGA expansion rates were ∼ 0.01 km2 a−1, 0.02 km2 a−1, and 0.08 km2 in the periods 1990–2000, 2000–2011, and 2011–2020 respectively, indicating an increasing rate of expansion of PBGA. Three types of PSFs, including rockfalls, sediment-mantled slope slides, and headward gully erosion, were mapped, with a total area of 0.75 ± 0.03 km2 in 2020. South-facing valley slopes (true left of the glacier) exhibited more destabilization (56 % of the total PSF area) than north-facing (true right) valley slopes (44 % of the total PSF area). Deformation of sediment-mantled moraine slopes (mean 1.65–2.63 ± 0.04 cm d−1) and an increase in erosion activity in ice-marginal tributary valleys caused by a drop in local base level (gully headward erosion rates are 0.76–3.39 cm d−1) have occurred in tandem with recent glacier downwasting. We also observe deformation of glacier ice, possibly driven by destabilization of lateral moraine, as has been reported in other deglaciating mountain glacier catchments. The formation, evolution, and future trajectory of PSFs at HLG (as well as other monsoon-dominated deglaciating mountain areas) are related to glacial history, including recent rapid downwasting leading to the exposure of steep, unstable bedrock and moraine slopes, and climatic conditions that promote slope instability, such as very high seasonal precipitation and seasonal temperature fluctuations that are conducive to freeze–thaw and ice segregation processes.

No abstract