Geophysical techniques can be used to examine the spatial distribution of subsurface geophysical properties to delineate horizontally and vertically the active layer, permafrost and taliks. Spatial and temporal changes in subsurface geophysical properties due to permafrost cooling, warming, aggradation or degradation can also be assessed through geophysical monitoring. This paper reviews the geophysical methods most frequently applied in mountain and arctic/subarctic lowland permafrost investigations. Key results and recommendations based on the analysis of the applicability and reliability of different geophysical techniques for permafrost studies are summarised. Emphasis is put on the tomographic capabilities of geophysical methods. Recent advances in application and data interpretation are shown in relation to five case studies, and future perspectives are highlighted. Copyright © 2008 John Wiley & Sons, Ltd.

An overview is given of the relatively short history, important issues and primary challenges of research on permafrost in cold mountain regions. The systematic application of diverse approaches and technologies contributes to a rapidly growing knowledge base about the existence, characteristics and evolution in time of perennially frozen ground at high altitudes and on steep slopes. These approaches and technologies include (1) drilling, borehole measurement, geophysical sounding, photogrammetry, laser altimetry, GPS/SAR surveying, and miniature temperature data logging in remote areas that are often difficult to access, (2) laboratory investigations (e.g. rheology and stability of ice-rock mixtures), (3) analyses of digital terrain information, (4) numerical simulations (e.g. subsurface thermal conditions under complex topography) and (5) spatial models (e.g. distribution of permafrost where surface and microclimatic conditions are highly variable spatially). A sound knowledge base and improved understanding of governing processes are urgently needed to deal effectively with the consequences of climate change on the evolution of mountain landscapes and, especially, of steep mountain slope hazards as the stabilizing permafrost warms and degrades. Interactions between glaciers and permafrost in cold mountain regions have so far received comparatively little attention and need more systematic investigation. ABSTRACT. An overview is given of the relatively short history, important issues and primary challenges of research on permafrost in cold mountain regions. The systematic application of diverse approaches and technologies contributes to a rapidly growing knowledge base about the existence, characteristics and evolution in time of perennially frozen ground at high altitudes and on steep slopes. These approaches and technologies include (1) drilling, borehole measurement, geophysical sounding, photogrammetry, laser altimetry, GPS/SAR surveying, and miniature temperature data logging in remote areas that are often difficult to access, (2) laboratory investigations (e.g. rheology and stability of icerock mixtures), (3) analyses of digital terrain information, (4) numerical simulations (e.g. subsurface thermal conditions under complex topography) and (5) spatial models (e.g. distribution of permafrost where surface and microclimatic conditions are highly variable spatially). A sound knowledge base and improved understanding of governing processes are urgently needed to deal effectively with the consequences of climate change on the evolution of mountain landscapes and, especially, of steep mountain slope hazards as the stabilizing permafrost warms and degrades. Interactions between glaciers and permafrost in cold mountain regions have so far received comparatively little attention and need more systematic investigation.

Sea level rise contribution from the Antarctic ice sheet is influenced by changes in glacier and ice shelf front position. Still, little is known about seasonal glacier and ice shelf front fluctuations as the manual delineation of calving fronts from remote sensing imagery is very time-consuming. The major challenge of automatic calving front extraction is the low contrast between floating glacier and ice shelf fronts and the surrounding sea ice. Additionally, in previous decades, remote sensing imagery over the often cloud-covered Antarctic coastline was limited. Nowadays, an abundance of Sentinel-1 imagery over the Antarctic coastline exists and could be used for tracking glacier and ice shelf front movement. To exploit the available Sentinel-1 data, we developed a processing chain allowing automatic extraction of the Antarctic coastline from Seninel-1 imagery and the creation of dense time series to assess calving front change. The core of the proposed workflow is a modified version of the deep learning architecture U-Net. This convolutional neural network (CNN) performs a semantic segmentation on dual-pol Sentinel-1 data and the Antarctic TanDEM-X digital elevation model (DEM). The proposed method is tested for four training and test areas along the Antarctic coastline. The automatically extracted fronts deviate on average 78 m in training and 108 m test areas. Spatial and temporal transferability is demonstrated on an automatically extracted 15-month time series along the Getz Ice Shelf. Between May 2017 and July 2018, the fronts along the Getz Ice Shelf show mostly an advancing tendency with the fastest moving front of DeVicq Glacier with 726 ± 20 m/yr.

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