Ground subsidence monitoring by Synthetic Aperture Radar interferometry (InSAR) over Arctic permafrost areas is largely limited by long revisit intervals, which can lead to signal decorrelation. Recent satellite missions such as COSMO-Skymed (X-band) and Sentinel-1 (C-band) have comparably short time intervals of a few days. We analyze dense records of COSMO-Skymed from 2013 and 2016 and of Sentinel-1 from 2016, 2017, and 2018 for the unfrozen period over central Yamal (Russia). These years were distinct in environmental conditions and 2016 in particular was unusually warm. We evaluate the InSAR-derived displacement with in situ subsidence records, active-layer thickness measurements, borehole temperature records, meteorological data, C-band scatterometer records, and a land-cover classification based on Sentinel-1 and -2 data. Our results indicate that a comparison of seasonal thaw evolution between years is feasible after accounting for the early thaw data gap in InSAR time series (as a result of snow cover) through an assessment with respect to degree-days of thawing. Average rates of subsidence agree between in situ and Sentinel-1 (corrected for viewing geometry), with 3.9 mm and 4.3 mm per 100 degree-days of thaw at the test site. X-band and C-band records agree well with each other, including seasonal evolution of subsidence. The average displacement is more than twice in magnitude at the active-layer monitoring test site in 2016 compared to the other years. We further demonstrate that InSAR displacement can not only provide information on the magnitude of ground thaw but also on soil properties through analyses of seasonal evolution in extreme years.

Synthetic aperture radar (SAR) applications often require normalization to a common incidence angle. Angular signatures of radar backscatter depend on surface roughness and vegetation cover, and thus differ, from location to location. Comprehensive reference datasets are therefore required in heterogeneous landscapes. Multiple acquisitions from overlapping orbits with sufficient incidence angle range are processed in order to obtain parameters of the location specific normalization function. We propose a simpler method for C-band data, using single scenes only. It requires stable dielectric properties (no variations of liquid water content). This method is therefore applicable for frozen conditions. Winter C-band data have been shown of high value for a number of applications in high latitudes before. In this paper we explore the relationship of incidence angle and Sentinel-1 backscatter across the tundra to boreal transition zone. A linear relationship (coefficient of determination R ${}^2$ = 0.64) can be found between backscatter and incidence angle dependence (slope of normalization function) as determined by multiple acquisitions on a pixel by pixel basis for typical land cover classes in these regions. This allows a simplified normalization and thus reduced processing effort for applications over larger areas.

The active layer above the permafrost, which seasonally thaws during summer, is an important parameter for monitoring the state of permafrost. Its thickness is typically measured locally, but a range of methods which utilize information from satellite data exist. Mostly, the normalized difference vegetation index (NDVI) obtained from optical satellite data is used as a proxy. The applicability has been demonstrated mostly for shallow depths of active-layer thickness (ALT) below approximately 70 cm. Some permafrost areas including central Yamal are, however, characterized by larger ALT. Surface properties including vegetation structure are also represented by microwave backscatter intensity. So far, the potential of such data for estimating ALT has not been explored. We therefore investigated the relationship between ALT and X-band synthetic aperture radar (SAR) backscatter of TerraSAR-X (averages for 10 × 10 m window) in order to examine the possibility of delineating ALT with continuous and larger spatial coverage in this area and compare it to the already-established method of using NDVI from Landsat (30 m). Our results show that the mutual dependency of ALT and TerraSAR-X backscatter on land cover types suggests a connection of both parameters. A range of 5 dB can be observed for an ALT range of 100 cm (40–140 cm), and an R² of 0.66 has been determined over the calibration sites. An increase of ALT with increasing backscatter can be determined. The root mean square error (RMSE) over a comparably heterogeneous validation site with maximum ALT of > 150 cm is 20 cm. Deviations are larger for measurement locations with mixed vegetation types (especially partial coverage by cryptogam crust) with respect to the spatial resolution of the satellite data.

This study assesses the vulnerability of Arctic coastal settlements and infrastructure to coastal erosion, Sea‐Level Rise (SLR) and permafrost warming. For the first time, we characterize coastline retreat consistently along permafrost coastal settlements at the regional scale for the Northern Hemisphere. We provide a new method to automatically derive long‐term coastline change rates for permafrost coasts. In addition, we identify the total number of coastal settlements and associated infrastructure that could be threatened by marine and terrestrial changes using remote sensing techniques. We extended the Arctic Coastal Infrastructure data set (SACHI) to include road types, airstrips, and artificial water reservoirs. The analysis of coastline, Ground Temperature (GT) and Active Layer Thickness (ALT) changes from 2000 to 2020, in addition with SLR projection, allowed to identify exposed settlements and infrastructure for 2030, 2050, and 2100. We validated the SACHI‐v2, GT and ALT data sets through comparisons with in‐situ data. 60% of the detected infrastructure is built on low‐lying coast (10 m a.s.l). The results show that in 2100, 45% of all coastal settlements will be affected by SLR and 21% by coastal erosion. On average, coastal permafrost GT is increasing by 0.8°C per decade, and ALT is increasing by 6 cm per decade. In 2100, GT will become positive at 77% of the built infrastructure area. Our results highlight the circumpolar and international amplitude of the problem and emphasize the need for immediate adaptation measures to current and future environmental changes to counteract a deterioration of living conditions and ensure infrastructure sustainability.

Earth observation offers a variety of techniques for monitoring and characterizing geomorphic processes in high mountain environments. Terrestrial laserscanning and unmanned aerial vehicles provide very high resolution data with high accuracy. Automatic cameras have become a valuable source of information—mostly in a qualitative manner—in recent years. The availability of satellite data with very high revisiting time has gained momentum through the European Space Agency’s Sentinel missions, offering new application potential for Earth observation. This paper reviews the status of recent techniques such as terrestrial laserscanning, remote sensed imagery, and synthetic aperture radar in monitoring high mountain environments with a particular focus on the impact of new platforms such as Sentinel-1 and -2 as well as unmanned aerial vehicles. The study area comprises the high mountain glacial environment at the Pasterze Glacier, Austria. The area is characterized by a highly dynamic geomorphological evolution and by being subject to intensive scientific research as well as long-term monitoring. We primarily evaluate landform classification and process characterization for: (i) the proglacial lake; (ii) icebergs; (iii) the glacier river; (iv) valley-bottom processes; (v) slope processes; and (vi) rock wall processes. We focus on assessing the potential of every single method both in spatial and temporal resolution in characterizing different geomorphic processes. Examples of the individual techniques are evaluated qualitatively and quantitatively in the context of: (i) morphometric analysis; (ii) applicability in high alpine regions; and (iii) comparability of the methods among themselves. The final frame of this article includes considerations on scale dependent process detectability and characterization potentials of these Earth observation methods, along with strengths and limitations in applying these methods in high alpine regions.

In this study, we analyze interactions in lake and lake catchment systems of a continuous permafrost area. We assessed colored dissolved organic matter (CDOM) absorption at 440 nm (a(440)_CDOM) and absorption slope (S_300–500) in lakes using field sampling and optical remote sensing data for an area of 350 km² in Central Yamal, Siberia. Applying a CDOM algorithm (ratio of green and red band reflectance) for two high spatial resolution multispectral GeoEye-1 and Worldview-2 satellite images, we were able to extrapolate the a(λ)_CDOM data from 18 lakes sampled in the field to 356 lakes in the study area (model R² = 0.79). Values of a(440)_CDOM in 356 lakes varied from 0.48 to 8.35 m⁻¹ with a median of 1.43 m⁻¹. This a(λ)_CDOM dataset was used to relate lake CDOM to 17 lake and lake catchment parameters derived from optical and radar remote sensing data and from digital elevation model analysis in order to establish the parameters controlling CDOM in lakes on the Yamal Peninsula. Regression tree model and boosted regression tree analysis showed that the activity of cryogenic processes (thermocirques) in the lake shores and lake water level were the two most important controls, explaining 48.4% and 28.4% of lake CDOM, respectively (R² = 0.61). Activation of thermocirques led to a large input of terrestrial organic matter and sediments from catchments and thawed permafrost to lakes (n = 15, mean a(440)_CDOM = 5.3 m⁻¹). Large lakes on the floodplain with a connection to Mordy-Yakha River received more CDOM (n = 7, mean a(440)_CDOM = 3.8 m⁻¹) compared to lakes located on higher terraces.