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Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9–100 %), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 %, 58.1 %, and 69.7 % for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91–0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92–0.98 between Sentinel-2 and Landsat+Sentinel-2 mosaic) across all twelve study sites, testifying good quality mosaic results. Our results show that especially the results for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining Landsat and Sentinel-2 data we accomplished to create reliably high spatial resolution input mosaics for time series analyses. Our approach allows to apply a high temporal continuous time series analysis to northern high latitude permafrost regions for the first time, overcoming substantial data gaps, and assess permafrost disturbance dynamics on an annual scale across large regions with algorithms such as LandTrendr by deriving the location, timing and progression of permafrost thaw disturbances
Subsea permafrost is perennially cryotic earth material that lies offshore. Most submarine permafrost is relict terrestrial permafrost beneath the Arctic shelf seas, was inundated after the last glaciation, and has been warming and thawing ever since. It is a reservoir and confining layer for gas hydrates and has the potential to release greenhouse gases and affect global climate change. Furthermore, subsea permafrost thaw destabilizes coastal infrastructure. While numerous studies focus on its distribution and rate of thaw over glacial timescales, these studies have not been brought together and examined in their entirety to assess rates of thaw beneath the Arctic Ocean. In addition, there is still a large gap in our understanding of sub-aquatic permafrost processes on finer spatial and temporal scales. The degradation rate of subsea permafrost is influenced by the initial conditions upon submergence. Terrestrial permafrost that has already undergone warming, partial thawing or loss of ground ice may react differently to inundation by seawater compared to previously undisturbed ice-rich permafrost. Heat conduction models are sufficient to model the thaw of thick subsea permafrost from the bottom, but few studies have included salt diffusion for top-down chemical degradation in shallow waters characterized by mean annual cryotic conditions on the seabed. Simulating salt transport is critical for assessing degradation rates for recently inundated permafrost, which may accelerate in response to warming shelf waters, a lengthening open water season, and faster coastal erosion rates. In the nearshore zone, degradation rates are also controlled by seasonal processes like bedfast ice, brine injection, seasonal freezing under floating ice conditions and warm freshwater discharge from large rivers. The interplay of all these variables is complex and needs further research. To fill this knowledge gap, this thesis investigates sub-aquatic permafrost along the southern coast of the Bykovsky Peninsula in eastern Siberia. Sediment cores and ground temperature profiles were collected at a freshwater thermokarst lake and two thermokarst lagoons in 2017. At this site, the coastline is retreating, and seawater is inundating various types of permafrost: sections of ice-rich Pleistocene permafrost (Yedoma) cliffs at the coastline alternate with lagoons and lower elevation previously thawed and refrozen permafrost basins (Alases). Electrical resistivity surveys with floating electrodes were carried out to map ice-bearing permafrost and taliks (unfrozen zones in the permafrost, usually formed beneath lakes) along the diverse coastline and in the lagoons. Combined with the borehole data, the electrical resistivity results permit estimation of contemporary ice-bearing permafrost characteristics, distribution, and occasionally, thickness. To conceptualize possible geomorphological and marine evolutionary pathways to the formation of the observed layering, numerical models were applied. The developed model incorporates salt diffusion and seasonal dynamics at the seabed, including bedfast ice. Even along coastlines with mean annual non-cryotic boundary conditions like the Bykovsky Peninsula, the modelling results show that salt diffusion minimizes seasonal freezing of the seabed, leading to faster degradation rates compared to models without salt diffusion. Seasonal processes are also important for thermokarst lake to lagoon transitions because lagoons can generate cold hypersaline conditions underneath the ice cover. My research suggests that ice-bearing permafrost can form in a coastal lagoon environment, even under floating ice. Alas basins, however, may degrade more than twice as fast as Yedoma permafrost in the first several decades of inundation. In addition to a lower ice content compared to Yedoma permafrost, Alas basins may be pre-conditioned with salt from adjacent lagoons. Considering the widespread distribution of thermokarst in the Arctic, its integration into geophysical models and offshore surveys is important to quantify and understand subsea permafrost degradation and aggradation. Through numerical modelling, fieldwork, and a circum-Arctic review of subsea permafrost literature, this thesis provides new insights into sub-aquatic permafrost evolution in saline coastal environments.
Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9–100 %), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 %, 58.1 %, and 69.7 % for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91–0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92–0.98 between Sentinel-2 and Landsat+Sentinel-2 mosaic) across all twelve study sites, testifying good quality mosaic results. Our results show that especially the results for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining Landsat and Sentinel-2 data we accomplished to create reliably high spatial resolution input mosaics for time series analyses. Our approach allows to apply a high temporal continuous time series analysis to northern high latitude permafrost regions for the first time, overcoming substantial data gaps, and assess permafrost disturbance dynamics on an annual scale across large regions with algorithms such as LandTrendr by deriving the location, timing and progression of permafrost thaw disturbances