Description: Abstract Waterbodies in the arctic permafrost zone are considered a major source of the greenhouse gas methane (CH4) in addition to CH4 emissions from arctic wetlands. However, the spatio-temporal variability of CH4 fluxes from waterbodies compli- cates spatial extrapolation of CH4 measurements from single waterbodies. There- fore, their contribution to the CH4 budget of the arctic permafrost zone is not yet well understood. Using the example of two study areas of 1,000 km2 each in the Mackenzie Delta, Canada, we approach this issue (i) by analyzing correlations on the landscape scale between numerous waterbodies and CH4 fluxes and (ii) by analyzing the influence of the spatial resolution of CH4 flux data on the detected relation- ships. A CH4 flux map with a resolution of 100 m was derived from two aircraft eddy-covariance campaigns in the summers of 2012 and 2013. We combined the CH4 flux map with high spatial resolution (2.5 m) waterbody maps from the Per- mafrost Region Pond and Lake Database and classified the waterbody depth based on Sentinel-1 SAR backscatter data. Subsequently, we reduced the resolution of the CH4 flux map to analyze if different spatial resolutions of CH4 flux data affected the detectability of relationships between waterbody coverage, number, depth, or size and the CH4 flux. We did not find consistent correlations between waterbody characteristics and the CH4 flux in the two study areas across the different resolu- tions. Our results indicate that waterbodies in permafrost landscapes, even if they seem to be emission hot spots on an individual basis or contain zones of above average emissions, do currently not necessarily translate into significant CH4 emis- sion hot spots on a regional scale, but their role might change in a warmer climate. KEYWORDS airborne eddy-covariance, Arctic, CH4, lakes, ponds, remote sensing, Sentinel-1, TerraSAR-X

Description: The high-latitude forest-tundra transitional zone is a region which is highly vulnerable to the current Arctic warming. The local changes accompanying expected northward migration of the treeline requires systematic monitoring. We focus on an area in the east of the Mackenzie Delta in Northwest Territories, Canada, which is characterised by patches of black spruce forest. We investigate the capability of TerraSAR-X / TanDEM-X bistatic constellation for the characterisation of these forest patches. Interferometric phase and coherence from seven image pairs were used to estimate tree height and density. We compare the SAR products with standard vegetation metrics from airborne LiDAR, such as vegetation height percentiles and vegetation ratio. The preliminary analysis shows a high agreement between SAR and LiDAR data.

Description: Low-land permafrost areas are subject to intense freeze-thaw cycles and characterized by remarkable surface displacement. We used Sentinel-1 SAR interferometry (InSAR) in order to analyse the summer surface displacement over four spots in the Arctic and Antarctica since 2015. Choosing floodplain or outcrop areas as the reference for the InSAR relative deformation measurements, we found maximum subsidence of about 3 to 10 cm during the thawing season with generally high spatial variability. Sentinel-1 time-series of interferograms with 6–12 day time intervals highlight that subsidence is often occurring rather quickly within roughly one month in early summer. Intercomparison of summer subsidence from Sentinel-1 in 2017 with TerraSAR-X in 2013 over part of the Lena River Delta (Russia) shows a high spatial agreement between both SAR systems. A comparison with in-situ measurements for the summer of 2014 over the Lena River Delta indicates a pronounced downward movement of several centimetres in both cases but does not reveal a spatial correspondence between InSAR and local in-situ measurements. For the reconstruction of longer time-series of deformation, yearly Sentinel-1 interferograms from the end of the summer were considered. However, in order to infer an effective subsidence of the surface through melting of excess ice layers over multi-annual scales with Sentinel-1, a longer observation time period is necessary.