@misc{ZwiebackKokeljGuentheretal.2018, author = {Zwieback, Simon and Kokelj, Steven V. and G{\"u}nther, Frank and Boike, Julia and Grosse, Guido and Hajnsek, Irena}, title = {Sub-seasonal thaw slump mass wasting is not consistently energy limited at the landscape scale}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {926}, issn = {1866-8372}, doi = {10.25932/publishup-44568}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-445688}, pages = {549 -- 564}, year = {2018}, abstract = {Predicting future thaw slump activity requires a sound understanding of the atmospheric drivers and geomorphic controls on mass wasting across a range of timescales. On sub-seasonal timescales, sparse measurements indicate that mass wasting at active slumps is often limited by the energy available for melting ground ice, but other factors such as rainfall or the formation of an insulating veneer may also be relevant. To study the sub-seasonal drivers, we derive topographic changes from single-pass radar interferometric data acquired by the TanDEM-X satellites. The estimated elevation changes at 12m resolution complement the commonly observed planimetric retreat rates by providing information on volume losses. Their high vertical precision (around 30 cm), frequent observations (11 days) and large coverage (5000 km(2)) allow us to track mass wasting as drivers such as the available energy change during the summer of 2015 in two study regions. We find that thaw slumps in the Tuktoyaktuk coastlands, Canada, are not energy limited in June, as they undergo limited mass wasting (height loss of around 0 cm day 1) despite the ample available energy, suggesting the widespread presence of early season insulating snow or debris veneer. Later in summer, height losses generally increase (around 3 cm day 1), but they do so in distinct ways. For many slumps, mass wasting tracks the available energy, a temporal pattern that is also observed at coastal yedoma cliffs on the Bykovsky Peninsula, Russia. However, the other two common temporal trajectories are asynchronous with the available energy, as they track strong precipitation events or show a sudden speed-up in late August respectively. The observed temporal patterns are poorly related to slump characteristics like the headwall height. The contrasting temporal behaviour of nearby thaw slumps highlights the importance of complex local and temporally varying controls on mass wasting.}, language = {en} } @misc{SchirrmeisterBobrovRaschkeetal.2018, author = {Schirrmeister, Lutz and Bobrov, Anatoly and Raschke, Elena and Herzschuh, Ulrike and Strauss, Jens and Pestryakova, Luidmila Agafyevna and Wetterich, Sebastian}, title = {Late Holocene ice-wedge polygon dynamics in northeastern Siberian coastal lowlands}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {719}, issn = {1866-8372}, doi = {10.25932/publishup-42660}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426603}, pages = {19}, year = {2018}, abstract = {Ice-wedge polygons are common features of northeastern Siberian lowland periglacial tundra landscapes. To deduce the formation and alternation of ice-wedge polygons in the Kolyma Delta and in the Indigirka Lowland, we studied shallow cores, up to 1.3 m deep, from polygon center and rim locations. The formation of well-developed low-center polygons with elevated rims and wet centers is shown by the beginning of peat accumulation, increased organic matter contents, and changes in vegetation cover from Poaceae-, Alnus-, and Betula-dominated pollen spectra to dominating Cyperaceae and Botryoccocus presence, and Carex and Drepanocladus revolvens macro-fossils. Tecamoebae data support such a change from wetland to open-water conditions in polygon centers by changes from dominating eurybiontic and sphagnobiontic to hydrobiontic species assemblages. The peat accumulation indicates low-center polygon formation and started between 2380 +/- 30 and 1676 +/- 32 years before present (BP) in the Kolyma Delta. We recorded an opposite change from open-water to wetland conditions because of rim degradation and consecutive high-center polygon formation in the Indigirka Lowland between 2144 +/- 33 and 1632 +/- 32 years BP. The late Holocene records of polygon landscape development reveal changes in local hydrology and soil moisture.}, language = {en} } @misc{RungeGrosse2019, author = {Runge, Alexandra and Grosse, Guido}, title = {Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {767}, issn = {1866-8372}, doi = {10.25932/publishup-43866}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-438660}, pages = {29}, year = {2019}, abstract = {The Arctic-Boreal regions experience strong changes of air temperature and precipitation regimes, which affect the thermal state of the permafrost. This results in widespread permafrost-thaw disturbances, some unfolding slowly and over long periods, others occurring rapidly and abruptly. Despite optical remote sensing offering a variety of techniques to assess and monitor landscape changes, a persistent cloud cover decreases the amount of usable images considerably. However, combining data from multiple platforms promises to increase the number of images drastically. We therefore assess the comparability of Landsat-8 and Sentinel-2 imagery and the possibility to use both Landsat and Sentinel-2 images together in time series analyses, achieving a temporally-dense data coverage in Arctic-Boreal regions. We determined overlapping same-day acquisitions of Landsat-8 and Sentinel-2 images for three representative study sites in Eastern Siberia. We then compared the Landsat-8 and Sentinel-2 pixel-pairs, downscaled to 60 m, of corresponding bands and derived the ordinary least squares regression for every band combination. The acquired coefficients were used for spectral bandpass adjustment between the two sensors. The spectral band comparisons showed an overall good fit between Landsat-8 and Sentinel-2 images already. The ordinary least squares regression analyses underline the generally good spectral fit with intercept values between 0.0031 and 0.056 and slope values between 0.531 and 0.877. A spectral comparison after spectral bandpass adjustment of Sentinel-2 values to Landsat-8 shows a nearly perfect alignment between the same-day images. The spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to Landsat-8 very well in Eastern Siberian Arctic-Boreal landscapes. After spectral adjustment, Landsat and Sentinel-2 data can be used to create temporally-dense time series and be applied to assess permafrost landscape changes in Eastern Siberia. Remaining differences between the sensors can be attributed to several factors including heterogeneous terrain, poor cloud and cloud shadow masking, and mixed pixels.}, language = {en} } @misc{RungeGrosse2020, author = {Runge, Alexandra and Grosse, Guido}, title = {Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1009}, issn = {1866-8372}, doi = {10.25932/publishup-48031}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-480317}, pages = {25}, year = {2020}, abstract = {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}, language = {en} } @misc{LaraNitzeGrosseetal.2018, author = {Lara, Mark J. and Nitze, Ingmar and Große, Guido and McGuire, David}, title = {Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1035}, issn = {1866-8372}, doi = {10.25932/publishup-45987}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-459875}, pages = {12}, year = {2018}, abstract = {Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10-100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999-2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.}, language = {en} } @misc{LaraNitzeGrosseetal.2018, author = {Lara, Mark J. and Nitze, Ingmar and Grosse, Guido and Martin, Philip and McGuire, A. David}, title = {Reduced arctic tundra productivity linked with landform and climate change interactions}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {550}, issn = {1866-8372}, doi = {10.25932/publishup-42313}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423132}, pages = {10}, year = {2018}, abstract = {Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) using the Landsat archive (1999-2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.}, language = {en} } @misc{DvornikovLeibmanHeimetal.2018, author = {Dvornikov, Yury and Leibman, Marina and Heim, Birgit and Bartsch, Annett and Herzschuh, Ulrike and Skorospekhova, Tatiana and Fedorova, Irina and Khomutov, Artem and Widhalm, Barbara and Gubarkov, Anatoly and R{\"o}ßler, Sebastian}, title = {Terrestrial CDOM in lakes of Yamal Peninsula}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1333}, issn = {1866-8372}, doi = {10.25932/publishup-45972}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-459720}, pages = {21}, year = {2018}, abstract = {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 (S300-500) in lakes using field sampling and optical remote sensing data for an area of 350 km(2) 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()(CDOM) data from 18 lakes sampled in the field to 356 lakes in the study area (model R-2 = 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()(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 (R-2 = 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.}, language = {en} }