TY - GEN A1 - Klein, Konstantin P. A1 - Lantuit, Hugues A1 - Heim, Birgit A1 - Doxaran, David A1 - Juhls, Bennet A1 - Nitze, Ingmar A1 - Walch, Daniela A1 - Poste, Amanda A1 - Søreide, Janne E. T1 - The Arctic Nearshore Turbidity Algorithm (ANTA) BT - A multi sensor turbidity algorithm for Arctic nearshore environments T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - The Arctic is greatly impacted by climate change. The increase in air temperature drives the thawing of permafrost and an increase in coastal erosion and river discharge. This leads to a greater input of sediment and organic matter into coastal waters, which substantially impacts the ecosystems by reducing light transmission through the water column and altering the biogeochemistry, but also the subsistence economy of local people, and changes in climate because of the transformation of organic matter into greenhouse gases. Yet, the quantification of suspended sediment in Arctic coastal and nearshore waters remains unsatisfactory due to the absence of dedicated algorithms to resolve the high loads occurring in the close vicinity of the shoreline. In this study we present the Arctic Nearshore Turbidity Algorithm (ANTA), the first reflectance-turbidity relationship specifically targeted towards Arctic nearshore waters that is tuned with in-situ measurements from the nearshore waters of Herschel Island Qikiqtaruk in the western Canadian Arctic. A semi-empirical model was calibrated for several relevant sensors in ocean color remote sensing, including MODIS, Sentinel 3 (OLCI), Landsat 8 (OLI), and Sentinel 2 (MSI), as well as the older Landsat sensors TM and ETM+. The ANTA performed better with Landsat 8 than with Sentinel 2 and Sentinel 3. The application of the ANTA to Sentinel 2 imagery that matches in-situ turbidity samples taken in Adventfjorden, Svalbard, shows transferability to nearshore areas beyond Herschel Island Qikiqtaruk. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1250 KW - Ocean color remote sensing KW - Turbidity retrieval KW - Nearshore zone KW - Arctic Ocean Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-553692 SN - 1866-8372 IS - 1250 ER - TY - GEN A1 - Dvornikov, Yury A1 - Leibman, Marina A1 - Heim, Birgit A1 - Bartsch, Annett A1 - Herzschuh, Ulrike A1 - Skorospekhova, Tatiana A1 - Fedorova, Irina A1 - Khomutov, Artem A1 - Widhalm, Barbara A1 - Gubarkov, Anatoly A1 - Rößler, Sebastian T1 - Terrestrial CDOM in lakes of Yamal Peninsula BT - Connection to lake and lake catchment properties T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1333 KW - CDOM KW - lakes KW - lake catchments KW - permafrost KW - Yamal KW - remote sensing data Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-459720 SN - 1866-8372 IS - 1333 ER - TY - GEN A1 - Stettner, Samuel A1 - Lantuit, Hugues A1 - Heim, Birgit A1 - Eppler, Jayson A1 - Roth, Achim A1 - Bartsch, Annett A1 - Rabus, Bernhard T1 - TerraSAR-X time series fill a gap in spaceborne snowmelt monitoring of small Arctic catchments BT - a case study on Qikiqtaruk (Herschel Island), Canada T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - The timing of snowmelt is an important turning point in the seasonal cycle of small Arctic catchments. The TerraSAR-X (TSX) satellite mission is a synthetic aperture radar system (SAR) with high potential to measure the high spatiotemporal variability of snow cover extent (SCE) and fractional snow cover (FSC) on the small catchment scale. We investigate the performance of multi-polarized and multi-pass TSX X-Band SAR data in monitoring SCE and FSC in small Arctic tundra catchments of Qikiqtaruk (Herschel Island) off the Yukon Coast in the Western Canadian Arctic. We applied a threshold based segmentation on ratio images between TSX images with wet snow and a dry snow reference, and tested the performance of two different thresholds. We quantitatively compared TSX- and Landsat 8-derived SCE maps using confusion matrices and analyzed the spatiotemporal dynamics of snowmelt from 2015 to 2017 using TSX, Landsat 8 and in situ time lapse data. Our data showed that the quality of SCE maps from TSX X-Band data is strongly influenced by polarization and to a lesser degree by incidence angle. VH polarized TSX data performed best in deriving SCE when compared to Landsat 8. TSX derived SCE maps from VH polarization detected late lying snow patches that were not detected by Landsat 8. Results of a local assessment of TSX FSC against the in situ data showed that TSX FSC accurately captured the temporal dynamics of different snow melt regimes that were related to topographic characteristics of the studied catchments. Both in situ and TSX FSC showed a longer snowmelt period in a catchment with higher contributions of steep valleys and a shorter snowmelt period in a catchment with higher contributions of upland terrain. Landsat 8 had fundamental data gaps during the snowmelt period in all 3 years due to cloud cover. The results also revealed that by choosing a positive threshold of 1 dB, detection of ice layers due to diurnal temperature variations resulted in a more accurate estimation of snow cover than a negative threshold that detects wet snow alone. We find that TSX X-Band data in VH polarization performs at a comparable quality to Landsat 8 in deriving SCE maps when a positive threshold is used. We conclude that TSX data polarization can be used to accurately monitor snowmelt events at high temporal and spatial resolution, overcoming limitations of Landsat 8, which due to cloud related data gaps generally only indicated the onset and end of snowmelt. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 689 KW - Snow Cover Extent (SCE) KW - TerraSAR-X KW - Landsat KW - wet snow KW - small Arctic catchments KW - satellite time series Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-426810 SN - 1866-8372 IS - 689 ER - TY - GEN A1 - Walther, Sophia A1 - Guanter, Luis A1 - Heim, Birgit A1 - Jung, Martin A1 - Duveiller, Gregory A1 - Wolanin, Aleksandra A1 - Sachs, Torsten T1 - Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - High-latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of the climate-sensitive tundra. Space-borne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render it highly challenging. Here, we conduct an extensive analysis of the timing of peak vegetation productivity as shown by satellite observations of complementary indicators of plant greenness and photosynthesis. We choose to focus on productivity during the peak of the growing season, as it importantly affects the total annual carbon uptake. The suite of indicators are as follows: (1) MODIS-based vegetation indices (VIs) as proxies for the fraction of incident photosynthetically active radiation (PAR) that is absorbed (fPAR), (2) VIs combined with estimates of PAR as a proxy of the total absorbed radiation (APAR), (3) sun-induced chlorophyll fluorescence (SIF) serving as a proxy for photosynthesis, (4) vegetation optical depth (VOD), indicative of total water content and (5) empirically upscaled modelled gross primary productivity (GPP). Averaged over the pan-Arctic we find a clear order of the annual peak as APAR ≦ GPP