TY - JOUR A1 - Coch, Caroline A1 - Juhls, Bennet A1 - Lamoureux, Scott F. A1 - Lafreniere, Melissa J. A1 - Fritz, Michael A1 - Heim, Birgit A1 - Lantuit, Hugues T1 - Comparisons of dissolved organic matter and its optical characteristics in small low and high Arctic catchments JF - Biogeosciences N2 - Climate change is affecting the rate of carbon cycling, particularly in the Arctic. Permafrost degradation through deeper thaw and physical disturbances results in the release of carbon dioxide and methane to the atmosphere and to an increase in lateral dissolved organic matter (DOM) fluxes. Whereas riverine DOM fluxes of the large Arctic rivers are well assessed, knowledge is limited with regard to small catchments that cover more than 40% of the Arctic drainage basin. Here, we use absorption measurements to characterize changes in DOM quantity and quality in a low Arctic (Herschel Island, Yukon, Canada) and a high Arctic (Cape Bounty, Melville Island, Nunavut, Canada) setting with regard to geographical differences, impacts of permafrost degradation, and rainfall events. We find that DOM quantity and quality is controlled by differences in vegetation cover and soil organic carbon content (SOCC). The low Arctic site has higher SOCC and greater abundance of plant material resulting in higher chromophoric dissolved organic matter (cDOM) and dissolved organic carbon (DOC) than in the high Arctic. DOC concentration and cDOM in surface waters at both sites show strong linear relationships similar to the one for the great Arctic rivers. We used the optical characteristics of DOM such as cDOM absorption, specific ultraviolet absorbance (SUVA), ultraviolet (UV) spectral slopes (S275-295), and slope ratio (SR) for assessing quality changes downstream, at base flow and storm flow conditions, and in relation to permafrost disturbance. DOM in streams at both sites demonstrated optical signatures indicative of photodegradation downstream processes, even over short distances of 2000 m. Flow pathways and the connected hydrological residence time control DOM quality. Deeper flow pathways allow the export of permafrost-derived DOM (i.e. from deeper in the active layer), whereas shallow pathways with shorter residence times lead to the export of fresh surface- and near-surface-derived DOM. Compared to the large Arctic rivers, DOM quality exported from the small catchments studied here is much fresher and therefore prone to degradation. Assessing optical properties of DOM and linking them to catchment properties will be a useful tool for understanding changing DOM fluxes and quality at a pan-Arctic scale. Y1 - 2019 U6 - https://doi.org/10.5194/bg-16-4535-2019 SN - 1726-4170 SN - 1726-4189 VL - 16 IS - 23 SP - 4535 EP - 4553 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Coelho, Christine A1 - Heim, Birgit A1 - Förster, Saskia A1 - Brosinsky, Arlena A1 - de Araujo, Jose Carlos T1 - In Situ and Satellite Observation of CDOM and Chlorophyll-a Dynamics in Small Water Surface Reservoirs in the Brazilian Semiarid Region JF - Water N2 - We analyzed chlorophyll-a and Colored Dissolved Organic Matter (CDOM) dynamics from field measurements and assessed the potential of multispectral satellite data for retrieving water-quality parameters in three small surface reservoirs in the Brazilian semiarid region. More specifically, this work is comprised of: (i) analysis of Chl-a and trophic dynamics; (ii) characterization of CDOM; (iii) estimation of Chl-a and CDOM from OLI/Landsat-8 and RapidEye imagery. The monitoring lasted 20 months within a multi-year drought, which contributed to water-quality deterioration. Chl-a and trophic state analysis showed a highly eutrophic status for the perennial reservoir during the entire study period, while the non-perennial reservoirs ranged from oligotrophic to eutrophic, with changes associated with the first events of the rainy season. CDOM characterization suggests that the perennial reservoir is mostly influenced by autochthonous sources, while allochthonous sources dominate the non-perennial ones. Spectral-group classification assigned the perennial reservoir as a CDOM-moderate and highly eutrophic reservoir, whereas the non-perennial ones were assigned as CDOM-rich and oligotrophic-dystrophic reservoirs. The remote sensing initiative was partially successful: the Chl-a was best modelled using RapidEye for the perennial one; whereas CDOM performed best with Landsat-8 for non-perennial reservoirs. This investigation showed potential for retrieving water quality parameters in dry areas with small reservoirs. KW - water quality KW - eutrophication KW - tropic state index KW - Landsat-8 KW - RapidEye KW - tropical inland water bodies KW - Brazil Y1 - 2017 U6 - https://doi.org/10.3390/w9120913 SN - 2073-4441 VL - 9 PB - MDPI CY - Basel ER - TY - JOUR 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 JF - Remote Sensing 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. KW - CDOM KW - lakes KW - lake catchments KW - permafrost KW - Yamal KW - remote sensing data Y1 - 2018 U6 - https://doi.org/10.3390/rs10020167 SN - 2072-4292 VL - 10 IS - 2 PB - MDPI CY - Basel 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 - JOUR A1 - Geng, Rongwei A1 - Andreev, Andrei A1 - Kruse, Stefan A1 - Heim, Birgit A1 - van Geffen, Femke A1 - Pestryakova, Luidmila A1 - Zakharov, Evgenii A1 - Troeva, Elena I. A1 - Shevtsova, Iuliia A1 - Li, Furong A1 - Zhao, Yan A1 - Herzschuh, Ulrike T1 - Modern pollen assemblages from lake sediments and soil in East Siberia and relative pollen productivity estimates for Major Taxa JF - Frontiers in Ecology and Evolution N2 - Modern pollen-vegetation-climate relationships underpin palaeovegetation and palaeoclimate reconstructions from fossil pollen records. East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and near natural vegetation under cold continental climate conditions. Reliable pollen-based quantitative vegetation and climate reconstructions are still scarce due to the limited number of modern pollen datasets. Furthermore, differences in pollen representation of samples from lake sediments and soils are not well understood. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface-sediment samples collected in Chukotka and central Yakutia in East Siberia. The pollen-vegetation-climate relationships were investigated by ordination analyses. Generally, tundra and taiga vegetation types can be well distinguished in the surface pollen assemblages. Moss/soil and lake samples contain generally similar pollen assemblages as revealed by a Procrustes comparison with some exceptions. Overall, modern pollen assemblages reflect the temperature and precipitation gradients in the study areas as revealed by constrained ordination analysis. We estimate the relative pollen productivity (RPP) of major taxa and the relevant source area of pollen (RSAP) for moss/soil samples from Chukotka and central Yakutia using Extended R-Value (ERV) analysis. The RSAP of the tundra-forest transition area in Chukotka and taiga area in central Yakutia are ca. 1300 and 360 m, respectively. For Chukotka, RPPs relative to both Poaceae and Ericaceae were estimated while RPPs for central Yakutia were relative only to Ericaceae. Relative to Ericaceae (reference taxon, RPP = 1), Larix, Betula, Picea, and Pinus are overrepresented while Alnus, Cyperaceae, Poaceae, and Salix are underrepresented in the pollen spectra. Our estimates are in general agreement with previously published values and provide the basis for reliable quantitative reconstructions of East Siberian vegetation. KW - modern pollen assemblages KW - pollen-vegetation-climate relationships KW - East Siberia KW - tundra KW - taiga KW - relative pollen productivity KW - quantitative vegetation reconstruction Y1 - 2022 U6 - https://doi.org/10.3389/fevo.2022.837857 SN - 2296-701X VL - 10 PB - Frontiers Media CY - Lausanne ER - TY - THES A1 - Heim, Birgit T1 - Qualitative and quantitative analyses of Lake Baikal's surface-waters using ocean colour satellite data (SeaWiFS) T1 - Qualitative und quantitative Analysen des Baikalsee Oberflächenwassers auf der Grundlage von Ocean Colour Satellitendaten (SeaWiFS) N2 - One of the most difficult issues when dealing with optical water remote-sensing is its acceptance as a useful application for environmental research. This problem is, on the one hand, concerned with the optical complexity and variability of the investigated natural media, and therefore the question arises as to the plausibility of the parameters derived from remote-sensing techniques. Detailed knowledge about the regional bio- and chemico-optical properties is required for such studies, however such information is seldom available for the sites of interest. On the other hand, the primary advantage of remote-sensing information, which is the provision of a spatial overview, may not be exploited fully by the disciplines that would benefit most from such information. It is often seen in a variety of disciplines that scientists have been primarily trained to look at discrete data sets, and therefore have no experience of incorporating information dealing with spatial heterogeneity. In this thesis, the opportunity was made available to assess the potential of Ocean Colour data to provide spatial and seasonal information about the surface waters of Lake Baikal (Siberia). While discrete limnological field data is available, the spatial extension of Lake Baikal is enormous (ca. 600 km), while the field data are limited to selected sites and expedition time windows. Therefore, this remote-sensing investigation aimed to support a multi-disciplinary limnological investigation within the framework of the paleoclimate EU-project ‘High Resolution CONTINENTal Paleoclimate Record in Lake Baikal, Siberia (CONTINENT)’ using spatial and seasonal information from the SeaWiFS satellite (NASA). From this, the SeaWiFS study evolved to become the first efficient bio-optical satellite study of Lake Baikal. During the course of three years, field work including spectral field measurements and water sampling, was carried out at Lake Baikal in Southern Siberia, and at the Mecklenburg and Brandenburg lake districts in Germany. The first step in processing the SeaWiFS satellite data involved adapting the SeaDAS (NASA) atmospheric-correction processing to match as close as possible the specific conditions of Lake Baikal. Next, various Chl-a algorithms were tested on the atmospherically-corrected optimized SeaWiFS data set (years 2001 to 2002), comparing the CONTINENT pigment ground-truth data with the Chl-a concentrations derived from the satellite data. This showed the high performance of the global Chl-a products OC2 and OC4 for the oligotrophic, transparent waters (bio-optical Case 1) of Lake Baikal. However, considerable Chl-a overestimation prevailed in bio-optical Case 2 areas for the case of discharge events. High-organic terrigenous input into Lake Baikal could be traced and information extracted using the SeaWiFS spectral data. Suspended Particulate Matter (SPM) was quantified by the regression of the SeaDAS attenuation coefficient as the optical parameter with SPM field data. Finally, the Chl-a and terrigenous input maps derived from the remote sensing data were used to assist with analyzing the relationships between the various discrete data obtained during the CONTINENT field work. Hence, plausible spatial and seasonal information describing autochthonous and allochthonous material in Lake Baikal could be provided by satellite data.Lake Baikal, with its bio-optical complexity and its different areas of Case 1 and Case 2 waters, is a very interesting case study for Ocean Colour analyses. Proposals for future Ocean Colour studies of Lake Baikal are discussed, including which bio-optical parameters for analytical models still need to be clarified by field investigations. N2 - Die Gewässerfernerkundung entwickelte sich seit den 70ern vor allem aus der Ozeanographie und der Atmosphärenforschung, und wird inzwischen als anerkannte Methode genutzt, um global die Phytoplanktonverteilung in den Weltmeeren erfassen zu können, u.a. für CO2-Haushaltsmodellierungen. Atmosphärenkorrigierte Multi- und Hyperspektralscannerdaten ermöglichen die Qualifizierung bio-optischer Gewässertypen und die Quantifizierung optisch sichtbarer Wasserinhaltsstoffe und bieten gerade auch für dynamische und heterogene Küsten- und Binnengewässer das große Potential des räumlichen Informationsgewinnes.Im Rahmen des Paläoklimaprojektes CONTINENT wurde in dieser Arbeit das Oberflächenwasser des Baikalsees mit Gewässerfernerkungsmethoden analysiert. Wichtig für die Interpretation von Klima-Proxies sind v.a. auch Hinweise auf die Verteilung des autochthonen Materials im Baikalsee (Fernerkundungsparameter: Chlorophyll-a), ebenso wie Hinweise auf allochthone Einträge an den Bohrungsstellen (Fernerkundungsparameter ‚Terrigener Eintrag’). Auf den Geländekampagnen in den Sommern 2001, 2002, 2003 in Sibirien und in Deutschland wurden Feldspektrometermessungen mit gleichzeitiger Wasserprobenahme auf die optisch sichtbaren Wasserinhaltsstoffe Phytoplankton, Schwebstoff, und DOC durchgeführt. Dabei konnten Messtechniken für Geländespektrometer evaluiert, und grundlegende Aussagen über die spektrale Verteilung des In-Wasser Lichtfeldes im Baikalsee gemacht werden. Die Ocean Colour Satellitendaten des NASA-Instrumentes SeaWiFS und die Möglichkeiten der komplexen NASA Software SeaDAS wurden genutzt. Für die Ableitung des am Baikalsee anzutreffenden organikreichen terrigenen Eintrages, wurde ein vorläufiger Algorithmus aus den Geländedaten generiert. Verschiedene Algorithmen für den Parameter ‚Chlorophyll-a’ wurden mit dem Geländedatensatz der Projektpartnerin S. Fietz (Institut für Gewässerökologie und Binnenfischerei, IGB) evaluiert. Als geeignetester etablierte sich der auf oligotrophe Gewässer optimierte NASA Chlorophyll Algorithmus ‚Ocean Colour (OC) 2’. Die Quantifizierungen und Ergebnisse werden diskutiert. Als Endergebnis wird der Überblick über Sedimenteintrag und Phytoplanktondynamik im Baikalsee für den Zeitraum 2001-2002 zur Verfügung gestellt und die autochthonen versus allochthonen Einflüsse an den Projektlokationen werden beschrieben. Der Baikalsee erwies sich als bio-optisch ein sehr komplexes und interessantes Studienobjekt. Ein wichtiger Punkt, der in dieser Arbeit angesprochen wird, ist die Atmosphärenkorrektur, die wesentliche Einflüsse auf die Qualifizierungen und Quantifizierungen hat, aber als Standardprogramm nur für den pelagialen Wasserkörper in Meeresspiegelhöhe mit marinen, bzw. Küstenatmosphären konditioniert ist. Ein weiterer bedeutender Punkt, der in dieser Arbeit diskutiert wird, ist der relevante spektrale Einfluss des organikreichen terrigenen Eintrages auf die Gewässerfarbe und dadurch auf die Qualität der Chlorophyll-Ableitung. Somit boten sich die Möglichkeiten, das räumliche Ausmaß und die Dynamik rezenter terrigener Einträge zu erfassen. Auch die Entwicklung des Phytoplankton von Frühsommer bis Spätsommer im Baikalsee konnte mit den SeaWiFS Daten nachvollzogen werden. Die hier vorgestellte Studie stellte sich als die erste grundlegende optische Gewässerfernerkundungsstudie mit Satellitendaten am Baikalsee heraus, und konnte erfolgreich abgeschlossen werden. KW - Baikalsee KW - Optische Fernerkundung KW - Phytoplankton KW - Sedimenttransport KW - Palaeoklima KW - SeaWiFS Ocean-Colour Satellitendaten KW - autochthon KW - allochthon KW - Gewässerfernerkundung KW - Lake Baikal KW - Ocean Colour satellite data KW - terrigenous input KW - phytoplankton distribution Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-7182 ER - TY - JOUR A1 - Heim, Birgit A1 - Lisovski, Simeon A1 - Wieczorek, Mareike A1 - Morgenstern, Anne A1 - Juhls, Bennet A1 - Shevtsova, Iuliia A1 - Kruse, Stefan A1 - Boike, Julia A1 - Fedorova, Irina A1 - Herzschuh, Ulrike T1 - Spring snow cover duration and tundra greenness in the Lena Delta, Siberia BT - two decades of MODIS satellite time series (2001-2021) JF - Environmental research letters N2 - The Lena Delta in Siberia is the largest delta in the Arctic and as a snow-dominated ecosystem particularly vulnerable to climate change. Using the two decades of MODerate resolution Imaging Spectroradiometer satellite acquisitions, this study investigates interannual and spatial variability of snow-cover duration and summer vegetation vitality in the Lena Delta. We approximated snow by the application of the normalized difference snow index and vegetation greenness by the normalized difference vegetation index (NDVI). We consolidated the analyses by integrating reanalysis products on air temperature from 2001 to 2021, and air temperature, ground temperature, and the date of snow-melt from time-lapse camera (TLC) observations from the Samoylov observatory located in the central delta. We extracted spring snow-cover duration determined by a latitudinal gradient. The 'regular year' snow-melt is transgressing from mid-May to late May within a time window of 10 days across the delta. We calculated yearly deviations per grid cell for two defined regions, one for the delta, and one focusing on the central delta. We identified an ensemble of early snow-melt years from 2012 to 2014, with snow-melt already starting in early May, and two late snow-melt years in 2004 and 2017, with snow-melt starting in June. In the times of TLC recording, the years of early and late snow-melt were confirmed. In the three summers after early snow-melt, summer vegetation greenness showed neither positive nor negative deviations. Whereas, vegetation greenness was reduced in 2004 after late snow-melt together with the lowest June monthly air temperature of the time series record. Since 2005, vegetation greenness is rising, with maxima in 2018 and 2021. The NDVI rise since 2018 is preceded by up to 4 degrees C warmer than average June air temperature. The ongoing operation of satellite missions allows to monitor a wide range of land surface properties and processes that will provide urgently needed data in times when logistical challenges lead to data gaps in land-based observations in the rapidly changing Arctic. KW - Arctic vegetation KW - tundra KW - snow cover duration KW - NDVI KW - NDSI KW - MODIS KW - Lena Delta Y1 - 2022 U6 - https://doi.org/10.1088/1748-9326/ac8066 SN - 1748-9326 VL - 17 IS - 8 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Herzschuh, Ulrike A1 - Li, Chenzhi A1 - Boehmer, Thomas A1 - Postl, Alexander K. A1 - Heim, Birgit A1 - Andreev, Andrei A. A1 - Cao, Xianyong A1 - Wieczorek, Mareike A1 - Ni, Jian T1 - LegacyPollen 1.0 BT - a taxonomically harmonized global late Quaternary pollen dataset of 2831 records with standardized chronologies JF - Earth system science data : ESSD N2 - Here we describe the LegacyPollen 1.0, a dataset of 2831 fossil pollen records with metadata, a harmonized taxonomy, and standardized chronologies. A total of 1032 records originate from North America, 1075 from Europe, 488 from Asia, 150 from Latin America, 54 from Africa, and 32 from the Indo-Pacific. The pollen data cover the late Quaternary (mostly the Holocene). The original 10 110 pollen taxa names (including variations in the notations) were harmonized to 1002 terrestrial taxa (including Cyperaceae), with woody taxa and major herbaceous taxa harmonized to genus level and other herbaceous taxa to family level. The dataset is valuable for synthesis studies of, for example, taxa areal changes, vegetation dynamics, human impacts (e.g., deforestation), and climate change at global or continental scales. The harmonized pollen and metadata as well as the harmonization table are available from PANGAEA (https://doi.org/10.1594/PANGAEA.929773; Herzschuh et al., 2021). R code for the harmonization is provided at Zenodo (https://doi.org/10.5281/zenodo.5910972; Herzschuh et al., 2022) so that datasets at a customized harmonization level can be easily established. Y1 - 2022 U6 - https://doi.org/10.5194/essd-14-3213-2022 SN - 1866-3508 SN - 1866-3516 VL - 14 IS - 7 SP - 3213 EP - 3227 PB - Copernicus CY - Göttingen ER - TY - JOUR 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 JF - Science of remote sensing 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. KW - Ocean color remote sensing KW - Turbidity retrieval KW - Nearshore zone KW - Arctic Ocean Y1 - 2021 U6 - https://doi.org/10.1016/j.srs.2021.100036 SN - 2666-0172 VL - 4 PB - Elsevier CY - Amsterdam ER - 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 -