@article{WalchSinghSoreideetal.2022,
  author    = {Walch, Daniela M. R. and Singh, Rakesh K. and Soreide, Janne E. and Lantuit, Hugues and Poste, Amanda},
  title     = {Spatio-temporal variability of suspended particulate matter in a high-arctic estuary (Adventfjorden, Svalbard) using sentinel-2 time-series},
  series = {Remote sensing},
  volume    = {14},
  journal   = {Remote sensing},
  number    = {13},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs14133123},
  pages     = {22},
  year      = {2022},
  abstract  = {Arctic coasts, which feature land-ocean transport of freshwater, sediments, and other terrestrial material, are impacted by climate change, including increased temperatures, melting glaciers, changes in precipitation and runoff. These trends are assumed to affect productivity in fjordic estuaries. However, the spatial extent and temporal variation of the freshwater-driven darkening of fjords remain unresolved. The present study illustrates the spatio-temporal variability of suspended particulate matter (SPM) in the Adventfjorden estuary, Svalbard, using in-situ field campaigns and ocean colour remote sensing (OCRS) via high-resolution Sentinel-2 imagery. To compute SPM concentration (C-SPMsat), a semi-analytical algorithm was regionally calibrated using local in-situ data, which improved the accuracy of satellite-derived SPM concentration by similar to 20\% (MRD). Analysis of SPM concentration for two consecutive years (2019, 2020) revealed strong seasonality of SPM in Adventfjorden. Highest estimated SPM concentrations and river plume extent (\% of fjord with C-SPMsat > 30 mg L-1) occurred during June, July, and August. Concurrently, we observed a strong relationship between river plume extent and average air temperature over the 24 h prior to the observation (R-2 = 0.69). Considering predicted changes to environmental conditions in the Arctic region, this study highlights the importance of the rapidly changing environmental parameters and the significance of remote sensing in analysing fluxes in light attenuating particles, especially in the coastal Arctic Ocean.},
  language  = {en}
}
@article{KleinLantuitHeimetal.2021,
  author    = {Klein, Konstantin P. and Lantuit, Hugues and Heim, Birgit and Doxaran, David and Juhls, Bennet and Nitze, Ingmar and Walch, Daniela and Poste, Amanda and S{\o}reide, Janne E.},
  title     = {The Arctic Nearshore Turbidity Algorithm (ANTA)},
  series = {Science of remote sensing},
  volume    = {4},
  journal   = {Science of remote sensing},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2666-0172},
  doi       = {10.1016/j.srs.2021.100036},
  pages     = {11},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@misc{KleinLantuitHeimetal.2021,
  author    = {Klein, Konstantin P. and Lantuit, Hugues and Heim, Birgit and Doxaran, David and Juhls, Bennet and Nitze, Ingmar and Walch, Daniela and Poste, Amanda and S{\o}reide, Janne E.},
  title     = {The Arctic Nearshore Turbidity Algorithm (ANTA)},
  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    = {1250},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-55369},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-553692},
  pages     = {11},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}