This metadata covers the Ice Cover Duration (ICD) product is generated once a year and it provides an estimated number of ice covered days for each pixel in the inland waters at European scale. The product is derived from Water/Ice Cover (WIC) products, both from Sentinel-1 and Sentinel-2 observations. It has a spatial resolution of 20 m x 20 m. It is also available in another projection as tiles aligned with the Pan-European High-Resolution Layers in the European 20 m x 20 m grid (ETRS89 LAEA - EPSG: 3035). ICD is one of the products of the pan-European High-Resolution Water Snow & Ice portfolio (HR-WSI), which are provided at high spatial resolution from the Sentinel-2 and Sentinel-1 constellations data from September 1, 2016 onwards.

This is the metadata covering the Water Layer (WL) product. The WL is one of the products of the pan-European High-Resolution Water Snow & Ice portfolio (HR-WSI), which are provided at high spatial resolution from the Sentinel-2 and Sentinel-1 constellations data from September 1, 2016 onwards.. The WL is generated for the 2021 & 2024 reference year. It is a a multi-annual product based on the information covering the period (e.g. 2016-2021). In the context of the HR-WSI, the water and dry frequency masks are derived from intermediate outputs of the WCD workflow, the monthly surface water masks in combination with the WIC S2 NRT product. It provides detailed information about the presence and condition of water surfaces across Europe. There are 5 major classes like: - Dry (always or mostly dry with minor instances of wet) - permanent water (always contains water) - temporary water ( temporary water surfaces, aliteration of dry and water) - sea water (oceans and sea) - clouds It is also generated in different spatial resolutions (10m and 100m) and projections (LAEA & WGS84/UTM). The High Resolution Water Layer portfolio consists of the WL, the Water Presence Index (WPI), the Water confidence layer (WCL) and the Rolling archive (WLRA). The WL is provided in a package (zip) containing the WL, the WPI and the WCL: The WCL is displaying a measure of confidence between 0 and 100%. It identifies the likelihood of (in)correctness on pixel level based on information gained during production for the WL for the respective reference year. It is also generated in different spatial resolutions (10m and 100m) and projections (LAEA & WGS84/UTM). The Water Presence Index (WPI) product is one of the products of the pan-European High-Resolution Water Snow & Ice portfolio (HR-WSI), which are provided at high spatial resolution from the Sentinel-2 and Sentinel-1 constellations data from September 1, 2016 onwards. The High Resolution Water Layer portfolio consists of the Water Layer (WL), the Water Presence Index (WPI), the Water confidence layer (WCL) and the Rolling archive (WLRA). The WPI is generated for the 2021 reference year. It is a a multi-annual product based on the information covering a7-year period (e.g. 2016-2021). In the context of the HR-WSI, the water and dry frequency masks are derived from intermediate outputs of the WCD workflow, the monthly surface water masks in combination with the WIC S2 NRT product. It provides detailed information about the presence and condition of water surfaces across Europe. It is also generated in different spatial resolutions (10m and 100m) and projections (LAEA & WGS84/UTM).

Urban Atlas Building Block Height 2021 is a 10 m high resolution raster layer containing height information generated for selected cities and urban areas as part of the Urban atlas suite of products. Height information is based on satellite information and derived datasets like the digital surface model, the digital terrain model and the normalized digital surface model (DSM).

EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Norwegian Sea, Barents Sea, Greenland Sea and Icelandic Waters. Data were aggregated and quality controlled by the 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)' in Norway. ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets . Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67 ). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/ . When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.025 kg/L. The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV ).

The Imperviousness Change Classified (IMCC) 2021-2024 layer is part of the High Resolution Layer (HRL) Imperviousness and provides categorical information on the imperviousness change per pixel between reference years 2021 and 2024 as derived from re-classification of the Imperviousness Density Change (IMDC) 2021–2024 layer. The production of the HRL Imperviousness is coordinated by EEA in the frame of Copernicus, the Earth observation component of the European Union’s Space programme. The product is a raster dataset with 20-meter grid spacing (spatial resolution) that covers the 38 Eionet member and cooperating countries as well as the United Kingdom (i.e. EEA38+UK). It is distributed as 100 x 100 km tiles that are fully conformant with the EEA reference grid.

Running 6-year analysis of Water body phosphate in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to a 6-year centred average. Periods span between 1975-2021. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300. Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis in n dimensions) tool. GEBCO_08 Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the horizontal correlation length is fixed to 80 km and decreasing towards the coastline, the vertical correlation length is varying with depth. Signal to noise ratio is fixed to 1.0. Background fields were created using data for the given time period and season. Log transformation was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is umol/l.

Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales. Original provider: Happywhale Dataset credits: Happywhale and contributorsSightings and images were submitted to Happywhale by contributors. A portion of the Happywhale data were transferred to OBIS-SEAMAP upon the agreement between Happywhale and OBIS-SEAMAP. There may be duplicate records among Happywhale datasets and other OBIS-SEAMAP datasets. The precision of date/time vary per record. Some records have date accuracy up to year only. This dataset includes sightings and photos from the following 280 contributors in alphabetic order: adam maire; Adelie Xiaohang Li; Adrian Neubert; Alexandre Lhériau; Alex Sinclair Lack; Alicia; Allan Finney; Allied Whale North Atlantic Humpback Whale Catalog; Allison Chen; Ana; Andrew Newlun; Andrew Stewart; Andy Rose; Angela Bowler; ANGEL SOLE; Anja Robanke; Anke Kugelstadt; Anna Astafurova; Annette Bombosch; AnninaS; Antoine Viot; Audrey Stephens; Austin Wyatt; Avner Chen; Babsi Neubarth; Barbara Anne Brandon; Beatriz Benares; Benoit Nabholz; B. Noordermeer; Bonnie Gretz; Borbala; Boyd Taylor; brad siviour; Calle Schönning; Camilo Rada; Carlos Rincon; Caroline Hodgkiss; Cassandra Ruiz; Cees Tineke; Charles Lavin; Charlotte Taplin; Chris Croxson; Christian Engelke; Christian Thrane; Christoph Fritz; Chrys Tremththanmor; Conor Ryan; Dani Abras; Daniel Stevens; Danilo Foresti; DarrenJew; Dave Matlin; David Bradley; David German; Dennis Boon; Devienne Gilles; Dimitri Vitkin; Dirk van Zandwijk; Dmitrii Kiselev; Domininc Barrington; Doug Gould; Eckhard; Eden Zang; Eivind Aksnes; Elaine Purnell; Elie Vannier; Eliott Lehoux; Elísabet Ýr Guðjónsdóttir; Elke; Ellen Klein; Elodie; emma; Emma Luck; Emma Neave-Webb; Emmanuelle Peyredieu; Enrico Hoefer; Eric Clark; Eric ROURE; Erin Sneider; Eugene Saxentoff; Eyd M. Grønadal; Fabian Schmalzried; Fabio; Familia Sanchez Planell; Fanny; Federico Arribere; Florentine Guinot; françois; Frank J.; Fredrik Broms; Gabriel Lett Viviani; gaidet; Gail Cousins; Garry Bray; Geffen family; Geir Hareide Hansen; Ghada; GordieBryce; Gordon Riddell; Greta Henderson; Hanna Michel; hannes heylen; Hans Verdaat; Harold Moses; Hazel Pittwood; Heidi Krajewsky; Henk Kamstra; Herman Sips; Herve Sibert; Husavik Research Centre; Ian Gordon; Irati Maruri; Isabella Clegg; James F C Hyde IV; Jamie Coleman; Jan Kajzar; Javier Cotin; Javier Solis; Jeff Reynolds; Jenifer; Jérôme JACOB; Jim Wilson; Joe Arceneaux; Joel Moore; John Mina; Jonas Astrup; Jonathan Rempel; joost vaeyens; Josef Wolf; Joy Martinello; Joy van der Beek; Judith Scott; Judit Roch; Julia Jayne; Juliane Schlei; Julia Yr Thorvaldsdottir; Julie Skyte; karen McMullen; Kate Sauvain; Kate Weston; Katrin Schmidt; Kayla Spencer; Ken Jensen; Ken Wells; Kerstin Langenberger; Kevin; Kirsten MacTaggart; Kit Kovacs; Konstantinos Kafritsas; Kurt Methfessel; LAMBIN Jean-Marc; Lars Maltha Rasmussen; Laura; Laurence Fischer; Laurens; Laurie Horsfall; Leendert; Lena Nicola; Lene Zachariassen; Leslie Stueben-Trumphour; Lisa Hildebrand; Loes de Heus; Maëva Accart; Manfred Moormann; Marc Gose; MARC SELLERS; Marcus Bergström; Margrét Ósk Elíasdóttir; Marian Herz; Marijke Nita de Boer; Marika Marnela; Marilia Olio; Marion JONCHERES; Marjolein Meijdam; Mark Harris; Marley Watkins; Martine; Martin Kemper; Mary Keenan; Matt McDermit; Max Schweiger; Menno Schaefer; Michael Scott; Michael Sterling; Michel Pierfitte; Mick Peerdeman; Mona Beate Wendelborg; Mona Wong; Mouser Williams; MS Fram; MS Maud; MS Otto Sverdrup; MS Spitsbergen; Nacho Oria; Nadine Hunziker; Natascha; Niklas Astrom; Nils; NOAA National Marine Mammal Laboratory (NMML); Ocean Missions; Olaf Pignataro; Olivier Blaud; Pascal Mauerhofer; Patrick Ruf; Patrick Scherer; Pat Sanders; Pauline van Monsjou; Paul Soulby; Per Nikolaj Bukh; Per Olsson; Petra Glardon; Petr Petrik; Philippe Jeanty; Pim Wolf; Pupanoid; Queloz; Rachael Barber; Radovan Sutora; Rafael Martins; Raina Burke; Rand Rudland; Rebecca Malkewicz; Richard Allan; Richard Lovelock; Richard Walker; Richard White; Rob Gons; Rodrigo A. Martinez Catalan; Rod White; Romane R; Rosa M. Coronas; Russian Cetacean Habitat Project; Ruud; Sabine Griesser; Sais Céline; Samantha Wormley; Sandra Zijlstra; Sea Fever Productions; Shannon; Shantala Wentink; Sheila Miller; S. Helgu; Siairra Tharp; Simon Smith; Slater T Moore; Sophie Carr; Soyer; Stacey Colebaugh; Steffen G.; Steffen Oehme; Steffo Polar; Stephan Uhlemann; Stephen King; Steve Jones; Steven dos-Remedios; Steve Willetts; Susan Smith; suse; Tanja; Ted Creek; Teresa Blase; Therese Horntrich; Thomas Podesta; Tiffany Fare; Tim Wright; Tobias Brehm; Tobias Paul; Tony Littler; Tressarieu; Tudor Morgan; Ursula Brändle; Vicki Beaver; Virgil Reglioni; Vladimir Burkanov; Whale Wise; Wilfried Schnessl; Wouter Verwee; Years of the North Atlantic Humpback whale (YoNAH); Yuri Choufour; Yves Roumazeilles

Moving 6-year analysis of Oxygen at Atlantic Sea for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centered average of each season. 6-year periods span from 1960-1965 until 2015-2020. Observational data span from 1960 to 2020. Depth range (IODE standard depths): -3000.0, -2500.0, -2000.0, -1750, -1500.0, -1400.0, -1300.0, -1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -20.0, -10.0, -5.0, -0.0 Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5 DIVA settings. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. Signal to noise ratio was fixed to 1. Background field: the data mean value is subtracted from the data. Detrending of data: no, Advection constraint applied: no. Units: umol/l

This product displays for Triphenyltin, median values of the last 6 available years that have been measured per matrix and are present in EMODnet regional contaminants aggregated datasets, v2022. The median values ranges are derived from the following percentiles: 0-25%, 25-75%, 75-90%, >90%. Only "good data" are used, namely data with Quality Flag=1, 2, 6, Q (SeaDataNet Quality Flag schema). For water, only surface values are used (0-15 m), for sediment and biota data at all depths are used.

Mapping and classifying the seabed of the West Greenland continental shelf. Marine benthic habitats support a diversity of marine organisms that are both economically and intrinsically valuable. Our knowledge of the distribution of these habitats is largely incomplete, particularly in deeper water and at higher latitudes. The western continental shelf of Greenland is one example of a deep (more than 500 m) Arctic region with limited information available. This study uses an adaptation of the EUNIS seabed classification scheme to document benthic habitats in the region of the West Greenland shrimp trawl fishery from 60┬░N to 72┬░N in depths of 61ÔÇô725 m. More than 2000 images collected at 224 stations between 2011 and 2015 were grouped into 7 habitat classes. A classification model was developed using environmental proxies to make habitat predictions for the entire western shelf (200ÔÇô700 m below 72┬░N). The spatial distribution of habitats correlates with temperature and latitude. Muddy sediments appear in northern and colder areas whereas sandy and rocky areas dominate in the south. Southern regions are also warmer and have stronger currents. The Mud habitat is the most widespread, covering around a third of the study area. There is a general pattern that deep channels and basins are dominated by muddy sediments, many of which are fed by glacial sedimentation and outlets from fjords, while shallow banks and shelf have a mix of more complex habitats. This first habitat classification map of the West Greenland shelf will be a useful tool for researchers, management and conservationists.