This visualization product displays the plastic bags abundance of marine macro-litter (> 2.5cm) per beach per year from Marine Strategy Framework Directive (MSFD) monitoring surveys. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Selection of plastic bags related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines and EU Threshold Value for Macro Litter on Coastlines from JRC (these two documents are attached to this metadata); - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not exactly 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of plastic bags related items of the survey (normalized by 100 m) = Number of plastic bags related items of the survey x (100 / survey length) Then, this normalized number of plastic bags related items is summed to obtain the total normalized number of plastic bags related items for each survey. Finally, the median abundance of plastic bags related items for each beach and year is calculated from these normalized abundances of plastic bags related items per survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. Percentiles 50, 75, 95 & 99 have been calculated taking into account plastic bags related items from MSFD data for all years. More information is available in the attached documents. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.

Global phytoplankton production monthly maps for 2017 are produced using an artificial neural network to perform a generalized nonlinear regression of PP on several predictive variables, including latitude, longitude, day length, MLD, SST, PBopt computed according to Behrenfeld and Falkowski (1997), PAR and CHL(0 m). More details about this model can be found in Scardi (2001). Behrenfeld, M. J., Falkowski, P. G. (1997), Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnology & Oceanography, 42(1), 1–20. Scardi, M. (2001), Advances in neural network modeling of phytoplankton primary production, Ecological Modelling, 146, 33–45.

The European Ground Motion Service (EGMS), part of the Copernicus Land Monitoring Service, provides consistent, regular, standardised, harmonised, and reliable information on natural and anthropogenic ground motion phenomena across Copernicus Participating States and national borders, with millimetre-level accuracy. This metadata describes EGMS Calibrated, which represents the second level of the EGMS portfolio and is considered the primary product due to its broad applicability. Unlike EGMS Basic, Calibrated provides absolute measurements, referenced to a model derived from Global Navigation Satellite System (GNSS) data. This calibration enables direct comparison of ground motion measurements across adjacent areas and between different products of the same level. EGMS Calibrated is delivered as a vector map of measurement points, each colour-coded by average velocity. Data is distributed in comma-separated values (CSV) format. Each point includes a displacement time series, representing ground motion values per satellite acquisition. The product is available for both ascending and descending satellite orbits. EGMS Calibrated is delivered to users on an annual basis, following a five-year moving window update strategy. This means that after the Baseline/first update (2016-2021), the following data periods are available: 2018-2022, 2019-2023 and 2020-2024.

Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7.

Energy class layer produced by EMODnet Seabed Habitats as an input layer (habitat descriptor) for the 2025 EUSeaMap broad-scale habitat model. The extent of the mapped area includes the Baltic Sea, and areas of the North Eastern Atlantic and Arctic extending from the Canary Islands in the south to Norway in the North. The map of energy classes was produced using underlying wave and current data and thresholds derived from statistical analyses or expert judgement on known conditions. This layer was updated in EUSeaMap 2025 using a the wave Kinetic energy layer at the seabed layer for the European Shelf area used in 2023 (linked in the Online Resources). An accompanying confidence layer is available for viewing and download from EMODnet Seabed Habitats - metadata is linked in the 'Composed of' section below. A report on the methods used in the 2025 version of EUSeaMap will be added in due course, but reports on previous versions (v2016, v2019, v2021 and v2023) are available in the lineage. Credit: Licensed under CC-BY 4.0 from the European Marine Observation and Data Network (EMODnet) Seabed Habitats initiative (https://emodnet.ec.europa.eu/en/seabed-habitats), funded by the European Commission.

Samples of the macrobenthic fauna of soft sediments were collected from around Svalbard during the 1991 Arctic EPOS cruise of RVPolarstern

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 Greater North Sea and Celtic Seas. Data were aggregated and quality controlled by 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' in Denmark. 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 ).

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).

The Sentinel-1 & Sentinel-2 Water and Ice Cover (WIC S1+S2) product is generated in near real-time at European scale. It combines ice and water extent information derived from radar data from the Sentinel-1 constellation (WIC S1), and from optical data from the Sentinel-2 constellation (WIC S2). The WICS1+S2 product is processed when both WIC S1 and WIC S2 data are available on the same day. It provides the water and ice extent on water bodies (rivers and lakes), at a spatial resolution of 20 m x 20 m. WIC S1+S2 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 WIC S1+S2 product is distributed in raster files covering an area of 110 km by 110 km with a pixel size of 20 m by 20 m in UTM/WGS84 projection, which corresponds to the Sentinel-2 input L1C product tile. Each product is composed of separate files corresponding to the different layers of the product, and another metadata file."

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