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 and Sentinel-2 Snow Phenology (SP S1+S2) product is generated once a year over high-mountain areas at European scale, based on daily cumulative Gap-Filled Fractional Snow Cover (GFSC) products calculated from Sentinel-2 optical and Sentinel-1 radar data. This product describes the snow season in terms of temporality as it provides, for each pixel, the number of days with snow cover, as well as the first and the last day of the longest observed snow period. It has a spatial resolution of 100 m x 100 m. Each product is composed of separate files corresponding to the different layers of the product, and another metadata file. The product is also available in another projection as tiles aligned with Sentinel-2 (UTM/WGS84) at 60 m x 60 m. SP 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. t.

The Sentinel-2 Snow Phenology (SP S2) product is generated once a year at European scale, based on Fractional Snow Cover (FSC) products calculated from Sentinel-2 optical data. This product describes the snow season in terms of temporality as it provides, within an hydrological year and for each pixel, the number of days with snow cover, as well as the first and the last day of the longest observed snow period. It has a spatial resolution of 100 m x 100 m. Each product is composed of separate files corresponding to the different layers of the product, and another metadata file." The product is also available in another projection as tiles aligned with Sentinel-2 (UTM/WGS84) at 20 m x 20 m. SP 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.

This is the metadata covering the Sentinel-1 and Sentinel-2 Snow Phenology (SPS1S2) product. It is generated once a year over high-mountain areas at European scale, based on daily cumulative Gap-Filled Fractional Snow Cover (GFSC) products calculated from Sentinel-2 optical and Sentinel-1 radar data. This product describes the snow season in terms of temporality as it provides, for each pixel, the number of days with snow cover, as well as the first and the last day of the longest observed snow period. It has a spatial resolution of 60 m x 60 m, as does the input GFSC product. Each product is composed of separate files corresponding to the different layers of the product, and another metadata file." The product is also available in another projection as tiles aligned with the Pan-European High-Resolution Layers in the European grid (ETRS89 LAEA - EPSG: 3035) at 60 m x 60 m and 100 m x 100 m. SP S2+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 High Resolution Layer Cropping Patterns - Secondary Crop Emergence (CPSCE) raster product provides the date of emergence of the cover crop in days of the year (DOY). YYDOY where YY = last 2 digits of the year (e.g. 19 for 2019) and DOY is the day of the year (1-365) This dataset is provided annually starting in 2017 with 10 meter rasters (fully conformant with the EEA reference grid) in 100 x 100 km tiles covering the EEA38 countries. High Resolution Layer Croplands product is part of the European Union’s Copernicus Land Monitoring Service. Confidence layer available for the dataset. This dataset includes data from the French Overseas Territories (DOMs)

This product displays for Cadmium, positions with values counts that have been measured per matrix for each year and are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for every available year.

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the Norwegian Sea, Barents Sea, Greenland Sea and Icelandic Waters with 220031 CDI stations. Data were aggregated and quality controlled by 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)'. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12 ). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/ Detailed documentation is available at: https://doi.org/10.6092/ec8207ef-ed81-4ee5-bf48-e26ff16bf02e The aggregated dataset can be downloaded as ODV spreadsheet, which is composed of metadata header followed by tab separated values. This worksheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ) The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search

Urban Atlas Land Cover/Land Use Change 2018-2021 provides reliable, inter-comparable, high-resolution land use and land cover change data for 764 Functional Urban Areas (FUA) with more than 50,000 inhabitants for the 2021 reference year in EEA38 countries (EU, EFTA, Western Balkans countries, as well as Türkiye) and the United Kingdom.

Running 6-year analysis of Water body silicate 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 1966-2023. 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.

This datasets contributes to a better understanding of diversity in small peracarid crustacean and their possible distribution patterns in remote deep-sea regions. It contains specimen ocurrence records of the taxon Cumacea sampled with diverse benthic gears (epibenthic sledges, box corer) on the Yermak Plateau north of Svalbard during the PASCAL project with RV Polarstern in 2017 and during the IceAGE expedition IceAGE1 in 2011 in deep sea regions of the Nordic GIN-Seas (Greenland, Iceland and Norwegian Sea). The specimens investigated on morphological and molecular basis in this study were sampled in the course of different projects: The IceAGE program (Icelandic marine Animals: Genetics and Ecology, Brix et al. 2014a) is an ongoing research project (IceAGE 2 in 2013, IceAGE-RR in 2018, IceAGE 3 in 2020) which was established as a follow up of the very successful BIOFAR (Biology of the Faroe Islands, Nørrevang et al. 1994; Gerken and Watling 1999) and BIOICE (Benthic Invertebrates of Icelandic waters, Omarsdottir et al. 2013) projects. It is aimed to develop into a long-term study to get an overview of the biodiversity in this extremely diverse region around Iceland with a variety of different habitats and environmental challenges in its adjacent waters. Based on genetic and morphological diversity, it aims to create an inventory of the fauna as elementary knowledge for a comprehensive understanding of possible responses to changing climate conditions in marine environments (Brix et al. 2014a). The focus of the expedition PS106/1 (ARK-XXXI/1.1, 24th of May – 21st of June, 2017) off northern Svalbard onboard the RV Polarstern in course of PASCAL (Physical feedbacks of Arctic PBL, Sea ice, Cloud and Aerosol) was an interdisciplinary approach for studying the interaction of different Arctic feedback mechanisms based on atmospheric, oceanographic, physical and biological studies (Macke and Flores 2018). In this context the vessel was attached to an ice floe during a two-week passive drifting according to the ocean’s current as a preliminary trial-expedition to the first year-round MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition (Sep/2019 – Sep/2020).