Corine Land Cover 2012 (CLC2012) is one of the Corine Land Cover (CLC) datasets produced within the frame the Copernicus Land Monitoring Service referring to land cover / land use status of year 2012. CLC service has a long-time heritage (formerly known as "CORINE Land Cover Programme"), coordinated by the European Environment Agency (EEA). It provides consistent and thematically detailed information on land cover and land cover changes across Europe. CLC datasets are based on the classification of satellite images produced by the national teams of the participating countries - the EEA members and cooperating countries (EEA39). National CLC inventories are then further integrated into a seamless land cover map of Europe. The resulting European database relies on standard methodology and nomenclature with following base parameters: 44 classes in the hierarchical 3-level CLC nomenclature; minimum mapping unit (MMU) for status layers is 25 hectares; minimum width of linear elements is 100 metres. Change layers have higher resolution, i.e. minimum mapping unit (MMU) is 5 hectares for Land Cover Changes (LCC), and the minimum width of linear elements is 100 metres. The CLC service delivers important data sets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as e.g. protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, monitoring urban land take, assessing developments in agriculture or dealing with water resources directives. part of the European Copernicus Programme coordinated by the European Environment Agency, providing environmental information from a combination of air- and space-based observation systems and in-situ monitoring.

Corine Land Cover Change 2012-2018 (CHA1218) is one of the Corine Land Cover (CLC) datasets produced within the frame the Copernicus Land Monitoring Service referring to changes in land cover / land use status between the years 2012 and 2018. CLC service has a long-time heritage (formerly known as "CORINE Land Cover Programme"), coordinated by the European Environment Agency (EEA). It provides consistent and thematically detailed information on land cover and land cover changes across Europe. CLC datasets are based on the classification of satellite images produced by the national teams of the participating countries - the EEA members and cooperating countries (EEA39). National CLC inventories are then further integrated into a seamless land cover map of Europe. The resulting European database relies on standard methodology and nomenclature with following base parameters: 44 classes in the hierarchical 3-level CLC nomenclature; minimum mapping unit (MMU) for status layers is 25 hectares; minimum width of linear elements is 100 metres. Change layers have higher resolution, i.e. minimum mapping unit (MMU) is 5 hectares for Land Cover Changes (CHA), and the minimum width of linear elements is 100 metres. The CLC service delivers important data sets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as e.g. protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, monitoring urban land take, assessing developments in agriculture or dealing with water resources directives. part of the European Copernicus Programme coordinated by the European Environment Agency, providing environmental information from a combination of air- and space-based observation systems and in-situ monitoring.

The Copernicus High Resolution Water and Wetness (WAW) 2015 layer is a thematic product showing the occurrence of water and wet surfaces over the period from 2009 to 2015 for the EEA38 area and the United Kingdom. This metadata corresponds to the 20m classified Water and Wetness product. The production of the High Resolution Water and Wetness layers was coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme. Two WAW products are available: - The main Water and Wetness (WAW) product, with defined classes of (1) permanent water, (2) temporary water, (3) permanent wetness and (4) temporary wetness. - The additional expert product: Water and Wetness Probability Index (WWPI). The products show the occurrence of water and indicate the degree of wetness in a physical sense, assessed independently of the actual vegetation cover and are thus not limited to a specific land cover class and their relative frequencies. Data is provided as a mosaic of the full area, and as tiles with a side length of 1000 km x 1000 km. In 2020, and due to methodological improvements, the temporary wet class has been reprocessed during the update for the 2018 reference year.

The high resolution forest product consists of three types of (status) products and additional change products. The status products are available for the 2012, 2015 and 2018 reference years: 1. Tree cover density providing level of tree cover density in a range from 0-100%; 2. Dominant leaf type providing information on the dominant leaf type: broadleaved or coniferous; 3. A Forest type product. The forest type product allows to get as close as possible to the FAO forest definition. In its original (20m) resolution it consists of two products: 1) a dominant leaf type product that has a MMU of 0.5 ha, as well as a 10% tree cover density threshold applied, and 2) a support layer that maps, based on the dominant leaf type product, trees under agricultural use and in urban context (derived from CLC and high resolution imperviousness 2009 data). For the final 100m product trees under agricultural use and urban context from the support layer are removed. The high resolution forest change products comprise a simple tree cover density change product for 2012-2015 (% increase or decrease of real tree cover density changes). The production of the high resolution forest layers was coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme.

The high resolution imperviousness products capture the percentage and change of soil sealing. Built-up areas are characterized by the substitution of the original (semi-) natural land cover or water surface with an artificial, often impervious cover. These artificial surfaces are usually maintained over long periods of time. A series of high resolution imperviousness datasets (for the 2006, 2009, 2012, 2015 and 2018 reference years) with all artificially sealed areas was produced using automatic derivation based on calibrated Normalized Difference Vegetation Index (NDVI). This series of imperviousness layers constitutes the main status layers. They are per-pixel estimates of impermeable cover of soil (soil sealing) and are mapped as the degree of imperviousness (0-100%). Imperviousness change layers were produced as a difference between the reference years (2006-2009, 2009-2012, 2012-2015, 2015-2018 and additionally 2006-2012, to fully match the CORINE Land Cover production cycle) and are presented 1) as degree of imperviousness change (-100% -- +100%), in 20m and 100m pixel size, and 2) a classified (categorical) 20m change product.

The High Resolution Layer Forest Type (FTY) provides a forest classification with 3 thematic classes (all non-forest areas / broadleaved forest / coniferous forest) at 10m spatial resolution and with a Minimum Mapping Unit (MMU) of 0.5 ha. This raster layer is largely following the FAO (Food and Agriculture Organisation of the United Nations) forest definition with tree covered areas in agricultural and urban context excluded using the respective Forest Additional Support Layer (FADSL). This dataset is provided on a 3-yearly frequency in 10 meter rasters (fully conformant with the EEA reference grid) in 100 x 100 km tiles covering the EEA38 countries. High Resolution Layer Tree Cover and Forest product is part of the European Union’s Copernicus Land Monitoring Service. This dataset includes data from the French Overseas Territories (DOMs)

Moving 6-year analysis of Water body dissolved oxygen concentration in the NorthEast Atlantic 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 centred average of each season. 6-year periods span from 1950/1955 until 2016/2021. Observation data span from 1950 to 2021. Depth levels (IODE standard depths): [0.0, 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 75.0, 100.0, 125.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1750.0, 2000.0, 2500.0, 3000.0]. Data sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Descrption of DIVAnd analysis: the computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.4, using GEBCO 30 sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps is 0.1 degrees. Horizontal correlation length varies from 400km in open sea regions to 50km at the coast. Vertical correlation length is defined as twice the vertical resolution. Signal-to-noise ratio was fixed to 1 for vertical profiles and 0.1 for time series to account for the redundancy in the time series observations.A logarithmic transformation (DIVAnd.Anam.loglin) was applied to the data prior to the analysis to avoid unrealistic negative values. Background field: a vertically-filtered profile of the seasonal data mean value (including all years) is substracted from the data. Detrending of data: no, advection constraint applied: no. Units: umol/l.

This visualization product displays the single use plastics (SUP) related items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations. 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 surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Selection of SUP related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines for Macro Litter on Coastlines from JRC (this document is attached to this metadata); - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 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 SUP related items of the survey (normalized by 100 m) = Number of SUP related items of the survey x (100 / survey length) Then, this normalized number of SUP related items is summed to obtain the total normalized number of SUP related items for each survey. Finally, the median abundance of SUP related items for each beach and year is calculated from these normalized abundances of SUP related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account SUP related items from other sources 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.

The High Resolution Layer Cropping Patterns - Main Crop Emergence (CPMCE) raster product provides the emergence date of the main (annual) crop expressed in DOY (day of year). 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)

The Slope of the green-up period (Left Slope, LSLOPE), one of the Vegetation Phenology and Productivity (VPP) parameters, is a product of the pan-European High Resolution Vegetation Phenology and Productivity (HR-VPP) component of the Copernicus Land Monitoring Service (CLMS). The slope of the green-up period (LSLOPE) expresses the rate of change in the values of the Plant Phenology Index (PPI) at the day when the vegetation growing season starts. The Plant Phenology Index (PPI) is a physically based vegetation index, developed for improving the monitoring of the vegetation growth cycle. The PPI index values, with 5-day satellite revisit cycle, are first used in a function fitting to derive the PPI Seasonal Trajectories, which is a filtered time series with regular 10-day time step. From these Seasonal Trajectories, a suite of 13 Vegetation Phenology and Productivity (VPP) parameters are then computed and provided, for up to two seasons each year. The green-up period slope is one of the 13 parameters. A complementary quality indicator (QFLAG) provides a confidence level, that is described in table 4 of the same manual. The LSLOPE dataset is made available as raster files with 10 x 10m resolution, in UTM/WGS84 projection corresponding to the Sentinel-2 tiling grid, for those tiles that cover the EEA38 countries and the United Kingdom and for two seasons in each year from 2017 onwards. It is updated in the first quarter of each year.