The Start-of-Season Value (SOSV), 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 Start-of-Season Value (SOSV) provides the value of the Plant Phenology Index (PPI) at the start of the vegetation growing season. 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 Start-of-Season Value 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 SOSV 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 and for two seasons in each year from 2017 onwards. It is updated in the first quarter of each year.

The Seasonal Productivity (SPROD), 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 Seasonal Productivity (SPROD), or small integral, is the growing season integral that is computed as the sum of all daily Plant Phenology Index (PPI) values between the dates of the season start (SOSD) and end (EOSD), minus their base level value. 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 Seasonal Productivity 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 SPROD 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.

The GEBCO_2020 Grid was released in May 2020 and is the second global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid provides global coverage of elevation data in meters on a 15 arc-second grid of 43200 rows x 86400 columns, giving 3,732,480,000 data points. Grid Development The GEBCO_2020 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds. The grid uses as a ‘base’ Version 2 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with the gridded bathymetric data sets developed by the four Seabed 2030 Regional Centers. The Regional Centers have compiled gridded bathymetric data sets, largely based on multibeam data, for their areas of responsibility. These regional grids were then provided to the Global Center. For areas outside of the polar regions (primarily south of 60°N and north of 50°S), these data sets are in the form of 'sparse grids', i.e. only grid cells that contain data were populated. For the polar regions, complete grids were provided due to the complexities of incorporating data held in polar coordinates. The compilation of the GEBCO_2020 Grid from these regional data grids was carried out at the Global Center, with the aim of producing a seamless global terrain model. In contrast to the development of the previous GEBCO grid, GEBCO_2019, the data sets provided as sparse grids by the Regional Centers were included on to the base grid without any blending, i.e. grid cells in the base grid were replaced with data from the sparse grids. This was with aim of avoiding creating edge effects, 'ridges and ripples', at the boundaries between the sparse grids and base grid during the blending process used previously. In addition, this allows a clear identification of the data source within the grid, with no cells being 'blended' values. Routines from Generic Mapping Tools (GMT) system were used to do the merging of the data sets. For the polar data sets, and the adjoining North Sea area, supplied in the form of complete grids these data sets were included using feather blending techniques from GlobalMapper software version 11.0, made available by Blue Marble Geographic. The GEBCO_2020 Grid includes data sets from a number of international and national data repositories and regional mapping initiatives. For information on the data sets included in the GEBCO_2020 Grid, please see the list of contributions included in this release of the grid (https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2020/#compilations).

Corine Land Cover 2018 (CLC2018) 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 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 (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.

This metadata refers to the Plant Phenology Index (PPI) dataset, one of the near real-time (NRT) Vegetation Index products of the pan-European High Resolution Vegetation Phenology and Productivity (HR-VPP), component of the Copernicus Land Monitoring Service (CLMS). The Plant Phenology Index (PPI) is a physically based vegetation index for improved monitoring of plant phenology, that is developed from a simplified solution to the radiative transfer equation by Jin and Eklundh (2014). PPI has a linear relationship with green leaf area index, a strong correlation with gross primary productivity, and is capable of disentangling remotely sensed plant phenology from snow seasonality. It is reported to be superior to other indices for spring phenology retrieval over the northern latitudes and for GPP estimation in African semi-arid ecosystems. Comparison of satellite-derived PPI to ground observations of plant phenology and gross primary productivity (GPP) shows strong similarity of temporal patterns over several Nordic boreal forest sites. The PPI 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 the period from October 2016 until today, with daily updates. Each file has an associated quality indicator (QFLAG2) to assist users with the screening of clouds, shadows from clouds and topography, snow and water surfaces.

The main high resolution grassland product is the Grassland layer, a grassland/non-grassland mask for the EEA39. This grassy and non-woody vegetation baseline product includes all kinds of grasslands: managed grassland, semi-natural grassland and natural grassy vegetation. It is a binary status layer for the 2015 reference year mapping grassland and all non-grassland areas in 20m and (aggregated) 100m pixel size and for the 2018 reference year - in 10m and (aggregated) 100m pixel size. The production of the high resolution grassland layers was coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme.

The main high resolution grassland product is the Grassland layer, a grassland/non-grassland mask for the EEA39. This grassy and non-woody vegetation baseline product includes all kinds of grasslands: managed grassland, semi-natural grassland and natural grassy vegetation. It is a binary status layer for the 2015 reference year mapping grassland and all non-grassland areas in 20m and (aggregated) 100m pixel size and for the 2018 reference year - in 10m and (aggregated) 100m pixel size. The production of the high resolution grassland 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 (HRL) Grassland Change 2015-2018 raster product at 20m resolution provides information on changes in grassland vegetation cover between the reference years 2015 and 2018. The thematic classes indicate all non-grassland areas, grassland gain and grassland loss, unchanged grassland in both years and unverified grassland gain and loss areas for the pan-European area of EEA38 and the United Kingdom. The production of the High Resolution grassland layers was coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme. This dataset is provided as 20 meter rasters in 100 x 100 km tiles grouped according to the EEA38 countries and the United Kingdom (fully conformant with the EEA reference grid). The HRL Grassland layer is the main High Resolution grassland product. This grassy and non-woody vegetation baseline product includes all kinds of grasslands: managed grassland, semi-natural grassland and natural grassy vegetation. It is a binary status layer for the 2015 reference year mapping grassland and all non-grassland areas in 20m and (aggregated) 100m pixel size and, for the 2018 reference year, in 10m and (aggregated) 100m pixel size.

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."