This metadata refers to the Quality Flag (QFLAG2) 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 Quality Flag (QFLAG2) is a quality indicator that assists users with the screening of clouds, shadows from clouds and topography, other dark areas, snow and water surfaces in their analysis of the four related Vegetation Indices datasets: the Plant Phenology Index (PPI), the Normalized Difference Vegetation Index (NDVI), the Leaf Area Index (LAI) and the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). The QFLAG2 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.

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 Coastal Zones LC/LU Change (CZC) 2012-2018 is providing the Land Cover / Land Use (LC/ LU) change for areas along the coastline of the EEA38 countries and the United Kingdom, between the reference years 2012 and 2018. The Coastal Zones product monitors landscape dynamics in European coastal territory to an inland depth of 10 km with a total area of approximately 730,000 km², with all the relevant areas (estuaries, coastal lowlands, nature reserves). The production of the coastal zone layers was coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme, as part of the Copernicus Land Monitoring Service (CLMS) Local Component. The Coastal Zones Change product covers a buffer zone of coastline derived from EU-Hydro v1.1. The Land Cover/Land Use (LC/LU) Change layer is extracted from Very High Resolution (VHR) satellite data and other available data. The reference years for the change are 2012 and 2018. The class definitions follow the pre-defined nomenclature on the basis of Mapping and Assessment of Ecosystems and their Services (MAES) typology of ecosystems (Level 1 to Level 4) and CORINE Land Cover adapted to the specific characteristics of coastal zones. The classification provides 71 distinct thematic classes with a Minimum Mapping Unit (MMU) of 0.5 ha and a Minimum Mapping Width (MMW) of 10 m. The status product is available for the 2012 and 2018 reference years. This CZC dataset is distributed in vector format, in a single OGC GeoPackage file covering the area of interest.

The Impervious Built-Up (IBU) 2024 layer is part of the High Resolution Layer (HRL) Imperviousness and provides binary information of built-up areas (class 1) and non built-up areas (class 0) for the reference year 2024 as derived from Sentinel-2 image time series. 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 10-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.

The High Resolution Layer Grassland Mowing Events (GRAME) raster product provides a basic land cover classification containing respectively the number of grassland mowing events within the detected Herbaceous cover layer (temporal and permanent grassland)) with a Minimum Mapping Unit (MMU) of 0.25 ha. The GRAME product will flag and map the number of mowing events (1, 2, 3, or 4+) on temporary or permanent grassland detected per year. 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 Grasslands 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 High Resolution Layer Cropping Patterns - Bare Soil After (CPBSA) raster product provides bare soil period (in days) after the harvest of the main annual crop. Note that the bare soil period cannot transcend the calendar year for which the product is generated. 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 Season Maximum Value (MAXV), 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 Season Maximum Value (MAXV) provides the maximum (peak) value that the Plant Phenology Index (PPI) reaches during 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 Season Maximum 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 MAXV 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 Impervious Built-Up (IBU) 2021 layer is part of the High Resolution Layer (HRL) Imperviousness and provides binary information of built-up areas (class 1) and non built-up areas (class 0) for the reference year 2021 as derived from Sentinel-2 image time series. 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 10-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.

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 High Resolution Layer Cropping Patterns - Secondary Crop Duration (CPSCD) raster product provides the duration (in days) of the cover crop season (can exceed the calendar year). 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)