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GeoTIFF

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  • Categories  

    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).

  • Categories  

    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.

  • Categories  

    The dataset provides supporting groundwater depth values as a supplement to the mapping of potential groundwater flooding hazard areas in Denmark. The dataset shows the depth to the projected typical winter groundwater table in metres below terrain for the period 2071-2100 under the RCP8.5 emissions scenario. The depth values can be used to interpret and add detail to the potential hazard areas, including how close the groundwater table is expected to be to the terrain surface. The dataset is provided as raster data with a spatial resolution of 10 × 10 m.

  • Categories  

    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.

  • Categories  

    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.

  • Categories  

    The Wet/Dry Snow (WDS) product is generated in near real-time at European scale based on C-band SAR satellite data from the Sentinel-1 constellation within the fractional snow cover on top of canopy (FSCTOC) derived from overlapping optical satellite data from the Sentinel-2 constellation. The product provides the snow state condition (wet / dry) for surfaces covered by snow (FSCTOC >= 90%) for non-forested land areas with a spatial resolution of 60 m x 60 m. Urban areas, forest and water bodies as well as clouds and cloud shadows from the S2 based FSCTOC product of the same date are masked. WDS 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 WDS product is distributed in raster files covering an area of 110 km by 110 km with a pixel size of 60 m by 60 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.

  • Categories  

    The pan-European High Resolution (HR) Image Mosaic 2006 provides HR2 (High Resolution: 20 meter) coverage over Europe. The surface covered by the image dataset is 5.8 million square kilometres and has a spatial resolution of 20 meters. The imagery is composed during specific acquisition windows between 2005 and 2007. Images are derived from the following satellite sensors: Resourcesat-1 SPOT-4/-5 The mosaic primarily is used as input data in the production of various Copernicus Land Monitoring Service (CLMS) datasets and services, such as land cover maps and high resolution layers on land cover characteristic and can be also useful for CLMS users for visualizations and classifications on land. The input imagery for the creation of the mosaic is provided by ESA. Due to license restrictions, HR Image Mosaic 2006 is only available as a web service (WMS), and not for data download.

  • Categories  

    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.

  • Categories  

    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 and 2015 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 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.

  • Categories  

    The High Resolution Layer Imperviousness Change (IMC) 2015-2018 is a 20m raster dataset showing change in imperviousness between 2015 and 2018 reference years, produced 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. This dataset is provided as 20 meter rasters (fully conformant with EEA reference grid) in 100 x 100 km tiles grouped according to the EEA38 countries and the United Kingdom.