Keyword

Geoscientific information

29 record(s)
 
Type of resources
Available actions
Topics
INSPIRE themes
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
status
Scale
Resolution
From 1 - 10 / 29
  • To meet the demand for statistics at a local level, Eurostat maintains a system of Local Administrative Units (LAUs) compatible with NUTS. These LAUs are the building blocks of the NUTS, and comprise the municipalities and communes of the European Union. The LAUs are: - administrative for reasons such as the availability of data and policy implementation capacity; - a subdivision of the NUTS 3 regions covering the whole economic territory of the Member States; - appropriate for the implementation of local level typologies included in TERCET, namely the coastal area and DEGURBA classification. Since there are frequent changes to the LAUs, Eurostat publishes an updated list towards the end of each year. The LAUs are currently available from 2011 onwards. The NUTS regulation makes provision for EU Member States to send the lists of their LAUs to Eurostat. If available, Eurostat receives additionally basic administrative data by means of the annual LAU lists, namely total population and total area for each LAU.

  • This data set contains the administrative boundaries at country level of the world and is based on the geometry from EBM v12.x. of EuroGeographics for the members of Eurogeographics, the Global Administrative Units Layer (2015) from FAO (UN) and geometry from the Turkish National Statistical Office. This dataset consists of 2 feature classes (regions, boundaries) per scale level and there are 6 different scale levels (100K, 1M, 3M, 10M, 20M and 60M). The public data set (1M - 60M) is available under the Download link indicated below. The full data set (100K - 60M) GISCO.CNTR_2016 is available via the EC restricted download link.

  • The Land Cover Map of Europe 2017 is a product resulting from the Phase 2 of the S2GLC project. The final map has been produced on the CREODIAS platform with algorithms and software developed by CBK PAN. Classification of over 15 000 Sentinel-2 images required high level of automation that was assured by the developed software. The legend of the resulting Land Cover Map of Europe 2017 consists of 13 land cover classes. The pixel size of the map equals 10 m, which corresponds to the highest spatial resolution of Sentinel-2 imagery. Its overall accuracy was estimated to be at the level of 86% using approximately 52 000 validation samples distributed across Europe. Related publication: https://doi.org/10.3390/rs12213523

  • This data set contains the administrative boundaries at country level of the world and is based on the geometry from EBM v2020 (ReferenceDate 31.12.2018) of EuroGeographics for the members of Eurogeographics, and GISCO Countries 2020. This dataset consists of 2 feature classes (regions, boundaries) per scale level and there are 6 different scale levels (100K, 1M,3M, 10M, 20M and 60M). The public data set (1M - 60M) is available under the Download link indicated below. The full data set (100K - 60M) GISCO.CNTR_2020 is available via the EC restricted download link.

  • The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. We provide two instances of Copernicus DEM named GLO-30 Public and GLO-90. GLO-90 provides worldwide coverage at 90 meters. GLO-30 Public provides limited worldwide coverage at 30 meters because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. Note that in both cases ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Two releases (i.e. 2019 and 2020) are currently available for all Copernicus DEM instances with the exception of COP-DEM_GLO-30-DTED_PUBLIC and COP-DEM_GLO-30-DGED_PUBLIC, only available as 2019 release. A full collection of tiles per each release can be found via FTP and PANDA Catalogue under dataset names marked with “2019_1” and “2020_1”. The 2020 release has undergone the following improvements with respect to the 2019 release: - infilling with high resolution DEM over Norway; - addition of 5 geocells containing missing small islands; - editing of source raw data; - correction of minor data/auxiliary files inconsistencies; - correction of implausible values. The products impacted by improvements can be identified via a dedicated list: https://spacedata.copernicus.eu/documents/20126/0/COP-DEM_delivery_sheet_v0.7_PUBLIC+%282%29.xlsx/771ce82f-0084-849d-8a34-702c421eacf2?t=1611651454540

  • Categories  

    Modified Normalized Difference Water Index (MNDWI) from MODIS data for Europe at 1 km resolution. Source data: - MODIS/Terra Surface Reflectance 8-Day L3 Global 500 m SIN Grid (MOD09A1 v006): https://lpdaac.usgs.gov/products/mod09a1v006/ The corresponding MODIS/Aqua product (MYD09A1 v006) could not be used due to the fact that the Aqua satellite has a number of broken detectors resulting in unreliable data for band 6 (SWIR) measurements. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra MOD09A1 Version 6 product provides an estimate of the surface spectral reflectance of Terra MODIS Bands 1 through 7 corrected for atmospheric conditions such as gasses, aerosols, and Rayleigh scattering. Along with the seven 500 meter (m) reflectance bands are two quality layers and four observation bands. For each pixel, a value is selected from all the acquisitions within the 8-day composite period. The criteria for the pixel choice include cloud and solar zenith. When several acquisitions meet the criteria the pixel with the minimum channel 3 (blue) value is used. For the time periods October 2016 - March 2017 and August 2020 - April 2021, the original data has been reprojected to ETRS89-extended / LAEA Europe and aggregated to a 1 km grid. The temporal resolution is 8 days. Bad quality pixels (cloud, cloud shadow, dead detector, solar zenith angle too large, etc.) have been masked using the provided quality assurance (QA) layers and appear as "no data". File naming: productCode.acquisitionDate[A (YYYYDDD)]_mosaic_spatialResolution_frequency_VI.tif example: MOD09A1.A2016353_mosaic_1000m_8_days_MNDWI.tif The date is Year and Day of Year. Values are MNDWI * 10000. Example: Value -5099 = -0.5099

  • Categories  

    Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from MODIS data for Europe at 1 km resolution. Source data: - MODIS/Terra Vegetation Indices 16-Day L3 Global 500 m SIN Grid (MOD13A1 v006): https://lpdaac.usgs.gov/products/mod13a1v006/ - MODIS/Aqua Vegetation Indices 16-Day L3 Global 500 m SIN Grid (MYD13A1 v006): https://lpdaac.usgs.gov/products/myd13a1v006/ The MOD/MYD13A1 Version 6 product provide Vegetation Index (VI) values at a per pixel basis at 500 meter (m) spatial resolution. There are two primary vegetation layers. The first is the Normalized Difference Vegetation Index (NDVI), which is referred to as the continuity index to the existing National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) derived NDVI. The second vegetation layer is the Enhanced Vegetation Index (EVI), which has improved sensitivity over high biomass regions. The algorithm for this product chooses the best available pixel value from all the acquisitions from the 16 day period. The criteria used is low clouds, low view angle, and the highest NDVI/EVI value. For the time periods October 2016 - March 2017 and August 2020 - April 2021, the original data has been reprojected to ETRS89-extended / LAEA Europe and aggregated to a 1 km grid. The temporal resolution is 16 days. Bad quality pixels or pixels with snow/ice and/or cloud cover have been masked using the provided quality assurance (QA) layers and appear as "no data". File naming: productCode.acquisitionDate[A (YYYYDDD)]_mosaic_spatialResolution_frequency_VI.tif example: MOD13A1.A2020305_mosaic_1000m_16_days_NDVI.tif The date is Year and Day of Year. Values are NDVI/EVI * 10000. Example: Value 6473 = 0.6473

  • The Earth Observations Group (EOG) is producing a version 1 suite of average radiance composite images using nighttime data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB). Prior to averaging, the DNB data is filtered to exclude data impacted by stray light, lightning, lunar illumination, and cloud-cover. Cloud-cover is determined using the VIIRS Cloud Mask product (VCM). In addition, data near the edges of the swath are not included in the composites (aggregation zones 29-32). Temporal averaging is done on a monthly and annual basis. The version 1 series of monthly composites has not been filtered to screen out lights from aurora, fires, boats, and other temporal lights. However, the annual composites have layers with additional separation, removing temporal lights and background (non-light) values. The version 1 products span the globe from 75N latitude to 65S. The products are produced in 15 arc-second geographic grids and are made available in geotiff format as a set of 6 tiles. The tiles are cut at the equator and each span 120 degrees of latitude. Each tile is actually a set of images containing average radiance values and numbers of available observations. In the monthly composites, there are many areas of the globe where it is impossible to get good quality data coverage for that month. This can be due to cloud-cover, especially in the tropical regions, or due to solar illumination, as happens toward the poles in their respective summer months. Therefore, it is imperative that users of these data utilize the cloud-free observations file and not assume a value of zero in the average radiance image means that no lights were observed. The version 1 monthly series is run globally using two different configurations. The first excludes any data impacted by stray light. The second includes these data if the radiance vales have undergone the stray-light correction procedure (Reference). These two configurations are denoted in the filenames as "vcm" and "vcmsl" respectively. The "vcmsl" version, that includes the stray-light corrected data, will have more data coverage toward the poles, but will be of reduced quality. It is up to the users to determine which set is best for their applications. The annual versions are only made with the “vcm” version, excluding any data impacted by stray light. Filenaming convention: The version 1 composite products have 7 filename fields that are separated by an underscore "_". Internal to each field there can be an additional dash separator "-". These fields are followed by a filename extension. The fields are described below using this example filename: SVDNB_npp_20140501-20140531_global_vcmcfg_v10_c201502061154.avg_rade9 Field 1: VIIRS SDR or Product that made the composite "SVDNB" Field 2: satellite name "npp" Field 3: date range "20140501-20140531" Field 4: ROI "global" Field 5: config shortname "vcmcfg" Field 6: version "v10" is version 1.0 Field 7: creation date/time Extension: avg_rade9 The annual products can have other values for the config shortname (Field 5). They are: "vcm-orm" (VIIRS Cloud Mask - Outlier Removed) This product contains cloud-free average radiance values that have undergone an outlier removal process to filter out fires and other ephemeral lights. "vcm-orm-ntl" (VIIRS Cloud Mask - Outlier Removed - Nighttime Lights) This product contains the "vcm-orm" average, with background (non-lights) set to zero. "vcm-ntl" (VIIRS Cloud Mask - Nighttime Lights) This product contains the "vcm" average, with background (non-lights) set to zero. Data types/formats: To reach the widest community of users, files are delivered in compressed tarballs, each containing a set of 2 geotiffs. Files with extensions "avg_rade9" contain floating point radiance values with units in nanoWatts/cm2/sr. Note that the original DNB radiance values have been multiplied by 1E9. This was done to alleviate issues some software packages were having with the very small numbers in the original units. Files with extension "cf_cvg" are integer counts of the number of cloud-free coverages, or observations, that went in to constructing the average radiance image. Files with extension “cvg” are integer counts of the number of coverages or total observations available (regardless of cloud-cover). Credit: When using the data please credit the product generation to the Earth Observation Group, Payne Institute for Public Policy.

  • Base epoch 2015 from the Collection 3 of annual, global 100m land cover maps. Other available (consolidated) epochs: 2016 2017 2018 2019 Produced by the global component of the Copernicus Land Service, derived from PROBA-V satellite observations and ancillary datasets. The maps include: - a main discrete classification with 23 classes aligned with UN-FAO's Land Cover Classification System, - a set of versatile cover fractions: percentage (%) of ground cover for the 10 main classes - - a forest type layer quality layers on input data density Online map viewer: https://lcviewer.vito.be

  • Overview: The Essential Climate Variables for assessment of climate variability from 1979 to present dataset contains a selection of climatologies, monthly anomalies and monthly mean fields of Essential Climate Variables (ECVs) suitable for monitoring and assessment of climate variability and change. Selection criteria are based on accuracy and temporal consistency on monthly to decadal time scales. The ECV data products in this set have been estimated from climate reanalyses ERA-Interim and ERA5, and, depending on the source, may have been adjusted to account for biases and other known deficiencies. Data sources and adjustment methods used are described in the Product User Guide, as are various particulars such as the baseline periods used to calculate monthly climatologies and the corresponding anomalies. Surface air relative humidity: The ratio of the partial pressure of water vapour to the equilibrium vapour pressure of water at the same temperature near the surface. Spatial resolution: 0:15:00 (0.25°) Temporal resolution: monthly Temporal extent: 1979 - present Data unit: percent * 10 Data type: UInt8 CRS as EPSG: EPSG:4326 Processing time delay: one month