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EUCROPMAP
European crop type map based on Sentinel-1 and LUCAS Copernicus 2018 in-situ observations for 2018; and one based on Sentinel-2 and LUCAS Copernicus 2022 for 2022. Capitalizing on the unique LUCAS 2018 Copernicus in-situ survey, the 2018 dataset is the first continental crop type map … crop eu jrc lucas sentinel1-derived -
EC JRC global map of forest cover 2020, V2
The global map of forest cover provides a spatially explicit representation of forest presence and absence for the year 2020 at 10m spatial resolution. The year 2020 corresponds to the cut-off date of the Regulation from the European Union "on the making available on the … eudr forest jrc -
Global map of forest types 2020
The global map of forest types provides a spatially explicit representation of primary forest, naturally regenerating forest and planted forest (including plantation forest) for the year 2020 at 10m spatial resolution. The base layer for mapping these forest types is the extent of forest cover … eudr forest jrc landcover primary-forest -
GHSL: Global settlement characteristics (10 m) 2018 (P2023A)
This spatial raster dataset delineates human settlements at 10 m resolution, and describes their inner characteristics in terms of the functional and height-related components of the built environment. More information about the GHSL data products can be found in the GHSL Data Package 2023 report … building built builtup copernicus ghsl height -
GHSL: Global building height 2018 (P2023A)
This spatial raster dataset depicts the global distribution of building heights at a resolution of 100 m, referred to the year 2018. The input data used to predict building heights are the ALOS Global Digital Surface Model (30 m), the NASA Shuttle Radar Topographic Mission … alos building built built-environment builtup copernicus -
GHSL: Global built-up surface 1975-2030 (P2023A)
This raster dataset depicts the distribution of built-up surfaces, expressed in square metres per 100 m grid cell. The dataset measures: a) the total built-up surface, and b) the built-up surface allocated to grid cells of predominant non-residential (NRES) use. Data are spatially-temporally interpolated or … built built-environment builtup copernicus ghsl jrc -
GHSL: Global built-up surface 10m (P2023A)
This raster dataset depicts the distribution of built-up surfaces, expressed in square metres per 10 m grid cell, for 2018 as observed from the S2 image data. The datasets measure: a) the total built-up surface, and b) the built-up surface allocated to grid cells of … built built-environment builtup copernicus ghsl jrc -
GHSL: Global building volume 1975-2030 (P2023A)
This raster dataset depicts the global distribution of building volume, expressed in cubic metres per 100 m grid cell. The dataset measures the total building volume and the building volume allocated to grid cells of predominant non-residential (NRES) use. Estimates are based on the built-up … alos building built-environment copernicus dem ghsl -
GHSL: Global population surfaces 1975-2030 (P2023A)
This raster dataset depicts the spatial distribution of residential population, expressed as the absolute number of inhabitants of the cell. Residential population estimates between 1975 and 2020 in 5-year intervals and projections to 2025 and 2030 derived from CIESIN GPWv4.11 were disaggregated from census or … ghsl jrc population sdg -
GHSL: Degree of Urbanization 1975-2030 V2-0 (P2023A)
This raster dataset represents a global, multitemporal rural-urban classification, applying the "Degree of Urbanisation" stage I methodology recommended by UN Statistical Commission, based on global gridded population and built-up surface data generated by the GHSL project for the epochs 1975-2030 in 5-year intervals. The Degree … ghsl jrc sdg settlement -
JRC Global Surface Water Mapping Layers, v1.2 [deprecated]
This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2019 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its … geophysical google jrc landsat-derived surface water -
JRC Global Surface Water Mapping Layers, v1.4
This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its … change-detection geophysical google jrc landsat-derived surface -
JRC Global Surface Water Metadata, v1.4
This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its … geophysical google jrc landsat-derived surface water -
JRC Monthly Water History, v1.4
This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its … geophysical google history jrc landsat-derived monthly -
JRC Monthly Water Recurrence, v1.4
This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its … geophysical google history jrc landsat-derived monthly -
JRC Yearly Water Classification History, v1.4
This dataset contains maps of the location and temporal distribution of surface water from 1984 to 2021 and provides statistics on the extent and change of those water surfaces. For more information see the associated journal article: High-resolution mapping of global surface water and its … annual geophysical google history jrc landsat-derived -
LUCAS Copernicus (Polygons with attributes, 2018) V1
The Land Use/Cover Area frame Survey (LUCAS) in the European Union (EU) was set up to provide statistical information. It represents a triennial in-situ landcover and land-use data-collection exercise that extends over the whole of the EU's territory. LUCAS collects information on land cover and … copernicus eu jrc landcover landuse lucas -
LUCAS Harmonized (Theoretical Location, 2006-2018) V1
The Land Use/Cover Area frame Survey (LUCAS) in the European Union (EU) was set up to provide statistical information. It represents a triennial in-situ landcover and land-use data-collection exercise that extends over the whole of the EU's territory. LUCAS collects information on land cover and … eu jrc landcover landuse lucas table -
Accessibility to Cities 2015
This global accessibility map enumerates land-based travel time to the nearest densely-populated area for all areas between 85 degrees north and 60 degrees south for a nominal year 2015. Densely-populated areas are defined as contiguous areas with 1,500 or more inhabitants per square kilometer or … accessibility jrc map oxford twente -
Accessibility to Healthcare 2019
This global accessibility map enumerates land-based travel time (in minutes) to the nearest hospital or clinic for all areas between 85 degrees north and 60 degrees south for a nominal year 2019. It also includes "walking-only" travel time, using non-motorized means of transportation only. Major … accessibility jrc map oxford twente -
Global Friction Surface 2019
This global friction surface enumerates land-based travel speed for all land pixels between 85 degrees north and 60 degrees south for a nominal year 2019. It also includes "walking-only" travel speed, using non-motorized means of transportation only. This map was produced through a collaboration between … accessibility jrc map oxford twente
[null,null,[],[[["This collection provides a variety of JRC datasets, including global and European maps of forest cover, forest types, crop types, surface water, and settlement characteristics."],["The datasets utilize various satellite data sources such as Sentinel-1, Sentinel-2, Landsat, and ALOS, along with in-situ observations like LUCAS Copernicus."],["Many datasets offer multi-temporal analysis capabilities, showcasing changes and trends over time, for example, built-up surfaces from 1975 to 2030 and surface water from 1984 to 2021."],["Several datasets provide insights into human impact and accessibility, including population distribution, degree of urbanization, and travel time to cities and healthcare."],["These datasets are valuable for environmental monitoring, urban planning, and research purposes, offering detailed information on land cover, land use, and human settlements."]]],[]]