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GHSL: Degree of Urbanization 1975-2030 V2-0 (P2023A)
Cet ensemble de données raster représente une classification rurale-urbaine mondiale multitemporelle, en appliquant la méthodologie de l'étape I du "Degré d'urbanisation" recommandée par la Commission statistique des Nations Unies, sur la base des données de population globale en grille et de surface bâtie générées par le projet GHSL pour les époques 1975-2030 à intervalles de cinq ans. Le diplôme… ghsl jrc population sdg settlement -
GHSL: hauteur des bâtiments dans le monde en 2018 (P2023A)
Cet ensemble de données raster spatial représente la répartition mondiale des hauteurs de bâtiments avec une résolution de 100 m, pour l'année 2018. Les données d'entrée utilisées pour prédire la hauteur des bâtiments sont le modèle de surface numérique global ALOS (30 m), la mission topographique Shuttle Radar de la NASA, etc. alos building built built-environment builtup copernicus -
GHSL: Volume mondial de construction 1975-2030 (P2023A)
Ce jeu de données raster représente la distribution mondiale du volume des bâtiments, exprimé en mètres cubes par cellule de grille de 100 m. Le jeu de données mesure le volume total des bâtiments et le volume des bâtiments alloué aux cellules de grille à usage principalement non résidentiel (NRES). Les estimations sont basées sur les données cumulées … alos building built-environment copernicus dem ghsl -
GHSL: surface bâtie mondiale 10 m (P2023A)
Cet ensemble de données raster représente la distribution des surfaces urbanisées, exprimée en mètres carrés par cellule de grille de 10 m, pour l'année 2018, telle qu'elle ressort des données d'image S2. Les ensembles de données mesurent: a) la surface bâtie totale et b) la surface bâtie allouée aux cellules de grille de … built built-environment builtup copernicus ghsl jrc -
GHSL: surface bâtie mondiale 1975-2030 (P2023A)
Ce jeu de données raster représente la distribution des surfaces urbanisées, exprimée en mètres carrés par cellule de grille de 100 m. Le jeu de données mesure: a) la surface bâtie totale et b) la surface bâtie allouée aux cellules de grille à usage non résidentiel (NRES) prédominant. Les données sont interpolées spatialement et temporellement ou… built built-environment builtup copernicus ghsl jrc -
GHSL: surfaces de population mondiale 1975-2030 (P2023A)
Cet ensemble de données raster représente la distribution spatiale de la population résidentielle, exprimée en nombre absolu d'habitants de la cellule. Les estimations de la population résidentielle entre 1975 et 2020 par tranches de cinq ans et les projections à l'horizon 2025 et 2030 issues de CIESIN GPWv4.11 ont été ventilées à partir de données de recensement ou … ghsl jrc population sdg -
GHSL: Global settlement characteristics (10 m) 2018 (P2023A)
Ce jeu de données raster spatial délimite les établissements humains à une résolution de 10 m et décrit leurs caractéristiques internes en termes de composants fonctionnels et liés à la hauteur de l'environnement bâti. Pour en savoir plus sur les produits de données GHSL, consultez le rapport "GHSL Data Package 2023" (Paquet de données GHSL 2023)… building built builtup copernicus ghsl height
Datasets tagged ghsl in Earth Engine
[null,null,[],[[["\u003cp\u003eThe GHSL datasets provide a global, multi-temporal view of human settlements, including building heights, built-up surfaces, and population distribution.\u003c/p\u003e\n"],["\u003cp\u003eBuilding characteristics are available at 10m resolution, while building heights, volumes, and population are provided at 100m resolution.\u003c/p\u003e\n"],["\u003cp\u003eThe datasets cover a range of time periods, including historical data from 1975 to present and projections for future years.\u003c/p\u003e\n"],["\u003cp\u003eData sources include satellite imagery such as Sentinel-2 and ALOS, as well as census data and other global datasets like CIESIN GPWv4.11.\u003c/p\u003e\n"],["\u003cp\u003eThe GHSL datasets support various applications like urban planning, disaster risk assessment, and monitoring sustainable development goals.\u003c/p\u003e\n"]]],["The content describes multiple Global Human Settlement Layer (GHSL) datasets, each focused on different aspects of human settlements. These datasets include: settlement characteristics, building height, built-up surface area (at 10m and 100m), building volume, population distribution, and degree of urbanization. The data spans from 1975 to 2030, providing historical data and projections, all derived from satellite imagery and census information. Each dataset measures in square or cubic meters.\n"],null,["# Datasets tagged ghsl in Earth Engine\n\n-\n\n |------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Degree of Urbanization 1975-2030 V2-0 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_SMOD_V2-0) |\n | 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 ... |\n | [ghsl](/earth-engine/datasets/tags/ghsl) [jrc](/earth-engine/datasets/tags/jrc) [population](/earth-engine/datasets/tags/population) [sdg](/earth-engine/datasets/tags/sdg) [settlement](/earth-engine/datasets/tags/settlement) |\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global building height 2018 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_H) |\n | 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 ... |\n | [alos](/earth-engine/datasets/tags/alos) [building](/earth-engine/datasets/tags/building) [built](/earth-engine/datasets/tags/built) [built-environment](/earth-engine/datasets/tags/built-environment) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) |\n\n-\n\n |----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global building volume 1975-2030 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_V) |\n | 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 ... |\n | [alos](/earth-engine/datasets/tags/alos) [building](/earth-engine/datasets/tags/building) [built-environment](/earth-engine/datasets/tags/built-environment) [copernicus](/earth-engine/datasets/tags/copernicus) [dem](/earth-engine/datasets/tags/dem) [ghsl](/earth-engine/datasets/tags/ghsl) |\n\n-\n\n |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global built-up surface 10m (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_S_10m) |\n | 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 ... |\n | [built](/earth-engine/datasets/tags/built) [built-environment](/earth-engine/datasets/tags/built-environment) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) [ghsl](/earth-engine/datasets/tags/ghsl) [jrc](/earth-engine/datasets/tags/jrc) |\n\n-\n\n |--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global built-up surface 1975-2030 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_S) |\n | 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 ... |\n | [built](/earth-engine/datasets/tags/built) [built-environment](/earth-engine/datasets/tags/built-environment) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) [ghsl](/earth-engine/datasets/tags/ghsl) [jrc](/earth-engine/datasets/tags/jrc) |\n\n-\n\n |-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global population surfaces 1975-2030 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_POP) |\n | 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 ... |\n | [ghsl](/earth-engine/datasets/tags/ghsl) [jrc](/earth-engine/datasets/tags/jrc) [population](/earth-engine/datasets/tags/population) [sdg](/earth-engine/datasets/tags/sdg) |\n\n-\n\n |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### GHSL: Global settlement characteristics (10 m) 2018 (P2023A)](/earth-engine/datasets/catalog/JRC_GHSL_P2023A_GHS_BUILT_C) |\n | 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 ... |\n | [building](/earth-engine/datasets/tags/building) [built](/earth-engine/datasets/tags/built) [builtup](/earth-engine/datasets/tags/builtup) [copernicus](/earth-engine/datasets/tags/copernicus) [ghsl](/earth-engine/datasets/tags/ghsl) [height](/earth-engine/datasets/tags/height) |"]]