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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: 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: 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 -
Empreinte mondiale des établissements humains 2015
L'empreinte urbaine mondiale (EUM) 2015 est un masque binaire de résolution de 10 m qui délimite l'étendue des établissements humains à l'échelle mondiale, dérivé à partir d'images Landsat-8 et Sentinel-1 multitemporelles de 2014 à 2015 (environ 217 000 et 107 000 scènes ont été traitées, respectivement). La dynamique temporelle des établissements humains … landcover landsat-derived population sentinel1-derived settlement urban
Datasets tagged settlement in Earth Engine
[null,null,[],[[["\u003cp\u003eThe World Settlement Footprint 2015 dataset provides a global, 10m resolution binary mask showing the extent of human settlements using 2014-2015 Landsat-8 and Sentinel-1 imagery.\u003c/p\u003e\n"],["\u003cp\u003eThe GHSL datasets offer various perspectives on global built-up areas, including settlement characteristics, built-up surface extent over time, and degree of urbanization.\u003c/p\u003e\n"],["\u003cp\u003eGHSL data is available at different resolutions (10m and 100m) and provides insights into built-up surface area and functional characteristics like building height and residential/non-residential use.\u003c/p\u003e\n"],["\u003cp\u003eThe Degree of Urbanization dataset from GHSL classifies areas globally as rural or urban using a multitemporal approach and gridded population and built-up surface data.\u003c/p\u003e\n"],["\u003cp\u003eThese datasets are derived from various satellite imagery sources including Landsat-8, Sentinel-1, and Sentinel-2 and cover different time periods from 1975 to 2030.\u003c/p\u003e\n"]]],[],null,["# Datasets tagged settlement 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 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 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) |\n\n-\n\n |-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n | [### World Settlement Footprint 2015](/earth-engine/datasets/catalog/DLR_WSF_WSF2015_v1) |\n | The World Settlement Footprint (WSF) 2015 is a 10m resolution binary mask outlining the extent of human settlements globally derived by means of 2014-2015 multitemporal Landsat-8 and Sentinel-1 imagery (of which \\~217,000 and \\~107,000 scenes have been processed, respectively). The temporal dynamics of human settlements ... |\n | [landcover](/earth-engine/datasets/tags/landcover) [landsat-derived](/earth-engine/datasets/tags/landsat-derived) [population](/earth-engine/datasets/tags/population) [sentinel1-derived](/earth-engine/datasets/tags/sentinel1-derived) [settlement](/earth-engine/datasets/tags/settlement) [urban](/earth-engine/datasets/tags/urban) |"]]