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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: 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 -
Polygones Open Buildings V3
Cet ensemble de données ouvert à grande échelle se compose de contours de bâtiments dérivés d'images satellite haute résolution de 50 cm. Il contient 1,8 milliard de détections de bâtiments en Afrique, en Amérique latine, dans les Caraïbes, en Asie du Sud et en Asie du Sud-Est. L'inférence couvrait une superficie de 58 millions de km². Pour chaque bâtiment de cet ensemble de données : afrique asie bâtiment urbain bâtiments ouverts population
Datasets tagged building in Earth Engine
[null,null,[],[[["\u003cp\u003eThis collection of datasets provides information on building footprints, heights, and volumes across the globe.\u003c/p\u003e\n"],["\u003cp\u003eThe Open Buildings V3 dataset offers high-resolution (50 cm) building outlines for regions in Africa, Latin America, Caribbean, South Asia, and Southeast Asia.\u003c/p\u003e\n"],["\u003cp\u003eThe GHSL datasets present insights into global settlement characteristics, including building heights and volumes, at varying resolutions (10 m and 100 m).\u003c/p\u003e\n"],["\u003cp\u003eBuilding height and volume data are derived from sources like ALOS, SRTM, and the GHSL built-up layer, enabling analysis of built environments worldwide.\u003c/p\u003e\n"]]],["The content describes four datasets focused on building data. One dataset, \"Open Buildings V3 Polygons,\" provides 1.8 billion building outlines derived from 50 cm satellite imagery across Africa, Latin America, the Caribbean, and South and Southeast Asia. The other three, from GHSL, provide spatial raster data describing human settlements at 10m resolution with functional and height characteristics; global building heights at 100m resolution; and global building volume from 1975-2030 in cubic meters.\n"],null,["# Datasets tagged building in Earth Engine\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 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 | [### Open Buildings V3 Polygons](/earth-engine/datasets/catalog/GOOGLE_Research_open-buildings_v3_polygons) |\n | This large-scale open dataset consists of outlines of buildings derived from high-resolution 50 cm satellite imagery. It contains 1.8B building detections in Africa, Latin America, Caribbean, South Asia and Southeast Asia. The inference spanned an area of 58M km². For each building in this dataset ... |\n | [africa](/earth-engine/datasets/tags/africa) [asia](/earth-engine/datasets/tags/asia) [building](/earth-engine/datasets/tags/building) [built-up](/earth-engine/datasets/tags/built-up) [open-buildings](/earth-engine/datasets/tags/open-buildings) [population](/earth-engine/datasets/tags/population) |"]]