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GHSL: Global building height 2018 (P2023A)
Dieser räumliche Rasterdatensatz zeigt die globale Verteilung der Gebäudehöhen mit einer Auflösung von 100 m für das Jahr 2018. Die Eingabedaten zur Vorhersage der Gebäudehöhen sind das ALOS Global Digital Surface Model (30 m), die NASA Shuttle Radar Topographic Mission … alos building built built-environment builtup copernicus -
GHSL: Global building volume 1975-2030 (P2023A)
Dieser Rasterdatensatz stellt die globale Verteilung des Gebäudevolumens in Kubikmetern pro 100 m²-Rasterzelle dar. Der Datensatz misst das Gesamtvolumen des Gebäudes und das Gebäudevolumen, das den Rasterzellen mit überwiegend gewerblicher Nutzung (NRES) zugewiesen ist. Die Schätzungen basieren auf dem … alos building built-environment copernicus dem ghsl -
GHSL: Global settlement characteristics (10 m) 2018 (P2023A)
Dieser räumliche Rasterdatensatz zeigt menschliche Siedlungen mit einer Auflösung von 10 m und beschreibt ihre inneren Merkmale in Bezug auf die funktionalen und höhenbezogenen Komponenten der bebauten Umwelt. Weitere Informationen zu den GHSL-Datenprodukten finden Sie im Bericht „GHSL Data Package 2023“ (GHSL-Datenpaket 2023)… building built builtup copernicus ghsl height -
Open Buildings V3-Polygone
Dieser groß angelegte offene Datensatz besteht aus Gebäudeumrissen, die aus hochauflösenden 50-cm-Satellitenbildern abgeleitet wurden. Sie enthält 1,8 Milliarden Gebäudeerkennungen in Afrika, Lateinamerika, der Karibik, Süd- und Südostasien. Die Inferenz umfasste eine Fläche von 58 Millionen km². Für jedes Gebäude in diesem Datensatz… africa asia building built-up open-buildings 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) |"]]