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GHSL: Global building height 2018 (P2023A)
Ten przestrzenny raster danych przedstawia globalny rozkład wysokości budynków w rozdzielczości 100 m w 2018 r. Dane wejściowe używane do przewidywania wysokości budynków to globalny cyfrowy model powierzchni ALOS (30 m), misja radarowa NASA … alos building built built-environment builtup copernicus -
GHSL: Globalny wolumen budynków w latach 1975–2030 (P2023A)
Ten zbiór danych rastrowych przedstawia globalny rozkład objętości budynków wyrażonej w metrach sześciennych na komórkę siatki o wymiarach 100 m. Zestaw danych mierzy łączną objętość budynku oraz objętość budynku przypisaną do komórek siatki o przeważającym przeznaczeniu niemieszkalnym (NRES). Prognozy są obliczane na podstawie skumulowanych … alos building built-environment copernicus dem ghsl -
GHSL: Global settlement characteristics (10 m) 2018 (P2023A)
Ten zbiór danych rastrowych przestrzennych przedstawia podział na osiedla ludzkie o rozdzielczości 10 m i charakteryzuje ich cechy wewnętrzne pod kątem komponentów funkcjonalnych i wysokościowych środowiska zabudowanego. Więcej informacji o produktach danych GHSL znajdziesz w raporcie GHSL Data Package 2023… budynek zbudowany zabudowany copernicus ghsl wysokość -
Otwarte wielokąty budynków V3
Ten duży, otwarty zbiór danych zawiera kontury budynków utworzone na podstawie zdjęć satelitarnych w wysokiej rozdzielczości 50 cm. Zawiera 1,8 mld wykryć budynków w Afryce, Ameryce Łacińskiej, na Karaibach, w Azji Południowej i Południowo-Wschodniej. Wniosek obejmował obszar 58 mln km². W przypadku każdego budynku w tym zbiorze danych… 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) |"]]