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GHSL:2018 年全球建筑物高度 (P2023A)
此空间栅格数据集描绘了 2018 年建筑高度的全球分布情况,分辨率为 100 米。用于预测建筑高度的输入数据包括 ALOS 全球数字地表模型 (30 米)、NASA 航天飞机雷达地形测绘任务… alos building built built-environment builtup copernicus -
GHSL:1975-2030 年全球建筑体量 (P2023A)
此光栅数据集描绘了建筑体积的全球分布情况,以每 100 米网格单元格的立方米数表示。该数据集衡量了建筑物总体积以及分配给主要用于非住宅用途 (NRES) 的网格单元的建筑体积。估算值基于积累的… alos building built-environment copernicus dem ghsl -
GHSL:2018 年全球结算特征(10 米)(P2023A)
此空间栅格数据集以 10 米的分辨率描绘了人类聚落,并从建筑环境的功能和高度相关组件方面描述了它们的内部特征。如需详细了解 GHSL 数据产品,请参阅 2023 年 GHSL 数据包报告… 建筑物 建成 建成区 哥白尼 ghsl 高度 -
Open Buildings V3 多边形
这个大型开放式数据集包含从高分辨率 50 厘米卫星图像派生出来的建筑物轮廓。其中包含非洲、拉丁美洲、加勒比地区、南亚和东南亚的 18 亿个建筑检测结果。推理涵盖了 5800 万平方公里的区域。对于此数据集中的每座建筑物… 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) |"]]