3D-GloBFP: the first global three-dimensional building footprint dataset

The 3D Global Building Footprints (3D-GloBFP) dataset is the first global-scale building height dataset at the individual building footprint level for the year 2020, generated through the integration of multisource Earth Observation (EO) data and the extreme gradient boosting (XGBoost) model. The reliability and accuracy of 3D-GloBFP have been validated across 33 subregions, achieving R² values ranging from 0.66 to 0.96 and root-mean-square errors (RMSEs) between 1.9 m and 14.6 m. This version supplements building footprints and height attributes for some countries in South America, Asia, Africa, and Europe, based on building footprints provided by Microsoft (https://github.com/microsoft/GlobalMLBuildingFootprints), Open Street Map (https://osmbuildings.org/), Google-Microsoft Open Buildings - combined by VIDA (https://source.coop/repositories/vida/google-microsoft-open-buildings), and EUBUCCO (https://eubucco.com/). The dataset is divided into spatial grid-based tiles, each stored as an individual ShapeFile (.shp) containing estimated building heights (in meters) in attribute tables. See world_grid.shp and readme.txt for details on the spatial grid and file naming. Data download links are provided in data_links.txt.3D全球建筑轮廓（3D-GloBFP）数据集是首个针对2020年、面向单体建筑轮廓尺度的全球尺度建筑高度数据集，通过多源地球观测（EO）数据与极限梯度提升（XGBoost）模型融合生成。3D-GloBFP的可靠性与精度已在33个子区域中得到验证，决定系数（R²）取值范围为0.66至0.96，均方根误差（RMSE）介于1.9米至14.6米之间。 本版本基于微软（https://github.com/microsoft/GlobalMLBuildingFootprints）、开放街道地图（https://osmbuildings.org/）、由VIDA整合的谷歌-微软开放建筑数据集（https://source.coop/repositories/vida/google-microsoft-open-buildings）以及EUBUCCO（https://eubucco.com/）提供的建筑轮廓数据，补充了南美洲、亚洲、非洲及欧洲部分国家的建筑轮廓与高度属性信息。 本数据集按空间网格分幅存储，每幅均为独立的形状文件（.shp），其属性表中包含以米为单位的估算建筑高度信息。有关空间网格与文件命名的详细说明，请参阅world_grid.shp与readme.txt。 数据集的下载链接已在data_links.txt中给出。