3D-GloBFP: the first global three-dimensional building footprint dataset (PART Ⅱ, grid ID: 400-699)

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. The dataset provides footprint-scale building height maps, divided into spatial grid-based tiles, each stored as an individual ShapeFile (.shp) containing estimated building heights (in meters) in attribute tables.

3D全球建筑轮廓（3D-GloBFP）数据集是全球首个面向2020年、基于单体建筑轮廓尺度的建筑高度数据集，通过多源地球观测（Earth Observation, EO）数据与极限梯度提升（XGBoost）模型融合生成。该数据集的可靠性与精度已在33个分区中得到验证，决定系数（R²）介于0.66至0.96之间，均方根误差（RMSE）处于1.9米至14.6米区间。本数据集提供轮廓尺度的建筑高度制图成果，按空间网格分幅存储，每幅均以独立的形状文件（ShapeFile, .shp）格式保存，其属性表中包含以米为单位的估算建筑高度值。