3D-GloBFP: the first global three-dimensional building footprint dataset (PART Ⅰ, grid ID: 0-400)

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全球建筑足迹（3D-GloBFP）数据集是首个针对2020年、单个建筑足迹级别的全球尺度建筑高度数据集，由多源地球观测（Earth Observation, EO）数据与极端梯度提升（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（root-mean-square error, RMSE）介于1.9米至14.6米之间。本数据集提供建筑足迹尺度的建筑高度地图，按空间网格分块存储，每个分块均为独立的ShapeFile（.shp）格式文件，其属性表中包含以米为单位的建筑高度估算值。

搜集汇总

背景与挑战

背景概述

3D-GloBFP是全球首个2020年单体建筑尺度的三维建筑足迹数据集，采用多源遥感数据和XGBoost模型生成，精度验证R²达0.66-0.96。数据按空间网格分块存储为ShapeFile格式，包含建筑高度属性信息。