3D-GloBFP: the first global three-dimensional building footprint dataset
Authors/Creators
- 1. Guangdong Key Laboratory for Urbanization and Geo-simulation
- 2. School of Geography and Planning, Sun Yat-sen University
- 3. College of Land Science and Technology, China Agricultural University
- 4. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)
- 5. The State Key Lab. LIESMARS, Wuhan University
- 6. Department of Geography, Ghent University
- 7. School of Geographical Sciences and Remote Sensing, Guangzhou University
- 8. School of Atmospheric Sciences, Sun Yat-sen University
Description
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.
Files
data_links.txt
Additional details
Funding
- National Natural Science Foundation of China
- National Science Fund for Distinguished Young Scholars 42225107
- National Natural Science Foundation of China
- National Natural Science Foundation of China 42471513