Articles | Volume 16, issue 11
https://doi.org/10.5194/essd-16-5357-2024
https://doi.org/10.5194/essd-16-5357-2024
Data description paper
 | 
25 Nov 2024
Data description paper |  | 25 Nov 2024

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

Yangzi Che, Xuecao Li, Xiaoping Liu, Yuhao Wang, Weilin Liao, Xianwei Zheng, Xucai Zhang, Xiaocong Xu, Qian Shi, Jiajun Zhu, Honghui Zhang, Hua Yuan, and Yongjiu Dai

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Short summary
Most existing building height products are limited with respect to either spatial resolution or coverage, not to mention the spatial heterogeneity introduced by global building forms. Using Earth Observation (EO) datasets for 2020, we developed a global height dataset at the individual building scale. The dataset provides spatially explicit information on 3D building morphology, supporting both macro- and microanalysis of urban areas.
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