Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 17, issue 12
Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-6647-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-6647-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 12
Data description paper
 | 
01 Dec 2025
Data description paper |  | 01 Dec 2025

GlobalBuildingAtlas: an open global and complete dataset of building polygons, heights and LoD1 3D models

Xiao Xiang Zhu, Sining Chen, Fahong Zhang, Yilei Shi, and Yuanyuan Wang

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Cao, Y. and Huang, X.: A deep learning method for building height estimation using high-resolution multi-view imagery over urban areas: A case study of 42 Chinese cities, Remote Sensing of Environment, 264, 112590, https://doi.org/10.1016/j.rse.2021.112590, 2021. a
Che, Y., Li, X., Liu, X., Wang, Y., Liao, W., Zheng, X., Zhang, X., Xu, X., Shi, Q., Zhu, J., Zhang, H., Yuan, H., and Dai, Y.: 3D-GloBFP: the first global three-dimensional building footprint dataset, Earth Syst. Sci. Data, 16, 5357–5374, https://doi.org/10.5194/essd-16-5357-2024, 2024. a, b, c, d
Chen, S., Shi, Y., Xiong, Z., and Zhu, X. X.: HTC-DC Net: Monocular Height Estimation From Single Remote Sensing Images, IEEE Transactions on Geoscience and Remote Sensing, 61, 1–18, https://doi.org/10.1109/TGRS.2023.3321255, 2023. a
City of Helsinki: Helsinki 3D City Model, [3D model], https://hri.fi/data/en_GB/dataset/helsingin-3d-kaupunkimalli (last access: 1 November 2025), 2017. a
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., and Houlsby, N.: An image is worth 16 × 16 words: Transformers for image recognition at scale, arXiv [preprint], https://doi.org/10.48550/arXiv.2010.11929, 2020. a
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We introduce GlobalBuildingAtlas, a publicly available dataset offering global and complete coverage of building polygons (GBA.Polygon), heights (GBA.Height) and Level of Detail 1 3D models (GBA.LoD1). This is the first open dataset to offer high quality, consistent, and complete building data in 2D and 3D at the individual building level on a global scale. With more than 2.75 billion buildings worldwide, it surpasses the most comprehensive database to date by more than 1 billion buildings.
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