GlobalBuildingAtlas: An Open Global and Complete Dataset of Building Polygons, Heights and LoD1 3D Models
Xiao Xiang Zhu, Sining Chen, Fahong Zhang, Yilei Shi, Yuanyuan Wang

TL;DR
GlobalBuildingAtlas is the first comprehensive open dataset providing detailed global building polygons, heights, and 3D models, enabling advanced geospatial analysis and sustainable development monitoring.
Contribution
It introduces a novel, high-quality global dataset of building data, derived using machine learning from satellite imagery, surpassing existing datasets in coverage and detail.
Findings
Over 2.75 billion buildings included
Achieves 3x3 meter resolution for height maps
Provides the first complete global LoD1 3D building models
Abstract
We introduce GlobalBuildingAtlas, a publicly available dataset providing global and complete coverage of building polygons, heights and Level of Detail 1 (LoD1) 3D building models. This is the first open dataset to offer high quality, consistent, and complete building data in 2D and 3D form at the individual building level on a global scale. Towards this dataset, we developed machine learning-based pipelines to derive building polygons and heights (called GBA.Height) from global PlanetScope satellite data, respectively. Also a quality-based fusion strategy was employed to generate higher-quality polygons (called GBA.Polygon) based on existing open building polygons, including our own derived one. With more than 2.75 billion buildings worldwide, GBA.Polygon surpasses the most comprehensive database to date by more than 1 billion buildings. GBA.Height offers the most detailed and accurate…
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Taxonomy
TopicsRemote Sensing and LiDAR Applications · 3D Modeling in Geospatial Applications · 3D Surveying and Cultural Heritage
