Articles | Volume 18, issue 4
https://doi.org/10.5194/essd-18-2609-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-2609-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
13 Apr 2026
Data description article |
| 13 Apr 2026
| 13 Apr 2026
BuildingSense: a new multimodal building function classification dataset
Pengxiang Su
College of Surveying and Geo-informatics, Tongji University, Shanghai, China
Runfei Chen
Urban Mobility Institute, Tongji University, Shanghai, China
Heng Xu
College of Surveying and Geo-informatics, Tongji University, Shanghai, China
Wei Huang
CORRESPONDING AUTHOR
College of Surveying and Geo-informatics, Tongji University, Shanghai, China
Urban Mobility Institute, Tongji University, Shanghai, China
Department of Civil Engineering, Toronto Metropolitan University, Toronto, Canada
Xinling Deng
Cornell Tech, Cornell University, New York City, USA
Songnian Li
Department of Civil Engineering, Toronto Metropolitan University, Toronto, Canada
Wanglin Yan
Faculty of Environment and Information Studies, Keio University, Fujisawa City, Japan
Hangbin Wu
College of Surveying and Geo-informatics, Tongji University, Shanghai, China
Chun Liu
College of Surveying and Geo-informatics, Tongji University, Shanghai, China
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Short summary
The accessibility of building function is essential for urban research. We reviewed the recent work and concluded three limitations: few open-source datasets, coarse building function categories, and poor model interpretability with inadequate multimodal feature fusion. Thus, we created BuildingSense with fine-grained categories and multimodal data, and proved that the large model can be used for improving the interpretability of results, with three directions for enhancing their performance.
The accessibility of building function is essential for urban research. We reviewed the recent...
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