Abstract
Decades of rapid urbanization have reshaped China’s cities, yet fine-scale built environment disparities remain unclear due to scarce building-level data. Here, we present SinoBF-1, a national building functional map of China that delineates 110 million buildings across 109 major cities using 1-meter multi-modal satellite data. Using nine indicators spanning urbanization intensity, facility accessibility, and infrastructure sufficiency, we quantify disparities across city tiers, geographic regions, and intra-city zones. Analyses reveal that: (1) Across city tiers, accessibility and amenity diversity decline sharply from top- to low-tier cities, while mid tiers show more equitable housing allocation; (2) Geographically, southern cities exhibit the highest access to healthcare, education, and public services but suffer from infrastructure overcrowding; and (3) Within cities, later-expanding zones exhibit greater disparities than early-established urban cores. This study reflects legacies of national development policies over the past half-century and offers a framework for evaluating urban inequality in rapidly urbanizing regions.
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Data availability
The SinoBF-130 data of all 109 cities generated in this study have been deposited in the Zenodo database under accession code https://doi.org/10.5281/zenodo.17844789. The source data utilized in this study were collected from various platforms. The optical images are available at https://earth.google.com. The CNBH-10m building height dataset is available at https://zenodo.org/records/7827315. It is acknowledged that the SDGSAT-1 data are kindly provided by the International Research Center of Big Data for Sustainable Development Goals (CBAS) https://sdg.casearth.cn/en. The building footprint data, including the CN-OpenData and the East Asia Building Dataset, are available at https://doi.org/10.11888/Geogra.tpdc.271702and https://zenodo.org/records/8174931. The Land use and AOI data used for constructing urban functional labels are retrieved from OpenStreetMap at https://www.openstreetmap.org/. The official government reports used for statistical validation are accessed from https://www.stats.gov.cn/sj/ndsj/2023/indexch.htmand https://www.mohurd.gov.cn/gongkai/fdzdgknr/sjfb/tjxx/jstjnj/index.html. The VGI data used in validation are provided through Amap at https://lbs.amap.com/api/javascript-api-v2. The 1-m land-cover map of China produced in our previous study is available at https://doi.org/10.5281/zenodo.7707461. The 100-m gridded population dataset that was used to analyze housing inequality and infrastructure allocation is from China’s seventh census dataset https://figshare.com/s/d9dd5f9bb1a7f4fd3734?file=43847643.
Code availability
The full methodological framework31, including the complete protocol, source code, and step-by-step implementation guidelines, is publicly available on GitHub at https://github.com/LiZhuoHong/SinoBF-1/. The repository provides comprehensive documentation, covering map utilization procedures, computation of multi-dimensional indicators, and reproducible workflows for building functional mapping.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (T2525018 to H.Z., 42230108 to L.Z., 42271370 to W.H., and 42201377 to T.H.) and the Open Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University (24R06 to T.H.).
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H.Z. conceived and supervised the whole project. Z.L. designed and organized the mapping framework of this study. Z.L., L.L., and T.H. performed data analysis and interpretation. H.Z., W.H., and T.H. supervised the “Methods” sections. Z.L., L.L., and M.C. contributed to producing the building function map. Z.H., L.L., M.C., T.H., T.Q., and H.Z. conducted the multi-dimensional assessments of inequality. Z.L., H.Z., L.L., T.H., T.Q., W.H., and L.Z. contributed to the result discussion and overall analysis. Z.L., H.Z., L.L., T.H., M.C., W.H., T.Q., and L.Z. wrote and revised the manuscript.
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Li, Z., Li, L., Hu, T. et al. Satellite mapping of every building’s function in urban China reveals deep built environment disparities. Nat Commun (2026). https://doi.org/10.1038/s41467-026-69589-5
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DOI: https://doi.org/10.1038/s41467-026-69589-5
