The vector files (.shp) of the SinoBF-1 product represent a national-scale, building-level functional map covering 109 major cities in China, created using the Paraformer mapping framework (Paper link), which is available at Paraformer. We processed over 69 TB of satellite data, including 1-meter Google Earth optical imagery, 10-meter nighttime lights (SGDSAT-1), and building height data (CNBH-10m). The data, method, and analysis have been published by Nature Communications: https://www.nature.com/articles/s41467-026-69589-5 We strongly recommend that users consult the associated paper before downloading or using the SinoBF-1 dataset. 该数据发表于Nature Communications (点击查看), 使用数据前建议先查看论文与用户手册 The code of analysis and mapping is open access at: https://github.com/LiZhuoHong/SinoBF-1/ NOTE: Additional related work can be found on the author’s homepage: https://lizhuohong.github.io/lzh/. If you have any questions or technical issues, contact us at ashelee@whu.edu.cn (Zhuohong Li 李卓鸿). User guide: Download the full user guide (Click here) This version of the dataset includes building-level functional maps of 109 Chinese cities, organized in the ESRI Shapefile format. The .shp file for each city is stored in a “.zip” archive. Each city file is named G_P_C.zip, where: G indicates the geographical region (South, Central, East, North, Northeast, Northwest, Southwest) P indicates the provincial administrative region C indicates the city name For example, the building functional map for Wuhan City, Hubei Province, is named Central_Hubei_Wuhan.zip. Furthermore, each shapefile contains building functional types stored in the attribute "Function", with the corresponding building functions listed below: Value in "Function": Residential building Commercial building Industrial building Healthcare building Sport and art building Educational building Public service building Administrative building Note: Due to Zenodo’s limit of 100 files, the cities in Hubei Province and Hainan Province were grouped into single compressed packages (i.e., Central_Hubei.zip and South_Hainan.zip). Cite the paper: Li, Z., Li, L., Hu, T. et al. (2026). Satellite mapping of every building’s function in urban China reveals deep built environment disparities. Nature Communications, 17, 2827. https://doi.org/10.1038/s41467-026-69589-5 Li, Z., He, W., Cheng, M., Hu, J., Yang, G., & Zhang, H. (2023). SinoLC-1: The first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data. Earth system science data, 15(11), 4749-4780.