CMAB-A First National-Scale Multi-Attribute Building Dataset

This data is the building dataset with a total rooftop area of 23.6 billion square meters in 3,667 natural cities in China, including the attribute of building rooftop, height, structure, function, age, style and quality, as well as the code files used to calculate these data. The deep learning models used are OCRNet, XGBoost, fine-tuned CLIP and Yolo-v8. Please refer to the paper and README file for details of specific parameters. This building data is the original version, and the processed version can be viewed here: 10.6084/m9.figshare.27992417. Related papers are published in Scientific Data.本数据集为覆盖中国3667座自然城市的建筑数据集，总屋顶面积达236亿平方米，包含建筑屋顶、高度、结构、功能、建成年代、风格与质量等属性，以及用于计算此类数据的代码文件。本次研究所采用的深度学习模型包括OCRNet、XGBoost、微调CLIP（fine-tuned CLIP）以及Yolo-v8。具体参数细节请参阅相关论文与README文件。本建筑数据集为原始版本，处理后的版本可通过以下链接查看：10.6084/m9.figshare.27992417。相关研究论文已发表于《Scientific Data》期刊。