Tang Jintong, Xu Liyan, Yu Hongbin, Jiang Hezhishi, He Dejie, Li Tianshu, Xiao Wanchen, Zheng Xinying, Liu Keyi, Li Yiqin, Li Shijie, Huang Qian, Zhang Jun, Zhou Yinsheng, Wu Lun, Liu Yu
Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China.
College of Architecture and Landscape Architecture, Peking University, Beijing, China.
Sci Data. 2025 Mar 19;12(1):456. doi: 10.1038/s41597-025-04704-7.
Street-blocks, as basic geographical units for dividing urban space, are widely used in urban planning and statistics. However, the availability and quality of street-block data vary significantly across different countries or regions worldwide. While developed countries tend to have mature urban street-block division systems and corresponding public data, such data in most developing countries are often incomplete or non-existent. Even in countries with available data, the lack of consistent standards for street-block division causes difficulty in international comparative research. To address this gap, we are releasing a new open dataset: Multi-level Street-block Divisions of 985 Cities Worldwide (MSDCW), offering a logical, standardized, and user-friendly street-block division system for cities with the estimated population over 500,000 by Demographia from 142 countries or regions, with results at five spatial levels. Validation shows that compared with official datasets, MSDCW offers a reasonable division of urban street-blocks, and is therefore suitable as foundational data for related research. Additionally, researchers can use our method to generate their own street-block division datasets.
街区作为划分城市空间的基本地理单元，在城市规划和统计中被广泛使用。然而，全球不同国家或地区的街区数据可用性和质量差异显著。发达国家往往拥有成熟的城市街区划分系统及相应的公共数据，而大多数发展中国家的此类数据通常不完整或不存在。即使在有可用数据的国家，街区划分缺乏统一标准也给国际比较研究带来困难。为弥补这一差距，我们发布了一个新的开放数据集：《全球985个城市的多级街区划分》（MSDCW），为来自142个国家或地区、人口超过50万的城市提供了一个逻辑清晰、标准化且用户友好的街区划分系统，结果涵盖五个空间层级。验证表明，与官方数据集相比，MSDCW对城市街区进行了合理划分，因此适合作为相关研究的基础数据。此外，研究人员可以使用我们的方法生成自己的街区划分数据集。
