ABSTRACT

This paper examined the use of navigation and point-of-interests big data in three urban planning tools: community detection, road importance assessment, and urban function pattern recognition. We revealed the community structure for the urban spatial organization, followed by identifying major transit corridors and the urban function pattern. We found that the detected communities were significantly associated with the administrative divisions in the city. Major commercial and residential centers were primarily located across several communities. Besides, the spatial mismatch between commercial-residential areas and industrial development areas was also identified and examined for spatial structure optimization in urban development.

摘要

本文研究了导航和兴趣点大数据在三种城市规划工具中的使用：社区检测、道路重要性评估和城市功能模式识别。我们揭示了城市空间组织的社区结构，然后确定了主要的交通走廊和城市功能模式。我们发现检测到的社区与城市中的行政区划显着相关。主要的商业和住宅中心主要分布在几个社区。此外，还识别和检查商住区与工业开发区之间的空间不匹配，以优化城市发展中的空间结构。