Community detection, road importance assessment, and urban function pattern recognition: a big data approach

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.

KEYWORDS:

• Community detection
• navigation data
• POI
• complex network
• urban functional area

Acknowledgments

The authors would like to thank journal editor and anonymous reviewers for their comments and suggestions that have led to a significant improvement of this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study is funded by the National Natural Science Foundation of China (41801107) and Natural Science Foundation of Jiangsu Province (BK20191486).