Identifying city communities in China by fusing multisource flow data

Abstract

The identification of city communities is essential for the regional planning and management of metropolitan areas. City communities could be identified from the perspective of mobile flows, and integrating the advantages of multisource flow data is essential to measure intercity connectivity. In this research, a multisource flow fusion method, which avoids the one-sidedness of a single flow, is proposed to combine the characteristics of population flow, traffic flow, and information flow. Moreover, the silhouette coefficient and hierarchical clustering algorithm are used to determine the number of city communities and the final clustering result. The results show that (1) although population flow, cargo flow, and information flow are positively correlated, there are also some differences among them; (2) the fusion flow between cities in China presents an obvious diamond structure, among which Beijing, Shanghai, Guangzhou, and Chengdu are the four points of the diamond, and Wuhan is located almost in the centre of the diamond structure; and (3) city communities are identified based on multisource flow and hierarchical clustering algorithm, which meet the principles that closely connected cities are in the same community and nonclosely connected cities are in different communities.

Keywords

• city community
• population flow
• traffic flow
• information flow
• hierarchical clustering