ABSTRACT
Investigating the spatial network structure of urban agglomerations based on traffic accessibility has an important practical significance in accelerating the process of regional integration. Taking urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) as the case study, this study aims to examine the characteristics associated with the spatial network structure based on traffic accessibility and its changes under scenarios of different traffic accessibilities by adopting real-time traffic data, modified gravity model, and social network analysis (SNA). The main conclusions are as follows. Wuhan, Changsha, and Nanchang are the central cities in the spatial network; the spatial network structure of UAMRYR is imbalanced and in the agglomeration stage of regional economic development. With the development of traffic accessibility, resources first gather in the individual center cities and then spread to other cities, and the network tends toward equilibrium.
Nomenclature
UAMRYR | = | Urban agglomeration in the middle reaches of the Yangtze River |
SNA | = | Social network analysis |
HSR | = | High-speed rail |
PC | = | Point centrality |
BC | = | Betweenness centrality |
CC | = | Closeness centrality |
SHL | = | Structural hole limit |
Acknowledgments
Thanks to Dr. Panda Su for his advice on the figures’ modifications.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. Natural breaks (Jenks) classification is a data classification method designed to optimize the arrangement of a set of values into ‘natural’ classes. A Natural class range is composed of items with similar characteristics that form a ‘natural’ group within a data set.