Reshaping China's urban networks and their determinants: High-speed rail vs. air networks

  • Haoran Yang
  • , Delin Du*
  • , Jiaoe Wang*
  • , Xiaomeng Wang
  • , Fan Zhang
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

As high-speed rail (HSR) and air transportation developed rapidly in the last decade, their coopetition and interactional relationship has reshaped China's urban networks. Based on HSR and flight schedule data from 2009 to 2019, this paper constructs a weighted network to compare China's urban networks and their evolution, and employs machine learning to investigate the potential determinants. The results indicated that both networks tend toward polarization in the overall distribution and that the structure of urban networks under HSR networks is more hierarchical. That of HSR networks gradually forms a corridor structure along the trunk lines, while that of airline networks mainly shows a diamond spatial structure with Beijing, Shanghai, Guangzhou, and Chengdu as the cores. As for the evolution of urban networks, geographical factors, per capita GDP, and the tourism function of cities have more important impacts on that of HSR networks, while the network's topological structure and education resources have a greater impact on that of airline networks. Some socioeconomic attributes, such as urban administrative level, population, and the proportion of tertiary industry, have similar and limited influences on the two networks.

Original languageEnglish
Pages (from-to)83-92
Number of pages10
JournalTransport Policy
Volume143
DOIs
StatePublished - Nov 2023

Keywords

  • Airline
  • Dynamic evolution
  • High-speed railway
  • Machine learning
  • Urban network

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