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The configurations of Chinese national urban systems in both high-speed railway and airline networks

can to a large extent underestimate the positions of major cities in the urban system,
especially in China with a larger-than-average capacity in the trains running from and to
these major tier cities to satisfy the demands of passenger travel.
As a result of all these limitations, there is a strong rationale for investigating urban systems
(1) through demand-related data, which (2) are based on true origins and destinations
(Neal, 2014). Of course, such data are usually not fully available (or even not available
at all) for scholars. Commercial privacy and confidentiality dominate academic purposes,
even in the strictly controlled railway sector in China (Liu et al., 2015).
In sum, the literature review above indicates that currently the research on both airline
and HSR network research is largely based on time schedule data instead of the actual
number of passengers carried by transportation networks between cities, which can
lead to some misunderstanding of the functional urban system. Furthermore, world city
research using airline data and the regional urban system research using HSR data only
include a limited number of cities at the global and regional scale, respectively. There is
no comparison between the roles of high-speed railway and airlines on the configuration
of urban systems with a large number of cities at the same spatial level. Our research
tries to fill the gaps by the applications of both HSR and airline O/D passenger flows
to compare the configurations of urban systems in the two high-speed transportation
networks at the national scale in China.

3. Methodology

3.1 Data description

In this study, cities are the nodes in the networks. The relationship between nodes is
operationalized as the number of actual number of HSR and airline passengers travelling
between cities. In China, there are four types of cities: municipalities, sub-provincial
and provincial capital cities, prefecture-level cities and county-level cities (Ma, 2005).
Country-level cities are merged with the prefecture-level cities since most cities do not
have airports and HSR stations and are under the administration of relevant prefecture-
level cities. If there are cities with multiple HSR stations and airports, those terminals
have been merged into one node. For example, if node i is Beijing and node j is Shanghai,
a represents the HSR or airline passenger flows between the two urban areas. The
ij
HSR passenger matrix was collected by the Transportation Bureau of the China Railway
Corporation, including the total actual numbers of aggregated HSR O/D passengers
2
travelling between pairs of cities . The data cover the 105 existing HSR cities (Figure
2) (4 municipality-level, 21 sub-provincial/provincial capital level and 80 prefecture-
level cities) and 1675 city links (passenger volume larger than 0) in China in 2013 (over
436 million passengers). The airline passenger matrix was collected by the Civil Aviation
Administration of China and includes a total actual number of O/D air passengers
travelling between pairs of cities. The data cover the 168 existing airport cities (Figure 2)
(4 municipality-level, 32 sub-provincial/provincial capital level and 132 prefecture-level
cities) and 1467 links (passenger volume larger than 0) in China in 2013 (over 306 million
passengers). In the end, we obtained 51 cities with both HSR and airport terminals and
3
144 city pairs with both HSR and airline connections in 2013.

2 According to China classification of HSR services, these are D and G trains.
3 Due to the fact that HSR passenger flow data are rarely accessible for researchers especially at the national scale in China,
we could only compare both HSR and airline passenger flow data in 2013 instead of the up-to-date data in 2016.

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