000 02306nab a2200253 4500
999 _c11404
_d11404
003 OSt
005 20210226150052.0
007 cr aa aaaaa
008 210226b ||||| |||| 00| 0 eng d
100 _aYang, Haoran
_931930
245 _aComparing passenger flow and time schedule data to analyse High-Speed Railways and urban networks in China
260 _bSage
_c2019
300 _aVol 56, Issue 6, 2019 : (1267-1287 p.)
520 _aChina’s High-Speed Railways (HSR) network is the biggest in the world, transporting large numbers of passengers by high-speed trains through urban networks. Little is known about the analytical meaning of the use of two types of flow data, namely, time schedule (transportation mode flow) and passenger flow data, to characterise the configuration of urban networks regarding the potential spatial effects of HSR networks on urban networks. In this article, we compare HSR passenger flow data with time schedule data from 2013 in China within the same analytical framework. The findings show great differences in the strength of cities and links generated using the two different types of flow data. These differences can be explained largely by the socio-economic attributes of the cities involved, such as tertiary employment, GDP per capita, the cities’ topological properties (closeness centrality) in HSR networks and institutional factors (hub status), especially for the difference in link strength. The strength of first-tier cities in China with high socio-economic performance and the HSR links connecting core cites and major cities within respective regions tends to be underestimated when using time schedule flows compared with passenger flows. When analysing the spatial structure of HSR and urban networks by means of flows, it is important for urban geographers and transportation planners to consider the meaning of the different types of data with the analytical results.
650 _aChina
_944627
650 _atime schedule
_944628
650 _apassenger flow
_939075
650 _aHigh-Speed Railways (HSR)
_933437
700 _aDijst, Martin
_944629
700 _aWitte, Patrick
_932405
773 0 _011188
_915499
_dsage, 2019.
_tUrban studies
856 _uhttps://doi.org/10.1177/0042098018761498
942 _2ddc
_cART