A unified spatial multigraph analysis for public transport performance

Yaoli Wang, Di Zhu, Ganmin Yin, Zhou Huang, Yu Liu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Public transport performance not only directly depicts the convenience of a city’s public transport, but also indirectly reflects urban dwellers’ life quality and urban attractiveness. Understanding why some regions are easier to get around by public transport helps to build a green transport friendly city. This paper initiates a new perspective and method to investigate how public transport network’s morphology contributes significantly to its performance. We investigate the significance of morphology from the perspective of graph classification – by extracting the typical local structures, called “motifs”, from the multi-modal public transport multigraph. A motif is seen as a certain connectivity pattern of different transport modes at a local scale. Combinations of various motifs decide the output of graph classification, particularly, public transport performance. We invent an innovative method to extract motifs on complex spatial multigraphs. The proposed method is adaptable to unify complex factors into one simple form for swift coding, and depends less on observational data to handle data unavailability. In the study area of Beijing, we validate that the measure can infer varied public transport efficiencies and access equalities of different regions. Some typical areas with undeveloped or unevenly distributed public transport are further discussed.

Original languageEnglish (US)
Article number9573
JournalScientific reports
Issue number1
StatePublished - Dec 1 2020
Externally publishedYes

Bibliographical note

Funding Information:
This paper is supported by the National Key Research and Development Program of China (2017YFE0196100), the National Natural Science Foundation of China (41771425,41830645,41625003), the Chinese Postdoctoral Funding (8206300189), and the joint research lab of Peking University and Amap (https://www.amap.com). We sincerely acknowledge Fengqing Zhou at the Harbin Institute of Technology (Shenzhen) for his discussion and feedback.

Publisher Copyright:
© 2020, The Author(s).


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