Comparative Analysis of Metro Passengers' Mobility Patterns and Jobs-housing Balance of Metropolitan

doi:10.11947/j.JGGS.2024.0201

Abstract

Abstract:

The advent of the big data era has provided many types of transportation datasets, such as metro smart card data, for studying residents' mobility and understanding how their mobility has been shaped and is shaping the urban space. In this paper, we use metro smart card data from two Chinese metropolises, Shanghai and Shenzhen. Five metro mobility indicators are introduced, and association rules are established to explore the mobility patterns. The proportion of people entering and exiting the station is used to measure the jobs-housing balance. It is found that the average travel distance and duration of Shanghai passengers are higher than those of Shenzhen, and the proportion of metro commuters in Shanghai is higher than that of Shenzhen. The jobs-housing spatial relationship in Shenzhen based on metro travel is more balanced than that in Shanghai. The fundamental reason for the differences between the two cities is the difference in urban morphology. Compared with the monocentric structure of Shanghai, the polycentric structure of Shenzhen results in more scattered travel hotspots and more diverse travel routes, which helps Shenzhen to have a better jobs-housing balance. This paper fills a gap in comparative research among Chinese cities based on transportation big data analysis. The results provide support for planning metro routes, adjusting urban structure and land use to form a more reasonable metro network, and balancing the jobs-housing spatial relationship.

Key words: metro smart card data; mobility patterns; association rules; jobs-housing balance

HUANG Yiman, ZHANG Anshu, SU Yuezhu, SHI Wenzhong. Comparative Analysis of Metro Passengers' Mobility Patterns and Jobs-housing Balance of Metropolitan[J]. Journal of Geodesy and Geoinformation Science, 2024, 7(2): 1-17.

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