Urban Rail Transit Station Type Identification Based on “Passenger Flow—Land Use—Job-Housing”

Hongxia Feng, Yaotong Chen, Jinyi Wu, Zhenqian Zhao, Yuanqing Wang () and Zhuoting Wang
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Hongxia Feng: School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China
Yaotong Chen: School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China
Jinyi Wu: School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China
Zhenqian Zhao: Beijing Qinghua Tongheng Planning and Design Institute, Beijing 100080, China
Yuanqing Wang: Key Laboratory of Transport Industry of Management, Control and Cycle Repair Technology for Traffic Network Facilities in Ecological Security Barrier Area, Chang’an University, Xi’an 710064, China
Zhuoting Wang: School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China

Sustainability, 2023, vol. 15, issue 20, 1-24

Abstract: Urban rail transit stations serve as pivotal hubs that facilitate the advancement of diverse economic activities. Based on different types of metro stations, the sustainable and coordinated development of public transport and land use can be achieved through rational land use planning and the rational allocation of urban infrastructure and public service facilities. Drawing upon mobile phone signaling data and land use data, this article presents a complex classification methodology for metro stations, employing the lens of “passenger flow behavior—land use structure—job-housing density” in the context of Xi’an. The stations are categorized into six distinct types, including employment-led stations with a job–housing density balance, as well as stations characterized by job–housing mismatch with a high residential density. The results indicate a low level of coupling between the passenger flow patterns of the stations and the spatial characteristics of the station areas. In addition, the spatial distributions of the stations demonstrate a significant aggregation effect in each station type, while the degree of integration between the different station types remains limited. These findings collectively suggest that the urban rail transit stations in Xi’an have not achieved complementary development, thereby reflecting a notable trend of cross-regional commuter flow in the city.

Keywords: metro station; mobile phone signaling data; station classification; spatial mismatch; K-means clustering algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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