Spatial Relationships between Population, Employment Density, and Urban Metro Stations: A Case Study of Tianjin City, China
Publication: Journal of Urban Planning and Development
Volume 150, Issue 1
Abstract
The development of rail transit is expected to gather housing and jobs around metro stations to improve the urban spatial structure for sustainable development. However, evaluations of the effects of transit-oriented development (TOD) practices in Chinese cities remain limited. Based on 2019 mobile phone signaling data, this study analyzed the spatial relationship between metro station areas, urban population density, and employment density in Tianjin City, China. Kernel density estimation, the coverage rate of population and employment, and the envelope range density method for rail transit networks were used to describe the spatial relationships between rail transit and the distribution of population and employment. The concentric circle method was used to analyze the spatial variation of residential population density and employment density within the station surrounding areas. Multiple linear regressions, spatial autocorrelation analysis, and geographically weighted regression analysis were established to quantitatively evaluate the effects of metro stations on the residential population density and employment density around the stations. Results show that: (1) population and employment are significantly concentrated along the rail transit area; (2) metro stations within the suburban area, which are roughly 10 km away from the center, have the most significant aggregation effect on population and employment; and (3) employment density and the proportion of residential and commercial lands are the most influential factors in residential population density within the station’s surrounding areas. These findings contribute to comprehensive spatial analysis on population and employment densities around metro stations and provide scientific support for sustainable urban development. Based on the research results, policy implications are proposed to better guide the coordinated development of rail transit and urban spatial structure.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author on reasonable request.
Acknowledgments
This research was supported by the National Natural Science Foundation of China (Grant Nos. 74804113 and 72174122), the Natural Science Foundation of Guangdong Province (Grant No. 2022A1515011816), and the Shenzhen Science and Technology Plan (Grant No. 20200813170728001).
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Journal of Urban Planning and Development
Volume 150 • Issue 1 • March 2024
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© 2023 American Society of Civil Engineers.
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Received: Nov 6, 2022
Accepted: Sep 29, 2023
Published online: Nov 7, 2023
Published in print: Mar 1, 2024
Discussion open until: Apr 7, 2024
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