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Aug 30, 2023
Unveiling the Urban Spatial Structure from the Perspective of Job-Housing Relationship: A Case Study of Guangzhou, China
Authors: Maosong Zhou [email protected], Xiaoming Zhang, Ph.D. [email protected], Tian Gan [email protected], Chuanyu Chen [email protected], Weifeng Li, Ph.D. [email protected], and Lu Zuo [email protected]Author Affiliations
Publication: CICTP 2023
ABSTRACT
Commuting is a substantial component of urban transportation. Understanding the commuting patterns may contribute to the decision-making of urban spatial structure optimization and quality-of-life improvement. This paper addresses the urban spatial structure analysis at the macro and meso levels based on commuting demand. Mobile phone data is introduced to identify the commuting demand and construct the commuting flow network. The community detection method is applied to divide the basic spatial analysis units and further analyzes the urban spatial structure from the perspective of a job-housing relationship. Guangzhou is selected as a case to demonstrate the proposed methods. As a result, the spatial divisions based on community detection are proved to be applicable as basic spatial analysis units. The outcomes show the regional cohesiveness and the hierarchical levels in the spatial structure of Guangzhou and reveal the significant effect of commuting distance on the spatial structure. The methodology proposed in this paper is an operable macro- and meso-tool for an over knowledge of urban spatial structure.
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Published online: Aug 30, 2023
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ASCE Technical Topics:
- Analysis (by type)
- Business management
- Case studies
- Commute
- Decision making
- Detection methods
- Engineering fundamentals
- Infrastructure
- Methodology (by type)
- Practice and Profession
- Research methods (by type)
- Spatial analysis
- Structural analysis
- Structural engineering
- Traffic engineering
- Transportation engineering
- Transportation management
- Transportation studies
- Urban and regional development
- Urban areas
Authors
Affiliations
1Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring, and Early Warning, Guangzhou Urban Planning & Design Survey Research Institute, Yuexiu District, Guangzhou, China. Email: [email protected]
2Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring, and Early Warning, Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou, China. Email: [email protected]
3Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji Univ., Shanghai, China. Email: [email protected]
4Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring, and Early Warning, Guangzhou Urban Planning & Design Survey Research Institute, Yuexiu District, Guangzhou, China. Email: [email protected]
5Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji Univ., Shanghai, China. Email: [email protected]
6Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring, and Early Warning, Guangzhou Urban Planning & Design Survey Research Institute, Yuexiu District, Guangzhou, China. Email: [email protected]
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