A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
How Does Polycentric Urban Form Affect Urban Commuting? Quantitative Measurement Using Geographical Big Data of 100 Cities in China
The relationship between polycentric urban form and urban commuting has been widely debated in Western academic circles. However, qualitative and quantitative studies have not reached a unified conclusion. The evolution of urban form in China is remarkably different from that of developed Western countries. Many Chinese cities have begun using polycentric structures as their future development strategies. This study quantitatively measures whether polycentric urban form can improve commuting efficiency in China by using traditional statistics and emerging geographic big data. We use the polycentric index (PI) as the dependent variable and the congestion delay index (CDI) and mean traffic speed (MTS) as the main independent variables. Control variables include urban morphological space compactness (CT), number of private cars per thousand people (PC), number of buses per thousand (PB), urban road area per capita (PUA) and urban population density (PD). Regression models are employed to detect the relationships among the variables. The main research conclusions are as follows: (1) A high degree of PI results in low CDI and fast MTS; (2) a compact spatial form increases the impact of polycentricity on commuting efficiency; (3) maturity road infrastructure is an important measure to promote urban commuting under a polycentric urban form; and (4) the order of effect magnitude of polycentricity on MTS is PD > PC > CT > PUA > PB; on CDI, PD > PC > PB > CT > PUA. The results can be used in examining whether the current polycentric urban pattern planning in China’s cities can effectively improve commuting efficiency. They also provide a reference for the healthy development of China’s urban space and policy formulation of subsequent urban planning.
How Does Polycentric Urban Form Affect Urban Commuting? Quantitative Measurement Using Geographical Big Data of 100 Cities in China
The relationship between polycentric urban form and urban commuting has been widely debated in Western academic circles. However, qualitative and quantitative studies have not reached a unified conclusion. The evolution of urban form in China is remarkably different from that of developed Western countries. Many Chinese cities have begun using polycentric structures as their future development strategies. This study quantitatively measures whether polycentric urban form can improve commuting efficiency in China by using traditional statistics and emerging geographic big data. We use the polycentric index (PI) as the dependent variable and the congestion delay index (CDI) and mean traffic speed (MTS) as the main independent variables. Control variables include urban morphological space compactness (CT), number of private cars per thousand people (PC), number of buses per thousand (PB), urban road area per capita (PUA) and urban population density (PD). Regression models are employed to detect the relationships among the variables. The main research conclusions are as follows: (1) A high degree of PI results in low CDI and fast MTS; (2) a compact spatial form increases the impact of polycentricity on commuting efficiency; (3) maturity road infrastructure is an important measure to promote urban commuting under a polycentric urban form; and (4) the order of effect magnitude of polycentricity on MTS is PD > PC > CT > PUA > PB; on CDI, PD > PC > PB > CT > PUA. The results can be used in examining whether the current polycentric urban pattern planning in China’s cities can effectively improve commuting efficiency. They also provide a reference for the healthy development of China’s urban space and policy formulation of subsequent urban planning.
How Does Polycentric Urban Form Affect Urban Commuting? Quantitative Measurement Using Geographical Big Data of 100 Cities in China
Xiaoyan Li (author) / Yanchuan Mou (author) / Huiying Wang (author) / Chaohui Yin (author) / Qingsong He (author)
2018
Article (Journal)
Electronic Resource
Unknown
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