Identifying China’s polycentric cities and evaluating the urban centre development level using Luojia-1A night-time light data

ABSTRACT

Studying the structure of polycentric cities can promote a better understanding of urban development and contribute to urban planning. In this study, we identified polycentric cities in China and evaluated the urban centre development level of polycentric cities from new data and method. We used Luojia-1A night-time light (NTL) data, combined with the concept of natural cities (NCs), to identify urban centres and thus identify polycentric cities in China. In addition, we used the urban centre development index (UCDI) to quantify the urban centre development level (UCDL) that represents the overall urban centre development level within a polycentric city. The polycentric cities in China are characterized by the spatial distribution pattern of a larger number in the east and fewer in the west. There are a large number of polycentric cities in eastern China, and the closer to the coastal areas, the more polycentric cities there are. The distribution of UCDL in China’s polycentric cities is characterized by significant spatial heterogeneity. UCDLs are generally smaller in polycentric cities in western China. In addition, polycentric cities in northeastern China have smaller UCDL. Polycentric cities with high UCDL are concentrated in the central and coastal regions of China.

KEYWORDS:

• Natural city
• night-time light data
• Luojia-1A
• urban centre
• polycentric city

Acknowledgements

We are grateful to Wuhan University for providing free use of Luojia-1A NTL data. This work was supported by the National Key R&D Program of China [grant no. 2018YFB2100703]; the National Natural Science Foundation of China [grant no. U1901219]; the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) [grant no. GML2019ZD0301]; the Key Science and Technology Projects of Guangzhou [grant no. 20180203008]; and the postgraduate innovation ability training program of Guangzhou University [grant no. 2019GDJC-M01].

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the the National Key R&D Program of China [2018YFB2100703]; the National Natural Science Foundation of China [U1901219]; the Postgraduate Innovation Ability Training Program of Guangzhou University [2019GDJC-M01]; the Key Science and Technology Projects of Guangzhou [20180203008]; the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) [GML2019ZD0301].