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Articles

Defining ‘centres’ in analyses of polycentric urban regions: the case of the Yangtze River Delta

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Pages 87-98 | Received 21 Mar 2020, Published online: 10 Jun 2021
 

ABSTRACT

The analysis of ‘polycentric urban regions’ (PURs) crucially depends on the operational definition of their constituent centres. We extend an insight into this issue by exploring how analyses of the level of intra- and inter-city polycentricity in the Yangtze River Delta, China, are contingent upon the identification and territorial delineation of its centres. The results help to specify more clearly PUR measurement procedures, and provide further evidence for the conceptual, analytical and empirical importance of consistent city definitions for regional studies in general and for research into urban and regional China in particular.

JEL:

ACKNOWLEDGEMENTS

The authors thank two anonymous reviewers for their constructive comments, which helped to improve the paper.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. Remote sensing images have proven to be a useful data source for monitoring urban landscapes. Several researchers have resorted to extracting continuous impervious surface information (combined with other gridded data such as population density) to define urban areas (Van de Voorde et al., Citation2011), and its reliability has been repeatedly validated (Lu & Weng, Citation2006).

2. These data can be download from the Hubei Data and Application Network, China High-Resolution Earth Observation System (http://www.hbeos.org.cn/) (accessed on 1 December 2020).

Additional information

Funding

This work was supported by financial support from the National Natural Science Foundation of China [grant numbers 41901186 and 41971197], the Shanghai Philosophy and Social Sciences Fund [grant number 2018ECK009], the Fundamental Research Funds for the Central Universities [grant number 2020ECNU-HWFW008], the Soft Sciences Project of Shanghai Science and Technology Innovation Action Plan [grant number 20692191400} and the Open Fund from Key Laboratory of Watershed Geographic Sciences [grant number WSGS2020004].

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