Delineating functional urban areas in Chinese mega city regions using fine-grained population data and cellphone location data: A case of Pearl River Delta. (April 2022)

• Record Type: Journal Article
• Authors: Chen, Zifeng; Yeh, Anthony Gar-On
• Is Part Of: Computers, environment and urban systems. Volume 93(2022)
• Publication Date: 2022-04
• Subjects: Functional urban area -- Mega city region -- Commuting -- Prefecture-level city -- Pearl River Delta; City planning -- Data processing -- Periodicals; Regional planning -- Data processing -- Periodicals; 303.4834
• DOI: 10.1016/j.compenvurbsys.2022.101771
• Languages: English
• ISSNs: 0198-9715

Abstract

Abstract: A functional urban area (FUA) is composed of nearby physical urban areas that have intense functional connections or linkages. This notion gains increasing popularity in recent decades. Like in many other developing countries, no official definition of FUAs exists in China despite a few scholarly attempts. The present study extends the literature by developing a novel method based upon fine-grained population data and cellphone location data to delineate FUAs in China. At a spatial unit of 1 km grid cells, the fine-grained population data are used to infer population density to identify core areas of FUAs. Thereafter, cellphone location data are used to infer commuting flows to identify periphery areas that are economically integrated with the core areas. Using 9 prefecture-level cities in the Pearl River Delta of southern China as a case study, a total of 26 FUAs are identified. The robustness of FUA delineation is validated based on three criteria, namely sensitivity, realisticness, and compactness. The present study unravels that prefecture-level cities in China are not good representation of FUAs. Some of the prefecture-level cities have multiple FUAs that are functionally separate from each other, while some FUAs may surpass the administrative borders and be shared by two or more prefecture-level cities. Through the empirical case, the present study contributes a rigorous method to delineate FUAs that is not affected by the spatial configuration of administrative boundaries at any scales, which can facilitate more precise understanding of regional spatial interactions and more effective measures in regional governance. Highlights: We granularly delineate functional urban areas (FUAs) in China using 1 km grid cells. We use fine-grained population data to infer density to identify core areas of FUAs. We use cellphone location data to infer commuting flows to identify periphery areas. 3 aspects of robustness (sensitivity, realisticness, and compactness) are addressed. The FUA delineation can address the critical problems of city definitions in China.