Similarities and differences of city-size distributionsin three main urban agglomerations of Chinafrom 1992 to 2015: A comparative study based on nighttime light data

doi:10.1007/s11442-017-1391-7

Abstract

Abstract:

Comparing the city-size distribution at the urban agglomeration (UA) scale is important for understanding the processes of urban development. However, comparative studies of city-size distribution among China’s three largest UAs, the Beijing-Tianjin-Hebei agglomeration (BTHA), the Yangtze River Delta agglomeration (YRDA), and the Pearl River Delta agglomeration (PRDA), remain inadequate due to the limitation of data availability. Therefore, using urban data derived from time-series nighttime light data, the common characteristics and distinctive features of city-size distribution among the three UAs from 1992 to 2015 were compared by the Pareto regression and the rank clock method. We identified two common features. First, the city-size distribution became more even. The Pareto exponents increased by 0.17, 0.12, and 0.01 in the YRDA, BTHA, and PRDA, respectively. Second, the average ranks of small cities ascended, being 0.55, 0.08 and 0.04 in the three UAs, respectively. However, the average ranks of large and medium cities in the three UAs experienced different trajectories, which are closely related to the similarities and differences in the driving forces for the development of UAs. Place-based measures are encouraged to promote a coordinated development among cities of differing sizes in the three UAs.

Key words: city-size distribution, comparative study, nighttime light data, rank clock, urban agglomeration

Bin GAO, Qingxu HUANG, Chunyang HE, Yinyin DOU. Similarities and differences of city-size distributions
in three main urban agglomerations of China
from 1992 to 2015: A comparative study based on nighttime light data[J].Journal of Geographical Sciences, 2017, 27(5): 533-545.

Figures/Tables 6

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References 54

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Urban agglomeration	Area (× 10⁴ km²)	Number of cities	Current core cities	Total population (million)	Percentage of urban population (%)	GDP per capita (×10⁴ yuan)
BTHA	18.20	105	Beijing, Tianjin	83.78	59.95	4.73
YRDA	10.75	75	Shanghai	106.51	69.75	6.58
PRDA	5.41	27	Guangzhou, Shenzhen, Hong Kong	56.13	82.72	6.71

Region	Time	DMSP/OLS NSL dataset		NLCDs
Region	Time	Pareto exponent	R² (%)	Pareto exponent	R² (%)
BTHA	1990	0.52	83.12	0.71	95.61
BTHA	2010	0.61	95.77	0.78	95.81
YRDA	1990	0.54	96.68	0.83	97.28
YRDA	2010	0.69	95.28	0.90	96.84
PRDA	1990	0.34	87.59	0.49	85.62
PRDA	2010	0.33	78.68	0.46	90.08

Region	City-size distribution dynamics		Major driving forces
Region	Similarity	Differences	Similarity	Differences
BTHA	Pareto exponent increased, indicating a more even distribution	Rank of large cities: Stable Rank of medium cities: Down Rank of small cities: Up	Political effects exerted great impacts on city-size distribution, such as the stable rank of large cities in BTHA and the rising of small cities in YRDA and PRDA (Lu, and Fan 2010, Gu et al., 2008).
YRDA		Rank of large cities: Down Rank of medium cities: Down Rank of small cities: Up		Spatial linkage of industries encouraged the rising rank of small cities close to Shanghai (Luo and Shen, 2009)
PRDA		Rank of large cities: Down Rank of medium cities: Stable Rank of small cities: Up		Investment and transportation encouraged the rising ranks of small cities close to Hong Kong (Yeh and Xu, 2010, 2013; Xu & Anthony, 2009)