Journal of Geographical Sciences >
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
Received date: 2016-07-14
Accepted date: 2016-10-13
Online published: 2017-05-10
Supported by
National Natural Science Foundation of China, No.41621061, No.41501092
Talents Training Program from the Beijing Municipal Commission of Education No.201500002012G058
Copyright
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.
GAO Bin
,
HUANG Qingxu
,
HE Chunyang
,
DOU Yinyin
. 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
.
DOI: 10.1007/s11442-017-1391-7
Figure 1 Urban expansion in China between 1992 and 2015 ^Note: Urban agglomeration abbreviations: BTHA (Beijing-Tianjin-Hebei agglomeration), YRDA (Yangtze River Delta agglomeration), and PRDA (Pearl River Delta agglomeration) |
Table 1 Comparison of socioeconomic status among the three urban agglomerations in 2010 |
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 |
Figure 2 Temporal changes in the Pareto exponent among the three urban agglomerations from 1992 to 2015^Please refer to Figure 1 for an explanation of the abbreviations. |
Figure 3 Comparison of rank fluctuations and the average rank for cities of differing sizes among the three urban agglomerations^Note: a-c: Rank clocks of individual cities within each urban agglomeration; d-f: Changes in the average ranks of cities of differing sizes |
Table 2 Comparison of the Pareto exponents derived from various datasets |
Region | Time | DMSP/OLS NSL dataset | NLCDs | ||
---|---|---|---|---|---|
Pareto exponent | R2 (%) | Pareto exponent | R2 (%) | ||
BTHA | 1990 | 0.52 | 83.12 | 0.71 | 95.61 |
2010 | 0.61 | 95.77 | 0.78 | 95.81 | |
YRDA | 1990 | 0.54 | 96.68 | 0.83 | 97.28 |
2010 | 0.69 | 95.28 | 0.90 | 96.84 | |
PRDA | 1990 | 0.34 | 87.59 | 0.49 | 85.62 |
2010 | 0.33 | 78.68 | 0.46 | 90.08 |
Note: DMSP/OLS NSL (Defense Meteorological Satellite Program/Operational Linescan System), NLCDs (National Land use/Cover Datasets) |
Table 3 Comparison of the major driving forces of city-size distribution dynamics among the three urban agglomerations |
Region | City-size distribution dynamics | Major driving forces | ||
---|---|---|---|---|
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) |
The authors have declared that no competing interests exist.
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