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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
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
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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
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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
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

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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
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
Journal Article

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

2017
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Overview
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.