Abstract

The New Form of Urbanization was proposed in 2012, emphasizing the development of small and medium-sized cities and towns. Analyzing the city-size distribution is significant in various studies, such as urban sustainable development, urban planning, population movement dynamics, and policy making in urban issues. But there lacks systematic analysis and mechanism discussion covering all cities sample especially after 2012 because of statistical data missing. This study assessed the city-size distribution of 337 cities (administratively defined) across Chinese mainland from 2013 to 2018 using multi-source data. Four main procedures are involved: 1) the urban areas of 337 cities were extracted using Head/tail Division Approach from remotely sensed nighttime light imagery; 2) the urban patterns were explored using spatiotemporal analysis (Kernel Density Estimation); 3) ln(rank) and ln(rank-1/2) were used as dependent variable to estimate Pareto exponent respectively; and 4) the economical mechanisms were explored using robust estimates. The results indicated that:1) The second mean of pixel values of NPP/VIIRS data was recommended to be the cut-off for the identification of urban areas in Chinese mainland, comparing to 1% National Population Sample Survey of 2015 and master plans of typical cities. 2) Using the total nighttime light (TNL) of urban areas to measure the city size, Zipf's Law was mostly violated in Chinese mainland. Overall, urban system was unequally distributed in all cities sample, equally distributed in upper-tail cities sample, showed great heterogeneity in provincial cities sample, meanwhile small and medium-sized cities developed rapidly after 2012. 3) Provinces with the larger value of regional scale and industrial structure were characterized as the more evenness of the city-size distribution, but with the larger value of trading level were characterized by unevenly distributed urban systems. The findings of the study indicated that the discussion about the applicability of Zipf's Law in Chinese mainland using multi-source data was of great significance, and the change of urban system in China is greatly affected by policies.

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