Understanding the urban scaling of urban land with an internal structure view to characterize China’s urbanization

Abstract

As an infrastructure-related urban indicator, urban land theoretically has a sub-linear scaling relationship with urban population, which has been evidenced around various urban systems. However, scaling relationships between different types of urban land such as residential, industrial land and population size are still unclear, which helps to understand how urban land expansion response to population growth with an internal structure view. Here, we take more than 500 Chinese cities as examples to investigate scaling relationships of population and land with eight types and their changes over time (2012–2018). Results show that eight types of urban land all have a robust scaling law with population, but with different scaling exponents, or even opposite scaling regimes. The whole urban land and other seven sub-types are all in line with the expected sub-linear behaviors, presenting the economies of scale. And scaling exponents of transportation land and green land decreased over time while exponents of other sub-types are stable. Industrial land surprisingly has a super-linear scaling relationship with population, presenting a faster speed than urban population. Smaller residuals of cities in the scaling regression model (Scale-Adjusted Metropolitan Indicators, SAMIs) of residential and industrial land are negatively correlated with housing prices, indicating the shortage of land supply compared to other cities of the same size spurred the rise of housing prices. While SAMIs of industrial land are positively correlated with industrial productions, demonstrating that increasing land supply is a powerful means of industrial outputs and economic growth. Our structure-based scaling analysis enriches the understanding of population-land relationship and supports differentiated land supply in land use and urban planning according to urban population size.