Contemporary evolution and scaling of 32 major cities in China

Abstract

Most of the planet's population currently lives in urban areas, and urban land expansion is one of the most dramatic forms of land conversion. Understanding how cities evolve temporally, spatially, and organizationally in a rapidly urbanizing world is critical for sustainable development. However, few studies have examined the coevolution of urban attributes in time and space simultaneously and the adequacy of power law scaling across cities and through time, particularly in countries that have experienced abrupt, widespread, political and economic changes. Here, we show the temporal coevolution of multiple physical, demographic, socioeconomic, and environmental attributes in individual cities, and the cross-city scaling of urban attributes at six time points (i.e., 1978, 1990, 1995, 2000, 2005, and 2010) in 32 major Chinese cities. We found that power law scaling could adequately characterize both the cross-city scaling of urban attributes across cities and the longitudinal scaling describing the temporal coevolution of urban attributes within individual cities. The cross-city scaling properties demonstrated substantial changes over time signifying evolved social and economic forces. A key finding was that the cross-city linear or superlinear scaling of urban area with population contradicts the theoretical sublinear power law scaling proposed between infrastructure and population. Furthermore, the cross-city scaling between area and population transitioned from linear to superlinear over time, and the superlinear scaling in recent times suggests decreased infrastructure efficiency. Our results demonstrate a diseconomy of scale in urban areal expansion that indicates a significant waste of land resources in the urbanization process. Future planning efforts should focus on policies that increase urban land use efficiency before continuing expansion.

On the relation between transversal and longitudinal scaling in cities

“…The result (10) also suggests that if F ext > 0 and b i > 1, which means that both the intercept parameter (global growth) and the population are growing in time, then β i will always be greater than the global exponent β T . The increment in the intercept implies a more accentuated slope of the city trajectory in the plane ln Y-x-ln N (that is, bigger β i ) in relation to the transversal trajectory (related to β T ), in accordance with empirical observations brought by our study as well as other evidences available in recent literature [49][50][51]. To sum up, the transversal and longitudinal scaling exponent will only be the same when:…”

“…In short, does an individual city growing in time follow the same scaling pattern observed for a snapshot of a group of cities? In the last years, few works have accurately focused on the dynamics of individual cities [47][48][49][50][51], while a growing literature has been concentrating on the scaling properties of sets of cities. We call the former longitudinal scaling properties, which take into account the evolution of individual cities in time, and the latter transversal scaling across an urban system, i.e., computed from the set of cities that compose the system.…”

“…In turn, Hong et al argued that longitudinal and transversal exponents are correlated, but it is essential to eliminate global effects to properly measure the longitudinal scaling exponent [50]. Another work has found that the power-law scaling of 32 major cities in China could adequately be characterized for both transversal and longitudinal scaling [51]. More recent work also analyzed the issue for the wage income in Sweeden and found superlinear scaling for both longitudinal and transversal scaling, but the former was characterized by larger scaling exponents [48].…”

Contemporary Urban Expansion in the First Fastest Growing Metropolitan Region of China: A Multicity Study in the Pearl River Delta Urban Agglomeration from 1980 to 2015

“…Combining them, we could get the third metric population per unit area, which contains information on population density. Furthermore, GDP per unit of urban land area was used to present land use efficiency of wealth creation [34,35]. We ranked these four indicators to explore the differences among cities and intraurban agglomeration dynamics.…”

Does China's City-Size Distribution Present a Flat Distribution Trend? A Socioeconomic and Spatial Size Analysis From DMSP-OLS Nighttime Light Data

“…Ci ty-size distribution (CD) has consistently remained a topic of interest in urban geography and economics [1][2][3]. Since Auerbach [4] found that CD followed a Pareto distribution in 1913, an increasing number of scholars have focused on the analysis of this rule [5,6].…”