Identifying Urban Agglomerations in China Based on Density–Density Correlation Functions

Abstract

Urban agglomeration (UA) is a special form of organization in which cities spontaneously participate in urban specialization and cooperative ventures and consequently establish socioeconomic and spatial ties with each other in a given region. Due to the unclear definition of UAs, coupled with an insufficient understanding of the UA formation mechanism, however, an objective and effective method for the spatial identification of UAs on an urban theoretical basis is still lacking. Therefore, this article proposes an approach to spatially and quantitatively identifying UAs based on urban density functions and density–density correlation functions. It is applied to delineate Chinese UAs and investigate their spatial distribution and evolution patterns. Three urban attributes (gross domestic product, population, and urban built-up areas) are measured, and the results show that the relationship between overall spatial correlations and distances approximately follows the negative exponential distribution at the national level. Based on these parameters, it is possible to objectively determine Chinese UAs; the analysis shows a belt-like spatial distribution along the major economic and transportation channels. At the UA level, two spatial patterns, fractional Gaussian noise and fractional Brownian motion, are identified, and there is a general transition from the former to the latter over time.