Polycentric Urban Development and its Determinants in China: A Geospatial Big Data Perspective

Abstract

The urban structure of large Chinese cities has been well researched, but a systematic analysis of polycentric urban development and the determinants of subcenter formation across municipal districts in cities at the prefectural level and above (PLACMD) is lacking. Using geospatial big data and spatial analysis methods, we measure the urban spatial structure of all 294 PLACMDs to determine the polycentric urban structure in China and conduct an exploratory regression analysis of 59 PLACMDs (due to data restrictions) to explore the formation of polycentric cities. Our results suggest that using location‐based data allows for a timelier and more accurate center identification of detailed urban structural features than using other data. Each PLACMD in China has at least one center, and polycentricity is currently the most common urban spatial structure. PLACMDs with higher populations are more polycentric. Compared with the results obtained from large American urban areas, our regression results imply that population alone accounts for most of the variation in the polycentric index and that commuting costs provide a weak explanation of the existence of Chinese PLACMDs. Both economic development and agglomeration economics are associated with the polycentric index. In contrast, the topographical features are statistically nonsignificant in the regression model.