Rethinking the Identification of Urban Centers from the Perspective of Function Distribution: A Framework Based on Point-of-Interest Data

Abstract

Urban spatial structure has a significant impact on the sustainable development of cities. An important step of urban spatial structure analysis is the identification of urban centers. From the perspective of urban function distribution, this study developed a theoretical framework of three layers for urban center identification. In the first layer, point-of-interest data were collected from geospatial databases and utilized to capture the spatial distribution of urban functions. In the second layer, the density-based spatial clustering of application with noise (DBSCAN) algorithm was employed to group points of interest into urban centers according to their inter-distances and urban functions. In the third layer, the spatial distribution of the identified urban centers was visualized by the ArcGIS platform. This framework was applied in the urban center analysis of Beijing. The results showed that Beijing is in the process of transitioning from monocentric to polycentric with urban functions distributed unevenly throughout the city. To facilitate this transition, strategies such as the construction of super-large communities, the development of branch campuses and higher-education parks, and the enhancement of modern culture industries should be considered for the 11 new towns of Beijing.