Integrating Points-of-Interest and Areas-Of-Interest for Commercial Space Pattern Analysis

Abstract

Abstract Commercial space pattern (CSP) analysis is an important topic in geographic research. Most studies on CSPs are conducted on a grid or block scale and therefore are unable to meet the requirements of refined CSP analysis. As geographic places that people can experience in urban environments, areas of interest (AOIs) provide a new research perspective for CSP analysis. Hence, a refined study on the CSP is presented, taking the Yuexiu district of Guangzhou as an example that integrates AOI and point-of-interest data extracted from AutoNavi Maps using kernel density analysis. The results show the following: the Yuexiu district has a multicore business development structure with relatively highly clustered business-operation AOIs. The approach in this study can help better discover business features, analyze more refined CSPs, and provide a new perspective for CSP research, making it valuable for understanding urban commercial spaces and optimizing commercial layouts.