Affiliation:
1. School of Geographical Sciences and Tourism, Jilin Normal University, Siping 136000, China
2. State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
Abstract
Using the Urban Network Analysis Tool, the centrality of a road network (closeness centrality, betweenness centrality, and straightness centrality) was calculated, and the POI data of the commercial facilities were reclassified. KDE estimation was used to estimate the centrality of the traffic network, and the correlation coefficient was calculated to explore the spatial relationship between road network centrality and the types of commercial facilities (catering facilities, shopping facilities, residential life facilities, and financial and insurance facilities). The results indicate the following: (1) Closeness centrality displays a discernible “Core–Periphery” pattern, and the high-value areas of betweenness centrality are mainly concentrated around the main arterial roads of the city. In contrast, straightness centrality unveils a polycentric structure. (2) The spatial distribution of commercial facilities demonstrates a notable correlation with the centrality of the road network. From the perspective of centrality, the distribution of residential life facilities is most strongly influenced by road network centrality, followed by financial and insurance facilities and then catering facilities, with the distribution of shopping facilities being the least affected. (3) The centrality of the road network plays a crucial role in shaping the arrangement of commercial facilities. Closeness centrality significantly influences the distribution of residential life facilities, catering facilities, and shopping facilities. Betweenness centrality has a noteworthy impact on the selection of locations for financial and insurance facilities, as well as residential life facilities. Furthermore, areas characterized by better straightness centrality are preferred for the distribution of residential life facilities, financial and insurance facilities, and catering facilities. (4) The centrality of the road network has a greater influence on the arrangement of various commercial facilities than the population distribution.
Funder
National Natural Science Foundation of China
Young Scientist Group Project of Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences
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