Exploring Location Pattern of Commercial Stores in Shichahai, Beijing from a Street Centrality Perspective

Abstract

The location pattern of different commercial stores in Shichahai, a historic conservation area in Beijing, was investigated from a street centrality perspective. Many previous studies have investigated the relationship between street centrality and land use patterns or commercial activities at interurban or intraurban scales. We considered Shichahai in this study to determine if street centrality applied at the street scale and if the street network was the only factor influencing the selection of store location. First, the nearest neighbor index, nearest neighbor hierarchical spatial cluster (NNHSC), and kernel density estimation (KDE) methods were used to provide baseline spatial distributions of commercial stores. Second, urban network analysis (UNA) tools were used to measure the street centrality indices under two conditions, with and without the weighting of cultural relics calculated by a principal component analysis (PCA). Finally, both store locations and centrality values at nodes were transformed to one unit (raster pixel) for a correlation analysis. The results showed that three of the four store types were clustered and had their own hotspots that were mostly located in the eastern and central parts of city blocks. The most momentous findings were determined from the street centrality indices. Among the three store types with correlation coefficients above 0.5, all centrality indices with landmark weighting, except straightness, had higher correlations, with closeness with landmark weighting having the highest correlation, followed by betweenness with landmark weighting. Therefore, we statistically concluded that street centrality could apply at the street scale and that the street network was not the only factor that influenced store location pattern, with landmarks also playing a significant role. The results provide guidance in determining the selection strategy for stores in a historic conservation area.