Geographic Distribution of Urban Retail and its Spatial Relationship with Subway Network

After over two decades of development, Subway has become one of the main transit modes for people's everyday commute, and is considered to attract and form retail clusters around subway stations. Based on a point of interest (POI) dataset of retail stores in Shanghai, this study looks into the geographic distribution of retail stores in Shanghai and examines its spatial relationship with subway network. The retails stores are classified into six types: department stores, specialty stores, convenience stores, restaurants and groceries, recreational facilities and personal service facilities. A series of spatial statistical analysis for measuring geographic distribution, analyzing geographic patterns and mapping clusters are conducted. The spatial pattern shows consistence to the polycentric urban structure of Shanghai and subway stations. In addition, six retail types reveal different extent of spatial clustering at different analysis scales. Last but not least, to qualify the spatial relationship between retail density and other influence factors, including density of population and local bus service, as well as the accessibility to subway station, Ordinary Least Squares (OLS) linear regression is conducted. It turns out that the Kernel Density estimation of retail stores is positively related to population density, bus stop density and existence of subway service, while negatively affected by distance from subway stations. Bus stop density tend to be the most significant influential factors, while department stores enjoy a relatively stronger correlation with distance from subway stations compared to other retail types.