Spatial patterns of retail stores using POIs data in Zhengzhou, China

摘要

Identifying spatial patterns of geographic entities such as retail stores is important in city for understanding how they behave. The pattern formed by the distribution of points can be measured by some quantitative methods. In Big Data era, the data sets for spatial patterns analysis are various including traditional street network data and points of interest (POIs) data in LBS (Location based services) application. This paper analyzed the spatial pattern of retail stores and its correlations with street centrality using POIs data in Zhengzhou, China. Firstly, the paper provided an exploratory analysis of spatial patterns using the centrographic methods including Standard Deviational Ellipse and Average Nearest Neighbor. Secondly, the paper uncovered the spatial distribution of retail stores using the kernel density estimation (KDE). Finally, the paper calculated the street centrality of Zhengzhou using three centrality assessment indexes and converted all nodes centrality index values to raster pixel using KDE for correlation analysis. Results show that the retail stores are clustering pattern and mainly elongated along the west-east direction. The street centralities are correlated with the retail store location in Zhengzhou, and there is a different level of correlation between them. The paper reveals that the spatial pattern analysis and street centralities index are valuable in location analysis or urban planning.