SCIENTIA GEOGRAPHICA SINICA ›› 2019, Vol. 39 ›› Issue (3): 442-449.doi: 10.13249/j.cnki.sgs.2019.03.010

Previous Articles     Next Articles

POI-based Spatial Correlation of the Residences and Retail Industry in Shenyang City

Bing Xue1,2(), Xiao Xiao1,2, Jingzhong Li2,3, Xiao Xie1,2, Chengpeng Lu1,2, Wanxia Ren1,2   

  1. 1. Key Lab of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, Liaoning, China
    2. Key Lab for Environmental Computation and Sustainability of Liaoning Province, Shenyang, 110016, Liaoning, China
    3.College of Urban Planning and Architecture, Xuchang University, Xuchang, 461000, Henan, China
  • Received:2017-12-22 Revised:2018-03-11 Online:2019-03-10 Published:2019-03-10
  • Supported by:
    National Natural Science Foundation of China (41471116,41701142,41701466), Sci & Tech Department of Liaoning Prov (201602743), Sci. & Tech. Department of Shenyang City(17-117-6-00, Z17-7-030), Youth Innovation Promotion Association CAS(Xue Bing, 2016181)


It is a crucial research content of human-economic geography to quantitatively research the spatial correlation between urban residences with its price and the regional commercial service. Taking Shenyang City in Liaoning Province as a case study and using the residential and retail points of interest (POI) as a data source, this paper extracted the spatial clustering patterns of various residences based on the spatial kernel density analysis method, and then quantitatively expressed the correlation between commercial and residential spatial distribution. On this basis, this paper used the geo-statistical method to measure the spatial heterogeneity of houses prices and measured the impact of retail format layout on houses prices. Solutions presented in this research can be summarized as follows: The overall spatial aggregation characteristics of retailing are similar to that of dwellings, the distribution pattern of the central urban agglomeration and the multi-centers dispersion in the periphery city is presented. The correlation coefficient between retails’ density and residences’ density is 0.95. There is a strong correlation between residences, and some small-scale retails including supermarkets and convenience stores, the aggregation effect of shopping malls is lagging behind the urban dwellings. Large retail’ should be located in the Tiexi eco-technological development zone and other similar residential areas, in order to provide residents advanced shopping services. The inverted ‘U’ type spatial distribution model that houses prices presented is consistent with the attenuation characteristics of retail space’s density.

Key words: POI data, urban residential prices, correlation between commercial and residential space, Shenyang City

CLC Number: 

  • F129.9