广州市商业型健身房空间分布及其影响因素

以百度地图网页上采集的POI数据和第六次人口普查数据为基础，借助ArcGIS 10.2和Geoda软件，通过核密度分析、方向分布分析、缓冲区分析、近邻分析和空间自相关等方法，对广州市商业型健身房的空间分布特征进行研究，结果表明：广州市商业型健身房在空间分布上呈现“中心圈层＋外围组团”结构，存在空间集聚现象以及沿城市干道和地铁站分布指向性不明显而呈现临近住宅小区分布指向性。在广州市商业型健身房空间分布的影响因素方面，经过模型比较，选择空间滞后模型对其进行定量分析，结果表明：人口规模与受教育水平对广州市商业型健身房的空间布局影响显著，而区位因素和社区环境影响力较小。

Spatial Distribution and Its Influential Factors of Commercial Fitness Clubs in Guangzhou

As a fast-growing industry in recent years, commercial fitness clubs have become significant parts of consumer services industries. However, relatively few studies on the spatial distribution of commercial fitness clubs in a city have been conducted at the street and town level. In addition, there are few studies on factors influencing the spatial distribution of commercial fitness clubs by quantitative analysis methods. To make up for this deficiency, this paper analyzed the spatial distribution of commercial fitness clubs utilizing the methods of GIS spatial analysis and spatial auto-correlation on the basis of POI data of 743 commercial fitness clubs, 136 subway stations and 6 013 residential neighborhoods in Guangzhou City collected from online map. Furthermore, spatial lag model (SLM) has been adopted to explore the influential factors of the spatial distribution of commercial fitness clubs in Guangzhou based on the latest demographic and housing-related data from the 6th population census in 2010 in Guangzhou. The results show: 1) The spatial distribution of commercial fitness clubs in Guangzhou is unbalanced and its quantity decreases generally from the central urban area to surrounding regions where small clusters exist as well, which shows a “center circle + peripheral group” structure. Specifically, 70.52% of the commercial fitness clubs are located in the central urban area, and the rest 29.48% which are located in the surrounding regions mostly gather in central towns. There is significant spatial agglomeration and correlation of commercial fitness clubs in Guangzhou. 2) Only a few commercial fitness clubs are located along main roads or near subway stations, while most of the commercial fitness clubs, accounting for 94.21%, are located near residential neighborhoods. That is to say, the distribution along city roads and subway stations is not obvious, but obvious near residential neighborhoods. 3) With regard to the influential factors on the spatial distribution of commercial fitness clubs, population scale and educational level play more important roles than location factors and community features. Both of these two demographic characteristics have positive impact on the quantity of commercial fitness clubs in townships. This result proves that market is a significant factor influencing the spatial distribution of consumer services industries. In this paper, it is found that the location factor is not a key factor affecting the spatial distribution of commercial fitness clubs in Guangzhou, which is different from previous views that location factors, especially traffic location, have essential effects on the spatial distribution of consumer services industries. The findings in this paper would enrich the research on spatial distribution of consumer services industries.