Abstract
The research target is the health club,which is a special type of the recreation space in a city. Based on GIS and geostatistical software,using point pattern identification and ESDA(exploratory spatial data analysis) methods,the paper analyzes the spatial pattern characteristics of health clubs in Beijing. The nearest neighbor indicator (NNI) and quadrat analysis results indicate that the health clubs cluster together evidently at a whole region scale. But if we observe the pattern in the units separated by the roads or district,it presents different spatial patterns,varying from clustering to random,even dispersing. The analyzing results of health clubs based on the 5 scale cell units from 1 km to 5 km grids make further explanation that its spatial pattern are influenced evidently by the units' scale. At any scales the density and NNI of health club samples have evident spatial diversification. From the Moran's I statistics and Moran Scatterplot Map we also find the evident spatial autocor-relation of the units. The 2 km and 3 km unit scales are the best scales for finding the microscopic spatial pat-tern and diversification. So the whole region scale is not the only or the best scale for spatial pattern research of recreation spaces especially for the health clubs. In some microscopic units the spatial pattern will be more evident and the research results will even be opposite to that at the whole region scale. The pattern description based on more statistical units at various scales may discover the points' distributional characteristics and the patterns more easily. The spatial pattern research of health club points in units at various scales provides a new way of describing spatial patterns of recreation space points. And the effects of such a way are also demonstrated in this paper.
Published Version
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