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基于道路网络的商业网点市场域分析 被引量:26

Delimitating the store market field based on the metric of the city-block distance
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摘要 社会经济活动中人们的空间行为往往是基于道路网络来实现的。但是,目前多数研究都假设地理空间是一个均质空间,采用基于平面欧氏距离的空间分析方法,这是有局限的。本文阐述了基于网络距离的网络Voronoi图基本概念和实现方法,以武汉市商业零售连锁企业为例,分别采用基于欧氏距离的普通Voronoi图方法和基于网络距离的网络Voronoi图方法来确定商业零售网点的市场域,结果表明武汉市主城区商业网点市场域较小、主城区外围市场域较大。市场域大小与城市路网密度呈现一定相关关系,路网密度高、市场域小,路网密度低、市场域大。两种方法的计算结果存在一定差异,差异大小与路网密度有关,路网密度大、差异小,路网密度小、差异大。这表明在路网密度大的情况下,可以采用普通Voronoi图粗略地模拟商业网点的市场域。 In social and economic activities, people usually actualize their spatial activities on road networks. However, most research results were on the ideal condition that geographical space was a homogeneous one, and almost all spatial analysis methods are according to the metric of planar Euclidean distance, its drawback is quite obvious. This paper presents the principle and the constructing method of network Voronoi diagrams, and the application of ordinary Voronoi diagram and network Voronoi diagram to the delimitation of the market fields of 17 stores in Wuhan, Hubei Province, China. The main results are as follows: (1) The market fields in the inner city are quite small while the ones in the outer city are a little large. If the road density in a store trade region was low, its area would be small; conversely, provided the road density in a store trade region was high, its area would be quite large. (2) There is a more or less difference between the application results of the methods based on ordinary Voronoi diagram and network Voronoi diagram. If the road density of a region was high, the difference would be small; and vice versa, there was a great difference in a region with a low road density. This shows that the method of ordinary Voronoi diagram can be chosen as a substitute of network Voronoi diagram to define the market fields of a store system in case of a region with a high road density.
出处 《地理研究》 CSCD 北大核心 2008年第1期85-92,共8页 Geographical Research
基金 地理信息科学教育部重点实验室开放研究基金资助项目
关键词 商业网点 市场域 VORONOI图 网络距离 欧氏距离 chain stores market field Voronoi diagrams network distance planar Euclidean distance
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