基于Voronoi图的高密度城区停车场空间布局分析——以广州市海珠区为例
收稿日期: 2012-11-09
修回日期: 2013-01-29
网络出版日期: 2013-06-17
基金资助
国家自然科学基金项目(41171446,31170445);资源与环境信息系统国家重点实验室开放基金项目(2010KF0006SA)。
Analysis of Spatial Distribution of Parking Lot in High Density Urban Area Based on Voronoi Diagram: Take Haizhu District in Guangzhou City as a case
Received date: 2012-11-09
Revised date: 2013-01-29
Online published: 2013-06-17
停车场是高密度城区基础设施的重要组成部分,对人口、道路、建筑等具有一定空间依赖,并形成其特定的分布规律。本文以广州市海珠区为例,运用Voronoi图对高密度城区停车场空间布局特征和空间聚集度与其影响因子的空间自相关性进行了GIS系统分析。通过研究区内及各街道区域内建立停车场Voronoi多边形,计算CV值、聚类指数及停车场聚集度。分析表明:(1)在高密度城区内,全区范围及各街道区域内停车场有集聚布局的趋势。集聚核出现在西北面江南大道商业圈和北面广州新中轴线贯穿的海珠区中心区段,高密度城区停车场有围绕商圈、中心发展区等高密度城区特征,突出区域集聚的趋势。(2)人口密度、道路密度、建筑密度等因子在全局及局部上影响着停车场的空间布局,而人口密度的影响最明显。(3)高密度城市化发展水平越高,各影响因子对停车场的密度与集聚程度影响越显著。
张杏娟, 文雅, 吴志峰, 程炯 . 基于Voronoi图的高密度城区停车场空间布局分析——以广州市海珠区为例[J]. 地球信息科学学报, 2013 , 15(3) : 415 -421 . DOI: 10.3724/SP.J.1047.2013.00415
As the important part of infrastructure in high density urban area, spatial distribution of parking lot relies on population, roads and buildings. Under the influence of various factors, parking lot in high density urban areas owns a specific distribution rule. Combining GIS with Voronoi diagram, we discussed the spatial distribution characteristics and co-agglomeration of parking lot in high density urban areas, and analyzed the spatial autocorrelation between parking lot and various factors. Taking Haizhu District in Guangzhou City as a case, we calculated CV value and clustering index by building Voronoi diagram in the researched area and streets. Through the analysis, we know that the parking lots agglomerated markedly in the whole district and every street. In high density urban areas, parking lots tend to gather in commercial circle and economic center such as Jiangnan Road commercial circle and center section of Guangzhou new axis which run through Haizhu District which are the cluster center of parking lots. It showed that population density, building density and road density affect the spatial distribution of parking lots obviously with two variable regional spatial autocorrelation analysis, which population density perform more significantly. Higher the development level of the high density city, more obvious the effect of various factors on density and the degree of agglomeration of parking lots.
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