摘要
以福建省县(区)为研究单元,以道路密度和加权密度为主要指标,运用ArcGIS、GeoDa等软件的叠加分析和空间分析方法,对福建省县域道路密度的空间分布特征进行研究。在此基础上,对人口密度、GDP密度与各县(区)路网密度分布差异之间的相关性进行了初步分析和讨论。结果显示,福建省道路密度的全局Moran's I指数大小为0.640 4,表明福建省道路网络空间分布具有显著的集聚特征和地带性,主要表现为:(1)在闽南和闽东地区分布较集中,而在闽西和闽北地区的分布较稀疏;(2)西北地区呈低-低集聚,而位于高高集聚类型的区县有鼓楼区、台江区、仓山区、思明区、湖里区、集美区和晋江市;(3)不同等级道路的道路密度具有明显的空间聚集性;(4)福建省道路密度分布格局与人口密度、生产总值等密切相关。
Taking Fujian county(district)as the research unit,the road density and weighted density as the main index,using ArcGIS and GeoDa overlay analysis and spatial analysis,the spatial distribution characteristics of road density in the county of Fujian province are studied.On this basis,the correlation between population density,GDP density and road network density distribution in counties(districts)is preliminarily analyzed and discussed.The results show that the global Moran′s I index of road density in Fujian Province is 0.6404,and the spatial distribution of road network in Fujian province has obvious agglomeration and the region,presenting as follows:(1)In the southern and eastern Fujian distribution is relatively concentrated,and distributed in the west of Fujian and the north of Fujian Province are sparse.(2)Northwest area is low agglomeration,and is located in high concentration type districts have Gulou District,Taijiang District,Cangshan District,Siming,Huli District,Jimei District and Jinjiang City.(3)Different grades of the road density has significant spatial aggregation.(4)The distribution pattern of road density in Fujian Province is closely related to population density and GDP.
作者
叶丽敏
邱荣祖
林玉英
史本杰
胡喜生
YE Li-min;QIU Rong-zu;Lin Yu-ying;Shi Ben-jie;HU Xi-sheng(Jinshan College of Fujian Agriculture and Forestry University, Fuzhou 350002 ,China;College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University,Fuzhou 350002,China)
出处
《公路》
北大核心
2018年第5期206-210,共5页
Highway
基金
国家自然科学基金资助项目,项目编号41201100
福建省自然科学基金项目,项目编号2015J01606
福建农林大学金山学院青年教师科研基金项目,项目编号z170405
福建农林大学金山学院青年教师科研基金项目,项目编号z170402
关键词
道路密度
空间自相关
空间回归模型
福建省
road density
spatial auto-correlation
Spatial Regression Model
Fujian Province