山东省人口密度分布模式的GIS空间分析  

A Study of the Population Spatial Distribution Model Based on Spatial Statistics in Shandong Province

作　　者：朱瑜馨[1,2] 张锦宗[2] 聂芹[2] 

机构地区：[1]北京师范大学地理学与遥感科学学院,北京100875 [2]聊城大学环境与规划学院,聊城252059

出　　处：《国土资源遥感》2011年第4期147-150,共4页Remote Sensing for Land & Resources

基　　金：山东省软科学基金项目(编号:2009RKB131);聊城大学青年项目(编号:X071015)

摘　　要：利用2010年山东省第六次人口普查数据,借助GIS技术,运用空间统计分析方法,对山东省17地市人口空间分布模式进行分析。采用四分位数计算方法和Moran’s I和Local Moran’s I指数研究方法分析可知,2010年山东省17地市人口密度的空间分布模式存在空间集聚现象,总体上以济南、淄博为中心大致划分为高密度区、较高密度区和较低密度区3个空间条带形区域,没有出现高值和低值异常的空间区域;山东省17地市人口密度呈正的空间自相关,空间分布并非处于完全的随机状态,表现出相似值之间的空间聚集:西部和南部5个地区存在着明显的"高-高"集聚;北部4个地区存在着明显的"低-低"集聚;存在着莱芜和日照两个"低-高"关联及潍坊市"高-高"关联的孤立点。Spatial autocorrelation has been applied to extensive data obtained from many research projects,and it is a common method for studying spatial distribution.Spatial autocorrelation analysis is a means for analyzing data correlation based on the spatial correlation analysis.It studies the correlation between one polygon and the nearest neighboring polygon through recognizing the similar degree of the major spatial object and other spatial objects.Using the 2010 census data and applying the spatial statistics and GIS,the authors analyzed the models of population spatial distribution of 17 prefectures in Shandong province by such means as quarters of population density,Moran＇s I and Local Moran＇s I.The population spatial correlation shows that there are no abnormal spatial areas of high density and low density in prefectures of Shandong province.The population spatial correlation shown by Moran＇s I and Local Moran＇s I indicates that the population density spatial distribution has spatial cluster,high-high cluster and low-low cluster.The general population density spatial distribution has three spatial belt-shaped regions,where the highest density is in the southwest areas,the density decreases to the lowest density in the northeast areas,and the similar population density areas are centralized in the vicinage.There are 5 ＂high-high＂ prefectures centralized in the west and south areas,4 ＂low-low＂ prefectures centralized in the north areas,2 ＂low-high＂ relation isolated points existent in Laiwu and Rizhao and a ＂high-high＂ isolated point existent in Weifang.

关 键 词：空间统计 空间自相关 空间模式 人口密度 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]