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甘肃省人口老龄化空间分布及演变特征分析
引用本文:马晓理,张旺锋,薛海燕,李坤.甘肃省人口老龄化空间分布及演变特征分析[J].西北人口,2014(6):115-121.
作者姓名:马晓理  张旺锋  薛海燕  李坤
作者单位:兰州大学 资源环境学院,兰州,730000
摘    要:本文以甘肃省各县区为研究对象,选取1990年、2000年、2010年的人口普查数据,分别计算各县区老年人口比重和老年人口密度。首先应用Arc GIS软件分析老龄化人口的时空分布特征,并通过重心计算均衡点;其次应用Geo Da软件对老年人口分布进行空间自相关分析;最后,从人口、经济、社会角度探索性地分析导致空间分布差异的原因。研究结果表明:甘肃省老龄化现象呈现由东南向西北推进的扇形模式,老年人口密度呈现以兰州市及周边地区为圆心的同心圆扩展模式,老龄化重心位置逐渐向兰州市靠近;老龄化空间分布具有较显著的自相关性;老龄化空间分布差异与人口、社会和经济发展具有一定的关系。

关 键 词:老龄化人口  空间分布特征  空间推进模式  空间自相关

Analysis of the Spatial Distribution and Evolution Characteristics of the Aging of Population in Gansu
MA Xiao-li,ZHANG Wang-feng,XUE Hai-yan,LI Kun.Analysis of the Spatial Distribution and Evolution Characteristics of the Aging of Population in Gansu[J].Northwest Population Journal,2014(6):115-121.
Authors:MA Xiao-li  ZHANG Wang-feng  XUE Hai-yan  LI Kun
Institution:(College of Earth and Environmental Sciences ,Lanzhou University,Lanzhou Gansu province 730000)
Abstract:Taking each country in Gansu province as the research object and choosing the census data which include 1990,2000 and 2010 to calculate the proportion of elderly people and the density of elderly people in various counties. Firstly, this paper applies ArcGIS to analysis the temporal and spatial distribution characteristics of aging population in each country, and through the center of gravity to determine the equal area;Secondly,this paper applies GeoDa to analysis spatial autocorrelation of aging population in each country;Finally ,this paper explores the causes of spatial distribution from population, economy and society. The results show that:the aging phenomenon in Gansu province presents fan mode extending from southeast to northwest, the density of the aging presents concentric circle model extending from Lanzhou and the surrounding areas as the center,the gravity of the aging gets closer to Lanzhou ;The spatial distribution of the aging are auto correlated signifi- cantly;The difference of spatial distribution of the aging is related to the development of population, economy and society.
Keywords:Aging population  Spatial distribution characteristics  Space propulsion mode  Spatial autocorrelation
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