文献类型：期刊文献

中文题名：河南省人口城镇化特征及影响因素的空间异质性

英文题名：Spatial Heterogeneity Analysis of Affecting Factors of Population Urbanization in Henan

作者：杨勇[1];杨忍[2]

第一作者：杨勇

机构：[1]河南财经政法大学资源与环境学院;[2]中山大学地理科学与规划学院

第一机构：河南财经政法大学资源与环境学院

年份：2014

卷号：30

期号：5

起止页码：60-65

中文期刊名：地理与地理信息科学

外文期刊名：Geography and Geo-Information Science

收录：CSTPCD;;国家哲学社会科学学术期刊数据库;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

基金：国家自然科学基金项目(41101128);河南省教育厅科学技术研究重点项目(14A170002)

语种：中文

中文关键词：城镇化;空间异质性;地理加权回归;河南省

外文关键词：urbanization; spatial heterogeneity; GWR ; Henan Province

摘要：采用变异系数、空间自相关和地理加权回归(GWR)等方法,分析了欠发达农区河南省1991年、2000年和2010年县域城镇化的时空动态变化,并对影响因素的空间异质性进行了分析。结果表明:河南省的城镇化初始呈低层次均衡,局部高值县区日趋集聚,总体差异程度减弱,城镇化率显著提高的县区主要分布在京广线以西,县区城镇化呈全局弱正自相关。分别采取OLS和GWR模型对社会经济发展水平、区位条件和产业结构等方面的8个影响因子进行分析,OLS和GWR分析显示第一和第二产业产值比重对所有县区城镇化为负效应,人口密度对所有县区为正效应,而GWR分析结果为变参数,因子的系数有正有负,表明各因素的影响效应存在显著的空间差异。
The spatial and temporal characteristics and heterogeneity of affecting factors of the county urbanization in Henan were analyzed systematically since 1991, using the methods including coefficient of variation, spatial autocorrelation and geo- graphically weighted regression. The results showed that the temporal and spatial differences of the county urbanization were significant, the county urbanization of Henan is in an low level equilibrium initially, then tends to cluster among some high value counties, the overall difference is weakened, the counties that urbanization rate increased significantly are mainly distributing in the west of Beijing-Guangzhou Railway, the county urbanization is weak positive autocorrelation globally. Selecting eight factors of social economic development level,location conditions and industrial structure, this paper makes an OLS and GWR analysis respectively, the results indicate that the first and second industry output value proportion to all the counties comes into negative effect, the population density of all counties is positive effect, the result of GWR analysis is an variable parameter, coefficient of factors can be positive or negative, effects of affecting factors shows an significant spatial difference.