摘要
以长沙市为研究对象,在空间自相关分析的基础上分别采用Kriging和Cokriging方法构建空间插值地图,并通过对比分析探讨住房价格空间格局特征。结果表明:1与Kriging方法相比,考虑多区域因素的Cokriging方法其空间插值预测精度更高,结果更佳;2长沙市住房价格的空间自相关性显著,南北向和东西向都呈二阶形态由中心向边缘递减,住房价格变化的空间变异表现为各向异性;3长沙市住房价格的空间格局整体表现为同心椭圆分布,核心圈层为传统的五一商圈,南北向扩散态势明显;4长沙市住房价格变化幅度区域性差异显著,二环内等值线分布密集,河西相较河东,等值线分布较为稀疏,价格衰减较慢。
The regional differences of house price distribution and the variance degree indicate that the spatial stability condition of house price regression analysis is not satisfied, so the consideration of regional variables in discussing the house price spatial distribution difference has become a new direction of studying house price. In order to examine the house price distribution pattern from region＇s multi-attributes, and enhance the evaluation accuracy, this paper, based on spatial auto correlation analysis, takes Changsha city as the case to comparatively study its house price spatial distribution pattern by interpolated maps from Kriging and Cokriging methods. The results show： 1） Cokriging method, with the consideration of regional multi-attributes, is more accurate in interpolating prediction than that of Kriging; 2） The house price of Changsha city is significant in spatial correlation, and the directions of south- north and east- west are secondorder decreasing from core to periphery, so the spatial variance of prices are heterotopic in their directions; 3） the whole spatial distribution of Changsha price is concentric oval like, and the core is traditional Wuyi business circle, and the direction of south- north has obvious tendency to proliferate; 4） the house price variance is regionally significant, and isolines in second ring are dense, while Hexi＇s（west district to Xiangjiang river） isolines are much sparser than that of Hedong（east district to Xiangjiang river）, so its price is more slowly decaying.
出处
《经济地理》
CSSCI
北大核心
2014年第12期99-105,共7页
Economic Geography
基金
国家自然科学基金项目(71171203)
湖南省教育厅科学研究青年项目(13B008)
湖南省城市经济研究基地资助项目
