基于GWR模型的天津住宅价格空间分异及影响因子研究  

Spatial Variability and Impact Factors of Tianjin Housing Price Based on GWR Model

作　　者：白一淋 李宁 BAI Yi-lin;LI Ning(Kunming University of Science and Technology,School of Land and Resources Engineering,Kunming,Yunnan;Kunming Institute of Surveying and Mapping,Kunming,Yunnan)

机构地区：[1]昆明理工大学国土资源工程学院 [2]昆明市测绘研究院

出　　处：《软件》2018年第10期126-132,共7页Software

摘　　要：本文利用2017年安居客等地产网站为样本源,对天津市224个住宅小区的平均房价数据,进行空间结构分析、趋势分析、空间自相关分析等,分析住宅价格分异的规律。利用地理加权回归模型,对影响住宅价格的不同因子进行分析,得出影响住宅价格分析的原因。结果表明:政府对住宅价格的影响为正相关;公园、医院、购物中心、高等学校对住宅价格的影响为负相关;综合超市和公交站点的个数对住宅价格的影响既有正相关又有负相关,负相关主要为天津市区的中部和西部,正相关主要为天津市区的东部及边缘区域。This paper makes use of real estate websites such as Anjuke as sample sources in 2017, and analyzes spatial structure analysis, trend analysis, and spatial autocorrelation analysis of the average house price data of 224 residential quarters in Tianjin, and analyzes the law of residential price differentiation. Using geographically weighted regression models, the different factors that affect residential prices are analyzed to determine the reasons for the impact of residential price analysis. The results show that： the government＇s impact on residential prices is positively correlated; parks, hospitals, shopping centers, colleges and universities have a negative correlation with the impact on residential prices; the impact of the number of supermarkets and public transport stations on residen-tial prices is positively correlated. Negative correlations, negative correlations are mainly in the central and western parts of Tianjin, and positive correlations are mainly in the eastern and marginal areas of Tianjin.

关 键 词：住宅价格分异 GWR模型 空间数据分析 

分 类 号：TP170.45[自动化与计算机技术—控制理论与控制工程]