广州市二手住宅价格的空间分异格局及影响机制

采用普通克里金插值法、空间趋势分析法和局部莫兰指数法，揭示广州市2020年二手住宅价格空间分异格局；在综合考虑建筑特征、邻里特征、区位特征和教育特征等影响因素的基础上，构建地理加权回归模型(GWR)，可视化探究各影响因素对二手住宅价格的作用机制。研究发现:广州市二手住宅价格在东西方向和南北方向上均呈现“倒U型”的趋势分布，在整体空间分布上呈现“中心高,周边低”的特点，并在房价水平上表现出较高的空间聚类程度和关联程度。各影响因素对住房价格的影响作用呈现显著的空间差异性，其中，商场和小学对住宅价格的作用表现出商业资源和教育资源服务的局域性；而且，教育资源对住宅价格的空间影响差异程度受政策变化的影响。此外，GWR模型中部分住宅价格样本点的拟合效果不足与局部区域集中的资源优势相关。

Spatial Differentiation Pattern and Influence Mechanism of Second Hand House Prices in Guangzhou City

This paper tries to reveal the spatial differentiation pattern of second hand house prices in Guangzhou City in 2020,using ordinary Kriging,spatial trend analysis and local Morans I,and constructs a geographically weighted regression model (GWR) to visually explore the mechanism of influencing factors each on second hand housing prices considering characteristics of architecture,neighborhood,location,education and other influencing factors.The research finds that second hand house price in Guangzhou City presents inverted U shaped distribution in the east west and south north directions,showing a central high and peripheral low pattern and considerably high spatial clustering and correlation in price level.Impacts of the influencing factors on house prices show significant spatial differences.Among them,impact of shopping malls and primary schools on house prices proves the locality of commercial and educational resources,and the spatial impact of educational resources on house prices is affected by policy changes.Moreover,an insufficient fit of house price sample points in GWR model is correlated with the concentrated resource advantage of local regions.