银川市城区房价空间分异与影响因素分析

Analysis on Spatial Differentiation and Influencing Factors of House Prices in Yinchuan City

利用多尺度地理加权回归模型对银川市2020年4—9月住宅价格均价进行分析,以探究多种影响因子对住宅价格空间异质性的影响。结果表明:(1)相较于地理加权回归模型,多尺度地理加权回归模型回归细致、拟合更好,能更好地反映影响因子的影响范围。(2)银川市“一主两副”的住宅价格分布格局与城市发展过程基本一致,呈现出东西向条带状分布的空间特征,并逐渐向“条带”的南北两端扩展。(3)距中小学的距离是影响住宅价格的最主要因素,公共休闲因子次之;娱乐场所负向影响住宅价格;金融设施、商务配套、医疗服务、路网密度和建造时间在全局范围内对住宅价格具有正向影响。

The average housing prices in Yinchuan from April to September 2020 was analyzed with the multi-scale geographically weighted regression model to explore the impact of various factors on the spatial heterogeneity of housing prices.The results show that compared with the traditional geographically weighted regression model, the multi-scale geographically weighted regression model fits better and presents more detailed regression, which can better reflect the impact of the factors.The housing price distribution pattern of “one core and two subsidiaries” in Yinchuan City is basically consistent with its urbanization, showing a spatial characteristics of east-west strip distribution and expanding to the north and south ends.Distance from primary and secondary schools is the most important factor affecting housing prices, followed by public recreation.While entertainment venues negatively affect housing prices, financial facilities, business facilities, medical services, road network density and construction time have a positive impact on housing prices on the whole.