西安市主城区居住空间住宅价格分布格局与驱动机制

Analysis on the Pattern of the House Price and Its Driving Forces in the Dwelling Space in the Urban District of Xi'an

采用探索性空间数据分析法(ESDA)、地理加权回归(GWR)等手段,定量分析西安市主城区居住空间住宅价格分布格局与驱动机制,并辅以定性探讨。研究结果表明:(1)西安市新房与二手房分布密度呈现城南城北大于城东城西的空间布局形式,新房居住空间呈现出二环以外大明宫—张家堡、曲江—电视塔、高新区南二环—锦业路3个连续组团,二手房居住空间呈现整体南倾的格局。(2)商业中心位置与大部分居住空间布局关系不紧密;随文化景观要素和重点中学要素的距离增加,大部分居住空间住宅价格降低;距离交通干线越近居住空间住宅价格不一定越高。(3)产业布局会影响西安市居住空间布局,城市整体路网密度的提升可能会弱化交通通达因素的影响,学区与景区周边的确出现了较显著的住房需求,而政策引导可以直接形成新的居住空间发展热点。基于先进的空间统计算法,可以有效提升研究结果的空间精度;而将新房与二手房对比出现,实现了空间换时间的数据处理方式,从而可以根据价格格局现状间接推断居住空间的演变。

In this article, exploring spatial data analyze （ESDA） and geographical weighted regression （GWR） was adopted as research method. The spatial pattern and driving forces in Xi＇ an＇ s urban district were quantified, and some qualitative discussions were added. The results were as follows. （1） The spatial pattern of density distributions for Xi＇ an＇ s new house and second-hand house prices were appeared as it dense higher in the north and south than in the east and west. The dwelling space spatial pattern for new house was organized as three groups, and for second-hand house the pattern was entirely south bias. （2） In the qualitative driving forces analyze, there was not a close relationship between commercial center distance and most dwelling space distributions; the further distance from culture landscape and key middle school, the lower of house price in the dwelling space; the house price was not always higher when it closer to the traffic artery. （3） The industrial layout may affect Xi＇ an＇ s dwelling space distribution ; the promotion of city road network density may reduce the traffic factor affection to dwelling space; the house requirement in school district and scenic spot was apparently high; and the new developing hot spot of dwelling space could be formed by policy guidance. In this article, advanced spatial statistic methods were adopted which could efficiently raise the precision. Use the compare between new house and second-hand house was a spatial to temporal method, which could indirectly infer the dwelling space evolution by the present situation of price patterns.