南京市住宅价格时空分异格局及其影响因素分析——基于地理加权回归模型的实证研究

以2009-2017年南京市“一主三副”商品房社区为基本研究单元,运用GIS地统计分析中的普通Kriging插值法对“一主三副”住宅价格空间分布进行模拟和估计,并利用地理加权回归（GWR）模型探究社区属性、商业区位、交通区位、服务区位和景观区位等类型变量对住宅价格的影响规律。研究结果表明：①南京市房价总体上呈现主城向副城递减的中心外围模式,“一主三副”住宅价格空间结构呈现出同心圆和扇形融合的混合模型。②中心位势对主城住宅价格影响相对下降,对副城影响相对提升,交通位势表现出相反的趋势,住宅房龄、绿化环境对住宅价格的影响由主城向副城递减,山水景观的影响由长江沿岸向外围递减。③主副城住宅价格影响因素具有空间异质性,其中主城受距CBD距离、住宅建筑年代和绿化率的影响较大,而副城主要受距地铁站距离、距景观资源距离的影响。

SPATIAL DIFFERENTIATION AND INFLUENCING FACTORS ANALYSIS OF HOUSING PRICES IN NANJING: BASED ON GEOGRAPHICALLY WEIGHTED REGRESSION MODEL

Based on 2009-2017 in Nanjing city "one main city and three subsidiary cities" commercial housing community as the research unit, using ordinary Kriging interpolation statistical analysis GIS in the simulation and estimation of the "one main city and three subsidiary cities" housing price spatial distribution, and the use of geographically weighted regression (GWR) model to explore the impact of community property, commercial location, traffic location, service location and landscape location to the housing price. The results of the study show that:1)The housing price of Nanjing city generally shows the central peripheral mode of the main city decrement to the vice city, and the residential price space structure of "one main city and three subsidiary cities" presents a mixed model of concentric circles and fan-shaped fusion. 2) Center of potential impact on the urban housing price relative decline, affect the relative increase of vice city, the transportation potential showed the opposite trend. 3)The main and deputy city house price influence factors of spatial heterogeneity, including central city by the distance from the CBD, residential building age and the influence of green area is larger.