基于大数据的南京市中心城区房价空间分布特征及建成环境影响研究

Research on the Spatial Distribution Characteristics and Built Environment Effects of Housing Prices in the Central Urban Area of Nanjing based on Big Data

采用链家网收录的2018年、2020年及2022年的二手房交易价格数据,通过克里金插值法研究南京市中心城区房价空间分布格局,进一步构建时空地理加权回归(GTWR)模型,并基于最小二乘法(OLS)进行比较,揭示不同建成环境因子对该空间分异的影响。研究发现,南京市中心城区房价空间分布态势以古都文化核及河西片区为中心高值区域,向四周递减,总体与规划政策的空间引导结构保持一致;开发建设强度和公交可达性对房价的影响作用最为显著,但基于不同区域的建设情况和居民需求差异,影响效果差别较大。应制定精细化的空间发展政策,以响应空间存量发展时代下的住房质量化发展需求。

Utilizing the second-hand housing transaction price data from Lianjia.com in 2018,2020 and 2022,this research examines the spatial distribution pattern of housing prices in the central urban area of Nanjing by applying Kriging interpolation method.Moreover,it develops a Geographically and Temporally Weighted Regression(GTWR)model and contrasts it with the Ordinary Least Square Regression(OLS)method to disclose the influence of various built environment factors on the spatial differentiation.The study reveals that the spatial distribution trend of housing prices in the central urban area of Nanjing is marked by a high-value area around the ancient capital culture core and Hexi area,which diminishes progressively to the peripheral areas,and aligns with the spatial guidance structure of planning policies.The development intensity and public transport accessibility exert the most substantial impact on housing prices,but the impact effects differ considerably according to the construction conditions and resident demand variations in different regions.It is recommended to devise refined spatial development policies to address the housing quality development demands in the era of spatial inventory.