【摘要】 基于重庆市渝中区298个小区共计2685个住宅样本点,利用GIS空间分析的网络分析和视域分析工具,在特征价格模型的框架下采用地理加权模型分析重庆市渝中区生态景观对住宅价格的空间影响。结果表明:(1)不同公园绿地和水体对住宅价格的影响力不同。(2)综合公园、专类公园距离与房价呈空间负相关,社区公园、游园对房价的影响小。(3)湖景距离、两江距离与房价呈空间负相关,湖景视域、两江视域与房价呈空间正相关。(4)与特征价格模型相比,地理加权模型对房价的解释能力提高了约23%,为厘清生态景观对房价的影响机制、优化城市生态空间提供参考。更多还原

【Abstract】 Based on 2685 residential sample points in 298 communities in Yuzhong district of Chongqing city, using the network analysis and viewshed analysis of GIS spatial analysis, geographically weighted model was used to analyze the impact of urban landscape on housing prices in the framework of the characteristic price model. The results show that:(1) Different parks and water have different influences on housing prices.(2) The distance of comprehensive parks and special parks is spatially negatively correlated with housing prices, while community parks and street parks have little effect on housing prices.(3) The distance of lakes and rivers is spatially negatively correlated with housing prices, and the visibility of lakes and rivers is spatially positively correlated with housing prices.(4) Compared with the hedonic price model,geographically weighted regression model’s ability to interpret house prices has increased by about 23%,providing a reference for clarifying the mechanism of ecological landscape’s impact on housing prices and optimizing urban ecological space.更多还原