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基于GWR模型的南京市住宅地价影响因素及其边际价格作用研究
引用本文:李志,周生路,张红富,姚鑫,吴巍.基于GWR模型的南京市住宅地价影响因素及其边际价格作用研究[J].中国土地科学,2009,23(10):20-25.
作者姓名:李志  周生路  张红富  姚鑫  吴巍
作者单位:南京大学地理与海洋科学学院,江苏,南京,210093
基金项目:南京市国土科技项目"征地区片综合价实施管理模式研究" 
摘    要:研究目的:以南京市为例,探索城市住宅地价影响因素及其边际作用空间变化性及各因素边际作用大小空间分布状况,为城市土地科学管理提供帮助。研究方法:地理加权回归模型(GWR)。研究结果:(1)地铁站点、商业网点、水景观、绿地公园对住宅地均价的边际影响能力的空间变化性强,高等学校、医院等其他因素边际作用的空间变化性较弱;(2)容积率住宅地价边际增值能力高于其他因素,各因素在具体不同地块上边际作用能力高低不同。研究结论: GWR模型可以改进传统空间回归方法,可对城市地价影响因素边际价格作用空间变化性进行良好的估计;住宅土地价格对快速交通、商服条件及自然景观因素较为敏感,反映主城区人们对住宅便捷性及休憩性呈强偏好;容积率边际增值能力空间变化弱与土地的住宅性用途有关,但容积率始终是边际增值能力最高的因素; GIS良好的输出图像可视化技术能够指导相关部门调控具体地块的主要规划因素,促进城市土地科学管理。

关 键 词:GWR模型  住宅地价  空间变化性  南京
收稿时间:2008-09-28
修稿时间:2009-04-07

Exploring the Factors Impacting on the Residential Land Price and Measuring Their Marginal Effects Based on Geographically Weighted Regression Model: A Case Study of Nanjing
LI Zhi,ZHOU Sheng-lu,ZHANG Hong-fu,YAO Xin,WU Wei.Exploring the Factors Impacting on the Residential Land Price and Measuring Their Marginal Effects Based on Geographically Weighted Regression Model: A Case Study of Nanjing[J].China Land Science,2009,23(10):20-25.
Authors:LI Zhi  ZHOU Sheng-lu  ZHANG Hong-fu  YAO Xin  WU Wei
Institution:School of Geographic and Ocean Science, Nanjing University, Nanjing 210093|China
Abstract:The purpose of this paper is to explore the factors and their marginal effects that impact on the residential land prices in the Nanjing urban areas, which can be used as references for scientifically governing the urban land. Geographically Weighted Regression(GWR) model was employed in the study. The findings include that, (1) the marginal effects of the locations of metro stations, commercial network, water body, green space and public gardens that impact on the average residential land price are significant, while on the contrary those of the location of high schools, and hospitals do not show the same;(2)FAR is the most influential factor that leads the increase of marginal price of residential land among others, and the marginal effects of other factors are also different according to different plots. The paper is concluded with that GWR-based model can improve the traditional space regression methods and can be used to effectively estimate the spatial trends of marginal effects of the factors that impact on urban residential land price. The change of urban residential land prices are sensitive with the availabilities of rapid transportation system, the commerce and service facilities, and natural landscape due to the urban residents prefer these factors. Although the spatial trend of marginal effect of FAR on the incremental land price is weak from the viewpoint of the whole study area, it is always the most influential factors on individual plot. Due to its advantages in visualizing, GIS can be an effective tool in readjusting and controlling the main factors in urban planning, and improve the performance of governing the urban land.
Keywords:GWR model  price of residential land  spatial trend  Nanjing
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