地理研究 ›› 2013, Vol. 32 ›› Issue (12): 2324-2333.doi: 10.11821/dlyj201312026

• 论文 • 上一篇    下一篇

基于GWR的南京市住宅地价空间分异及演变

曹天邦1,2, 黄克龙*1,2, 李剑波1,2, 董平1, 王亚华1   

  1. 1. 南京师范大学地理科学学院, 南京210046;
    2. 江苏金宁达不动产评估咨询有限公司, 南京210036
  • 收稿日期:2013-05-12 修回日期:2013-11-11 出版日期:2013-12-10 发布日期:2013-12-10
  • 通讯作者: 黄克龙(1963- ),男,江苏扬中人,教授,主要研究方向为地理信息系统和土地管理。E-mail:HKL@jsemap.com E-mail:HKL@jsemap.com
  • 作者简介:曹天邦(1968- ),男,江苏兴化人,博士,高级工程师,主要从事地价评估研究。E-mail:njcaotb@163.com
  • 基金资助:
    教育部人文社会科学研究青年基金项目(11YJC840051);国家自然科学基金项目(41071084)

Research on spatial variation and evolution of residential land price in Nanjing based on GWR Model

CAO Tianbang1,2, HUANG Kelong*1,2, LI Jianbo1,2, DONG Ping1, WANG Yahua1   

  1. 1. College of Geographic Science, Nanjing Normal University, Nanjing 210046, China;
    2. Jiangsu Jinningda Real Estate Valuation and Consultation Co., Ltd., Nanjing 210036, China
  • Received:2013-05-12 Revised:2013-11-11 Online:2013-12-10 Published:2013-12-10

摘要: 以南京市主城区为例,在空间自相关分析和蒙特卡罗检验的基础上,构建城市住宅地价地理加权回归模型,通过2003 年、2009 年住宅地价空间分异的对比,探讨不同影响因素对住宅地价影响的空间差异性及其随时间变化的特点,揭示住宅地价及其影响因素的空间变化关系,以促进地价的科学化管理。研究表明:① 随着影响因素数量不断增加以及合理均衡分布,区域差异性缩小,一般会减弱其对地价的影响。② 随着交通条件的不断完善,导致影响因素如CBD、主干道、公交等对地价的影响程度和范围发生变化。③ 随着时间推移,城市居民逐渐注重生活质量、居住品位的提高,公园绿地对地价的影响程度超过其他公用设施。

关键词: 地理加权回归模型, 住宅地价, 空间分异, 空间演变, 南京

Abstract: This thesis, taking the downtown of Nanjing as an example, constructs a GWR model of the residential land price in urban areas based on spatial autocorrelation analysis and Monte Carlo Significance Test. After comparing the spatial variation of residential land prices in 2003 and 2009, this thesis probes into different factors in the spatial and temporal variations of residential land price, so as to reveal the relation between the space of residential land price and its influencing factors and to promote the scientific management of land price. The results indicate that: 1) a continuous increase of the influencing factors, as well as their reasonable distribution can narrow regional differences, and weaken their impacts on the land price; 2) due to the constant improvement of traffic facilities, the influencing factors, such as CBD, arterial roads, bus lines, witness variations in the degree and range of impacts on the land price; 3) as the city residents are paying attention to the improvement of living quality and taste over time, the impact of park and green space on land price exceeds that of any other public facilities.

Key words: GWR Model, residential land price, spatial variation, spatial evolution, Nanjing City