地理科学进展 ›› 2014, Vol. 33 ›› Issue (10): 1322-1331.doi: 10.11820/dlkxjz.2014.10.004

• • 上一篇    下一篇

基于住宅价格的北京城市空间结构研究

王芳1,2(), 高晓路1(), 颜秉秋1,2   

  1. 1. 中国科学院区域可持续发展分析与模拟重点实验室,中国科学院地理科学与资源研究所,北京 100101
    2. 中国科学院大学, 北京 100049
  • 出版日期:2014-10-25 发布日期:2014-10-25
  • 作者简介:

    作者简介:王芳(1987-),女,内蒙古呼和浩特人,博士研究生,主要从事城市地理与城市环境评价研究,E-mail:wangf741@163.com

  • 基金资助:
    国家自然科学基金项目(41171138);中国科学院重点部署项目(KZZD-EW-06)

Research on urban spatial structure in Beijing based on housing prices

Fang WANG1,2(), Xiaolu GAO1(), Bingqiu YAN1,2   

  1. 1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Online:2014-10-25 Published:2014-10-25

摘要:

城市空间结构是城市地理研究的核心重点之一。近年来,城市住宅价格快速增长,一方面导致城市空间结构出现了一些新的特征和问题,另一方面住宅价格也可敏锐地反映出城市空间结构的演变。因此,本文从住宅价格的角度对北京市城市空间结构进行了探讨。利用北京市2005年和2012年二手房市场住宅的空间数据,通过GIS空间分析、空间自相关分析和Hedonic回归分析等方法,对住宅价格时空格局及影响因素进行了分析,并在此基础上从住宅价格的角度探讨了城市空间结构的优化调整问题。北京市住宅价格存在蔓延式增长、空间差异明显及空间自相关性高等特点,其主要的影响因素包括区位条件、交通便利度、周围环境、基础设施、物业等级等。基于住宅价格得出北京市空间结构的主要特征为:①已形成了多中心的城市空间结构格局。除市中心外,还有亚奥地区、万柳—香山地区、中关村地区、复兴门地区、CBD等次中心,空间扩张仍呈现“摊大饼”的发展模式;②社会空间分异现象有所缓解,但仍存在明显的居住隔离。金融街、月坛等街道是房价高值集聚区,易形成“富人区”,而南六环尤其是房山则易形成“穷人区”;③交通条件和周围硬件环境等基础设施对城市空间结构有一定的调整作用,但调整的效果并不理想。

关键词: 住宅价格, 城市空间结构, 特征价格, 北京

Abstract:

The development of housing market in Beijing has brought phenomenal changes to urban structures, and in recent years, soaring housing price has become a serious public concern. This paper explores the spatiotemporal evolution of housing prices using the spatial data of residential blocks in 2005 and 2012 in order to reveal its influencing factors, especially factors affecting the spatial structure of housing prices. Based on the analysis, this paper discusses the characteristics of such spatial structure and put forward some suggestions for urban planning and construction from the viewpoint of housing prices, which is a new perspective of urban spatial structure studies. The result of the analysis shows that housing prices increased overall, and particularly, the prices of subsidized housings for lower income population and regular housing increased much faster compared to higher-end housing. Spatial autocorrelation effect associated with housing price has become significantly stronger in 2012, especially in the central part of Beijing. The influencing factors of housing prices were analyzed using a multivariate linear regression model-the hedonic pricing model. In addition to the location factor, high property maintenance standard, good environment, well-developed transportation infrastructure, high-quality educational resources, and high availability of other public service facilities around the residential blocks can significantly increase housing prices. Multiple centers of high price housing have started to emerge in the past decade, such as the CBD, Zhongguancun, and Ya'ao districts. The Financial Street and Yuetan areas are the high value centers of housing prices. The areas around the south Sixth Ring Road, especially the Fangshan District, are the concentrated areas of lower price housing. This may eventually lead to social segregation of urban residents. Effective policies should be made to avoid this problem. In addition, the city should strengthen traffic infrastructure development and enhance the coordination of different facilities to influence the spatial pattern of housing prices and promote equal provision of urban social resources fundamentally.

Key words: housing price, urban spatial structure, hedonic model, Beijing

中图分类号: 

  • F127