Spatial Pattern of Newly Built Housing's Price in Changchun City

Expand
  • 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, Jilin 130012, China;
    2. Graduate School of the Chinese Academy of Sciences, Beijing 100049, China

Received date: 2010-06-18

  Revised date: 2010-09-29

  Online published: 2011-01-20

Abstract

Changchun has experienced many changes in housing price compared with other provincial capital cities in China. This paper examined the spatial pattern of housing price and its driving factors in Changchun City by the aid of spatial interpolation method and GIS technology. The results showed that the general spatial pattern of housing price in Changchun shows a series of circle layers with two cores in the centre. One core is located near Changchun Zoological and Botanical Garden and the other is located near the South Lake Square. The second-level circle layer of housing price covers the central areas of the city, including the area near South Lake and parts of the Yitong River. The spatial change rates of housing price in different directions are much different. Housing price declines much faster in the northeast-southwest direction than that in the southeast-northwest direction. Two regional housing price centers are found in the western and southern parts of the city. Several factors influenced the spatial pattern of Changchun City, such as residential environment, urban development strategy, public transportation services, land use and the income level of the main consumers. According to the development strategy of Changchun, the southern, western and northeast parts of the city will experience a rapid development in the near future, which will make the real estate market flourish. Based on the research, several advices are given to optimize the spatial structure of real estate development in Changchun City. The southern area of the city has better infrastructure conditions, thus high level of ecological community is suggested. In the northeastern part, it is much suitable to develop large areas of ecological community by the side of the North Lake Wetland Park; in the western and northern area, a combination of low and middle level housing should be developed after the large areas of slum clearance.

Cite this article

LIU Ying, ZHANG Ping-Yu, LI Jing . Spatial Pattern of Newly Built Housing's Price in Changchun City[J]. SCIENTIA GEOGRAPHICA SINICA, 2011 , 31(1) : 95 -101 . DOI: 10.13249/j.cnki.sgs.2011.01.95

References

[1] Tomson O,Wang B T.A Hedonic Price Function for a Northern BC Community[J].Social Indicators Research,2003,61(3):285-296.
[2] Pearson L J,Tisdell C,Lisle A T.The impact of Noosa National Park on surrounding property values:An application of the Hedonic Price Method[J].Economic Analysis & Policy,2002,32(2):155-171.
[3] 邵飞波,张 鑫.基于Hedonic模型的上海住宅价格影响因素分析[J].经济论坛,2007, (23): 9~13.
[4] 王 德,黄万枢.外部环境对住宅价格影响的Hedonic法研究[J].住宅规划研究,2007,31(9):34~41.
[5] 陈永霞,陈民强.南京市住宅价格特征的分析——应用Hedonic模型[J].淮阴工学院学报,2009,18(4):55~60.
[6] 周 华,李同升.基于Hedonic模型的西安市住宅价格空间分异机制研究[J].西安文理学院学报,2007,10(2):68~71.
[7] 赵何军.基于Hedonic模型的天津住宅价格因素分析[J].现代经济,2008,7(12):15~16.
[8] Can A.GIS and spatial analysis of housing and mortgage markets[J].Journal of Housing Research,1998,9(1):61-86.
[9] Basu S,Thibodeau T.Analysis of spatial autocorrelation in house prices[J].Journal of Real Estate Finace and Economics,1998,17(1):61-85.
[10] Gillen K,Thibodeau T.Anisotropic autocorrelation in house prices[J].Journal of Real Estate Finace and Economics,2001,23(1):5-30.
[11] Chhetri P, Han J H, Corcoran J.Modelling spatial fragmentation of the brisbane housing market[J].Urban Policy and Research,2009,27(1):73-89.
[12] 马敏蕾,吕 斌,冯长春.基于GIS基础上的北京住住宅价格格空间格局研究[J].资源产业经济,2008, 21(12):26~28.
[13] 王 霞,朱道林.地统计学在都市房价空间分布规律研究中的应用——以北京市为例[J].中国软科学,2004,(8):152~155.
[14] 许晓晖.上海市商品住宅价格空间分布特征分析[J].经济地理,1997,17(1): 80~87.
[15] 周春山,罗 彦.近10年广州市房地产价格的空间分布及其影响[J].土地利用,2004,28(3):52~56.
[16] 周 敏,甄 峰.基于空间分析的城市商品住宅价格空间分布研究——以南京市2007年开盘在售商品住宅为例[J].现代城市研究,2008,23(7):47~53.
[17] 梅志雄.基于半变异函数的住宅价格空间异质性分析——以东莞市为例[J].华南师范大学学报,2008,(4):123~128.
[18] 王艳妮,谢金梅,郭 祥.ArcGIS中的地统计克里格插值法及其应用[J].软件导刊,2008,7(12):36~38.
[19] 郭旭东,傅伯杰,陈利顶,等.河北省遵化平原土壤养分的时空变异特征——变异函数与Kriging插值分析[J].地理学报,2000,55(5):555~556.
[20] 侯 帅.长春市城市密度与规划策略研究.长春:东北师范大学,2009.
Outlines

/