空间分析方法在房地产市场研究中的应用——以北京市为例

Application of spatial analysis to the research of real estate:taking Beijing as a case

基于北京市2003年普通住宅数据,利用空间分析中点模式分析、空间自相关分析和空间插值方法等,对北京市房地产,尤其是普通住宅的空间格局进行分析。研究表明,北京市房地产发展在空间上具有强烈的集聚特点,而房价的空间自相关特性也非常明显。空间分析方法提供了准确认识、评价和综合理解空间位置和空间相互作用的手段,为定量研究空间格局提供了支持。在房地产发展等社会经济现象研究中,空间分析方法强调了“位置”因素的重要性,是刻画房地产空间格局的理想工具。

In social and environmental sciences, researchers are interested in the analysis and modeling of the spatial data. Unlike ordinary data, the locations of the observation are also concerned as well as the values relating to the objects in spatial data analysis. Real estate has gone through a dramatic growth in China these years, and there were a lot of researches on the development of real estate. But most of the studies just considered the social and economic attributes of the real estate. The location of the real estate was not fully considered. With the development of the Geographical Information Sciences （GISc）, the theories and methods about spatial dada analysis developed too. And there are more tools and softwares focused on spatial analysis, which improved the application of the spatial data analysis. In this paper, the way of spatial data analysis, such as point pattern analysis, spatial correlation analysis and spatial interpolation were recommended and used in the study about the real estate in Beijing, the capital of China. By using the quadrat analysis, nearest neighbor analysis and Ripley＇s K function, the clumped pattern of the real estate in Beijing is found. The Moran＇s I, which is often used to test the spatial autocorrelation, also suggests that there is significant spatial autocorrelation in the price of the house in Beijing. This means that the research about the price of the house in Beijing must concern about this important characteristic. By use of ordinary kirging, the spatial pattern of the house price in Beijing was simulated, and the results also show that the price has some interesting relationship with the development of the city itself.