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扬州市住宅价格的空间分异与模式演变
引用本文:王洋,方创琳,盛长元.扬州市住宅价格的空间分异与模式演变[J].地理学报,2013,68(8):1082-1096.
作者姓名:王洋  方创琳  盛长元
作者单位:1. 广州地理研究所, 广州 510070;2. 中国科学院地理科学与资源研究所, 北京 100101;3. 扬州市城市规划编制研究中心, 扬州 225002
基金项目:国家社科基金重大项目(13&ZD027);国家“十二五”科技支撑计划项目(2012BAJ22B03-04)~~
摘    要:以2001-2012 年扬州中心城区各居住小区的住宅平均单价为基本数据,通过建立住宅价格总体分异测度指数(GDI) 计算其总体分异趋势及各住宅类型内部的分异趋势;采用核密度函数等方法探索住宅价格的分布形态和分异格局的演变规律;利用趋势面分析不同住宅类型价格的空间分异趋势;基于上述结果总结空间分异的演变模式,并分别探索空间分异与格局演变的驱动力。结果表明:① 2001 年以来扬州市住宅价格差距显著增大,分异趋势在波动中增强,与城市住宅均价的年增长率耦合;住宅价格呈现西高东低的空间分异格局,同档次价格小区由空间集聚转为相对分散,高、低价格住宅区分别沿固定扇面由中心向外围扩散。②不同住宅类型内的价格分异走势差别显著,各类型住宅间的价格趋势面差距明显,但其空间形态类似。③ 空间分异模式由2001 年西高东低的扇形同档次价格集聚式分异转变为2012 年扇形与圈层相结合的多档次价格混合式分异。④ 2001 年以来住宅价格总体分异的核心驱动力是城市居住空间的迅速扩展、居民收入差距的增大、房地产市场的繁荣和住宅类型的多元化,其住宅价格空间格局演变的驱动力为城市发展方向的确立与变化、特定住宅类型建设的区位指向和古城保护、旧城改造与新区建设。

关 键 词:住宅价格  空间分异  模式  扬州  GDI指数  驱动力  核密度函数  
收稿时间:2012-11-26
修稿时间:2013-04-27

Spatial differentiation and model evolution of housing prices in Yangzhou
WANG Yang;FANG Chuanglin;SHENG Changyuan.Spatial differentiation and model evolution of housing prices in Yangzhou[J].Acta Geographica Sinica,2013,68(8):1082-1096.
Authors:WANG Yang;FANG Chuanglin;SHENG Changyuan
Institution:1. Guangzhou Institute of Geography, Guangzhou 510070, China;2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;3. Yangzhou Urban Planning and Research Center, Yangzhou 225002, Jiangsu, China
Abstract:Urban housing price differentiation is an important issue in urban geography. However, relatively little analysis is available on continual time for all types, and all space. In China's high housing price times, housing price has become the core issue which was paid close attention by the government and inhabitants. The focus of this research is to examine global differentiation, spatial differentiation, model evolution and dynamics of housing prices in Yangzhou. Housing prices data for housing estates in the period 2001-2012 were used. Global differentiation index (GDI) was established to measure the trend of global and within-group differentiations on housing prices in Yangzhou. Then based on kernel density estimation (KDE), the evolvement rule of distribution shape and differentiation pattern of housing price is examined. After that, the trend of spatial differentiation of 6 types housing prices was captured by trend analysis. Finally, the model and dynamics of spatial differentiation and pattern were summarized according to the above results. The results show that: (1) there have been increasing gaps among housing estates since 2001. In this period, the trend of differentiation has showed an upward fluctuation, which is coupled with the annual growth rate of housing price. Moreover, there exists a sector pattern of western-eastern differentiation. The spatial distribution of housing estates of homogeneity price turned cluster in 2001 into dispersion in 2012. Meanwhile, high price and low price housing estates are expanded along particular directions from core to periphery; (2) the fluctuations of prices on 6 types housing are obviously different. And their price levels are unequal, but their shapes of trend are similar; (3) the spatial model that is sector of western-eastern differentiation with cluster on housing estates of homogeneity price in 2001 has been turned into sector and concentric circles integrated on housing estates of heterogeneity price in 2012; (4) the core dynamics of global differentiation on housing price exert great influence on rapidly expansion of urban residential land, widening of residents' income gap, boom of real estate market, and diversification of housing types. The main dynamics of the enrollment of spatial pattern on housing price are as follows: the formulation and change of direction for urban development, locational direction on dwelling construction of particular housing types, ancient city protection, urban redevelopment and new urban district construction.
Keywords:spatial differentiation  kernel density estimation (KDE)  model  dynamics  global differentiation index (GDI)  housing prices  Yangzhou  
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