武汉市商品住宅价格时空演变及影响因素研究

发布时间：2017-12-31 12:09

本文关键词：武汉市商品住宅价格时空演变及影响因素研究　出处：《中南民族大学》2013年硕士论文　论文类型：学位论文

【摘要】：城市商品住宅市场作为区域性市场，很大程度上，与区位密切相关。由于城市发展时间和空间的不平衡性，使不同时期城市商品住宅价格在空间分布上存在差异。城市商品住宅价格研究的难点在于住宅的时间特性与空间特性交错在一起。本文以城市住宅价格研究的基础理论为指导，以武汉市商品住宅价格为研究对象，重点研究了基于灰色理论、GIS系统的武汉市商品住宅价格的时间变化特征、空间分布规律及其影响因素，丰富发展了城市商品住宅价格时空变化规律研究，探讨了不同时期武汉市商品住宅价格在空间分布上的演变规律，同时揭示了武汉市商品住宅价格时序变化的主要因素与次要因素。首先，基于2002年—2011年武汉市商品住宅平均销售价格，运用灰色系统理论，建立GM（1,1）灰色预测模型，从时间上探讨武汉市商品住宅价格变动趋势。研究表明，GM（1,1）预测模型关于住宅价格的预测精确度为一级，体现了GM（1,1）预测模型的优越性，并用此模型预测了2012年、2013年的商品住宅平均销售价格，反映出商品住房价格随时间不断上升的趋势；此外，以2002年—2011年武汉市商品住宅平均销售价格、人均国内生产总值、城镇居民人均可支配收入、居民消费价格指数、城镇人口、房地产开发投资额、商品住宅竣工面积、住宅销售面积等十年的数据为统计对象，通过灰色关联度模型，进行影响因素与商品住宅价格关联度大小比较。研究得出：城镇居民人均可支配收入是最主要因素，人均国内生产总值位于第二。其次，本文创新性地把地理信息技术（GIS）系统运用到武汉市商品住宅价格空间研究中，收集了武汉市七个中心城区、两大经济技术开发区以及东西湖区2006年、2008年、2010年、2011年商品住宅样点的住宅成交均价信息，利用GIS信息技术，对武汉市2006—2011年的住房位置进行地理定位，将研究范围地图网格化，并绘制价格等值线图，继而进行各种空间分析。结果表明，武汉市商品住宅价格分布呈现圈层式结构，整体房价呈现不断上升趋势，，不管是内环核心区、二环中央活动区还是三环外的远城区。住宅价格变化自城中心向外围由高向低逐渐递减，二环至内环等值线比较密集，离城中心较远地区等值线较为稀疏。研究还表明，道路轨道交通、城市商圈、临江临水等条件对商品住宅价格的空间分布影响很大，解放大道、徐东大街等周边，江汉路商圈、中南商圈等商业中心周围，以及临近长江、东湖等水域都是住宅价格高值区。
[Abstract]:As a regional market, urban commodity housing market is closely related to location to a great extent, because of the imbalance of urban development time and space. The difficulty of the study on the price of urban commercial housing lies in the staggered time and space characteristics of the housing. This paper is based on the study of the price of urban housing. Basic theory for guidance. Taking the commodity housing price in Wuhan as the research object, this paper focuses on the temporal change characteristics, spatial distribution law and influencing factors of the commodity housing price in Wuhan based on the grey theory and GIS system. Rich development of the urban commodity housing price temporal and spatial changes in the study of different periods of Wuhan City commodity housing prices in the spatial distribution of the evolution of the law. At the same time, it reveals the main factors and secondary factors of the time series change of the commodity housing price in Wuhan. First of all, based on the average sales price of commercial housing in Wuhan from 2002 to 2011, using the grey system theory, a grey prediction model is established. This paper probes into the changing trend of commodity housing price in Wuhan City in time. The research shows that the accuracy of the forecast model of housing price in Wuhan is first class, which reflects the GM(1. 1) the superiority of the forecasting model, and using this model to predict the average selling price of commercial housing in 2012 and 2013, which reflects the rising trend of commodity housing price with time; In addition, from 2002 to 2011, the average sales price, per capita GDP, per capita disposable income of urban residents, consumer price index, urban population. Investment in real estate development, commercial housing completed area, residential sales area and other data for 10 years as statistical objects, through the grey correlation model. The study shows that the per capita disposable income of urban residents is the most important factor, and the per capita GDP is the second. Secondly, this paper innovatively applies the geographical information technology (GIS) system to the study of the commodity housing price space in Wuhan, and collects the seven central urban areas of Wuhan. Two major economic and technological development zones as well as the East and West Lake District on 2006, 2008, 2010, 2010 commercial residential samples of residential transaction average price information, using GIS information technology. The location of housing in Wuhan City from 2006 to 2011 was geo-located, the research range map was gridding, and the price isoline map was drawn, and then various spatial analysis was carried out. The results show that. The distribution of commodity housing price in Wuhan presents the structure of ring layer, and the whole house price presents a rising trend, whether it is the core area of the inner ring. The central activity area of the second ring ring is still the far urban area outside the third ring. The change of housing price gradually decreases from the center of the city to the periphery from the high to the low, and the contour line from the second ring to the inner ring is relatively dense. The study also shows that the conditions such as road rail transit, urban commercial area, riverside water and other conditions have a great impact on the spatial distribution of commodity housing prices, Liberation Avenue. The surrounding areas of Xudong Street, Jianghan Road, Central South and other commercial centers, as well as the waters near the Yangtze River and East Lake are all high value residential areas.
【学位授予单位】：中南民族大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F299.27;F224.32

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