【作者】 罗罡辉；

【导师】 吴次芳；

【作者基本信息】 浙江大学 ， 土地资源管理， 2007， 博士

【摘要】 地价是反映土地市场和土地供需状况的“晴雨表”，也是政府宏观调控的主要工具。科学地研究地价及其空间结构，为显化城市土地资产，制定和实施土地供应计划、调控土地供应结构提供科学参考，也是土地市场交易、房地产开发、建设项目投资决策和房地产税制改革的重要依据。过去关于地价的研究主要视地价的空间结构变化为静态，多以特征价格方程等方法全域刻画地价空间变化，将误差项假设为独立与相等的分配，这样所得到。的地价空间结构信息非常单一的和缺乏实用性，忽略了地价在局域变化的跳跃性与个别性。在基准地价等研究中，往往人为地分区域来划同质区域，决定影响因素的选取，超出同质区域视为没有影响，这种缺乏足够依据的划分相当程度地影响了土地价值的表达。以往的地价研究，大多数局限于数据调查与数据计算，很少通过图示清楚地解释地价空间结构形成的原因，各种因素在不同空间上对地价的作用机理解释也是很少涉及，人们并不很清楚周边地价之间的相互关系，规划者也很少探及规划变更对直接相关地区的土地价值的影响。地价的研究急需要技术创新，才能更为有效地支持城市的和谐发展，为政府调控提供有效和科学的决策依据。本文主要应用了目前理论与应用较为先进的地理加权回归(Geographicall Weighted Regression，缩写GWR)模型来尝试处理地价相关的技术问题。以杭州市老城区住宅地价为例进行了实证，样本为杭州市1998-2005年的土地“招、拍、挂”数据，并辅之于各种调查、统计资料，是较为完整的杭州市“公开市场”地价空间结构的研究。本研究首先强调了研究数据的预处理，按照地理学和统计学的原理对数据进行了完备性处理、特异点处理、标准化处理；特别是标准化处理，以“变程”进行了缓冲区分析，缩小了实际的研究范围，提高了研究的精度，同时为样点选择影响因素的影响范围提供了支持。在数据预处理时，同时应用了数据空间探索性分析技术，对地价样点间的空间相关性进行了分析，结果显示地价空间结构不是单一趋势分布的，不同的空间区域具有不同的相关关系。为进一步证实了地价空间的非平稳性的存在，把地理统计学、GIS工具融入地价空间结构描述的模型中去，易于直观显示地价空间结构的形态。地价空间不稳定性的存在，必须引入专门的空间分析方法，本文通过不同模型、方法的比较，在理论上深入探讨了GWR模型的机理以及在地价研究中的可行性和意义。在住宅地价GWR模型案例实证部分，详细阐述了因素的选择和量化，通过最优带宽计算、回归系数计算、方差分析、事件智能诊断、Monto Carlo显著性检验等，比较分析了GWR的固定型和调整型两种空间核模型的差异，选择后者作为住宅地价空间结构解释的模型。住宅地价空间结构的解释分10个因素展开详细论述的，分别是：CBD、西湖、钱塘江、城市快速道路系统、小学、大专院校、医院、主要生活品市场、土地面积、容积率。在解释分析过程中，使用了详细的地价空间结构影响图，比以往的研究更加注重直观性和真实性。为了对比，本研究使用相同的数据，应用特征价格模型进行了计算，结果显示GWR模型更具有技术先进性。为了进一步体现本研究成果的实用性和社会价值，分个案估价面积修正和基准地价的宗地面积修正为例分别进行了应用性研究，前者的研究使土地估价的影响因素修正更为全面；后者的研究解决了长期以来宗地面积修正方面的技术困难，为政府决策提供了一种有效的方法。更多还原

【Abstract】 Land price is a "weatherglass" of the land market and conditions of supply anddemand, and also is governments’ main instrument for macro-economic regulation.Studies on land price and its spatial structure could provide a reference to visualizethe property of urban land, formulate and implement land supply plans, and toregulate the supply structure of land. It is also an important basis for land market trade,real estate development, decision-making of construct projects and reform in realestate tax system.The former researches on land price, usually treating spatial structure change as astatic one, often use Hedonic Model to depict the spatial variety of the whole studyarea. This research method hypothesized that the error items were dividedindependently and equally. Spatial information got from this way was often infrequentand unpractical, as it neglected the local jump and individual variety of land price.Among researches on base land price, homogeneous areas were divided subjectivelyby dividing regions. Also, influence factors were selected subjectively and theinfluence was deemed to zero when it out of the homogeneous areas. This dividingaffected the express of land value badly. The existing literatures on land price inChina, almost limited to data survey and data compute, scarcely using maps to interpret why this spatial structure of land price was formed. It seems that peopledidn’t know the relationships between the prices of land sites seated aside very well.In a same way, planners scarcely realized the effect of the plan on land price. Underthis condition, researches on land price need technical innovation to advanceharmonious development of cities and help governments to make decisions.Geographical Weighted Regression (GWR) model was adopted in thisdissertation to deal with technical problems related with land price. By taking housingprices in Hangzhou as an example, this dissertation used open land market data(including calling for bids, auction and listed on board, between 1998 and 2005) andother data collected from investigate and statistics. The data was quite complete andclose to market reality.This dissertation emphasized the importance of the data pretreatments at first.Treatments such as complete disposal, outlier exclusion and standardization weredone according tO Geography theory and Statistics theory. Especially during theprocess of standalization, a buffer analysis using "range" was done to make the studyarea smaller and improve the precision of the research, and it helped to selectinfluence factors in a certain distance range in the meantime. Exploratory spatial dataanalysis (ESDA) was adopted to do spatial autocorrelation analysis. The resultsshowed that the structure was not single-trend distributed, but have different spatialautocorrelation relationship at different location.In order to confirm spatial non-stationarity of land price spatial structure,Geostatistics tools and GIS tools were introduced to display the spatial structure easily.The existence of spatial non-stationarity of land price need specialized spatial analysismethod. By comparing with other models, this dissertation explored the mechanism ofGWR model and proved its feasibility and value in land price research.In applying GWR model to housing land price, the research depicted factorschoosing and their quantization in detail. It compared the difference between fixedspatial kernels model and adaptive spatial kernels model, after taking the followingsteps: computing optimal bandwidth and regression coefficients, doing ANOVA,casewise diagnostics, Monto Carlo significance test and so on. Adaptive spatial kernels model was selected. Ten influence factors were selected in interpreting thespatial structure of housing land price. These ten variables were: CBD, West Lake,Qiantang River, quick transportation system, elementary school, colleges, hospitals,main household goods markets, land area and FAR. A detail spatial structure map onland price was used to make the analysis more intuitionistic and real. Hedonic modelwas used with the same data in order to do comparison. The results showed that theGWR model was more advanced in technique.At the end of the dissertation, the results of the GWR model were applied in caseland valuation and the amendment of base land price to show its practicability andgreat social value. The former made the revise of land valuation factors morecompletely. The latter solved the technique problems existed in area amendment ofparcel land for long time and provided an effective and credible method forgovernments’ decision-making.更多还原