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城镇住宅用地基准地价的地质灾害影响及修正系数研究 ——以兰州市为例
引用本文:彭建超,吴群,钱畅.城镇住宅用地基准地价的地质灾害影响及修正系数研究 ——以兰州市为例[J].中国土地科学,2016,30(9):73-81.
作者姓名:彭建超  吴群  钱畅
作者单位:南京农业大学 公共管理学院,南京农业大学土地管理学院,南京市国土资源信息中心
基金项目:国家自然科学基金(重点)项目“我国土地资源效率提升能力与建设研究——基于转变经济发展方式的视角”(71233004);国家自然科学基金青年项目“新型城镇化进程中农村土地利用与居民地域认知相关性研究”(71403129);教育部人文社会科学研究青年基金项目“发达地区农村土地综合整治对地域性认同的影响研究”(13YJC630117)。
摘    要:研究目的:研究地质灾害对城镇住宅地价的影响及城镇住宅基准地价的地质灾害因素修正系数编制。研究方法:探索性空间数据分析、网格地价模型和地理加权回归模型。研究结果:基于兰州市1621个住宅地价调查样点数据的分析显示,地质灾害隐患可导致土地价值的降低,但作用程度在不同土地级别、不同空间位置存在差异,地质灾害对地价产生负作用的极值易出现在各类洪道、沟坡地带;运用兰州市公开出让住宅用地数据进行验算,将网格地价模型和GWR模型法得出的修正系数应用于兰州市基准地价修正法评估,验算结果基本符合兰州市地价实际情况,网格地价模型的验算结果较GWR模型更为平稳。研究结论:地质灾害因素修正系数的空间量化,有助于提高地价评估的准确和客观性;网格地价模型法较GWR模型法更适合当前基准地价修正系数编制。

关 键 词:土地经济  基准地价  地质灾害  修正系数  地理加权回归模型  网格地价模型
收稿时间:2016/5/6 0:00:00
修稿时间:2016/10/18 0:00:00

Influence of Geological Hazard on the Benchmark Land Price of Urban Residential Land and Its Correction Coefficient Appraisal: A Case Study in Lanzhou City
Abstract:The purpose of this paper is to study the influence of geological hazards on the urban residential land price and the computation of the correction coefficient of geological hazard factors of the urban residential benchmark land price. Research methods include exploratory spatial data analysis(ESDA), grid land price model and geographically weighted regression model(GWR). Results indicate that based on the analysis of land price of 1621 residential plots surveyed in Lanzhou, the geological hazard risk can lead to land value decrease, but such effect varies in different land grades and different spatial locations. The negative effect of geological hazards on land price is easy to be found extremely in all kinds of spillway and gully slope zone. 51 cases of public sale of residential land data of Lanzhou from 2011 to 2014 are used for model verification. Applying the correction coefficient produced by the grid land price model and GWR model respectively in the land price appraisal method of benchmark land price correction in Lanzhou, the verification results are generally in accordance with the actual land price of Lanzhou. Grid land price model shows much more stable performance than GWR. The study is concluded that the spatial quantization of the geological hazards correction coefficient contributes to improving the accuracy, objectivity, convenience and safety of land price evaluation, and compared with the GWR Model, grid land price model is more suitable for calculating the correction coefficients of benchmark land price system at present.
Keywords:land economy  benchmark land price  geological hazards  correction coefficient  GWR  grid land price model
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