基于MGWR模型的城市住宅用地地价驱动因素分析  

Analysis of Driving Factors of Urban Residential Land Price Based on MGWR Model

作　　者：刘亚静 李胜男 LIU Ya-jing;LI Sheng-nan(College of Mining Engineering,North China University of Science and Technology,Tangshan Hebei 063210,China)

机构地区：[1]华北理工大学矿业工程学院,河北唐山063210

出　　处：《华北理工大学学报（自然科学版）》2022年第3期53-62,共10页Journal of North China University of Science and Technology：Natural Science Edition

基　　金：河北省自然科学基金项目(D2019209598)。

摘　　要：以2010~2019年唐山市土地出让成交均价为基础数据,采用空间自相关分析、全局趋势分析与克里金插值法,探索唐山市住宅用地地价的空间关联特征以及空间分布格局,并运用多尺度地理加权回归模型分析测算唐山市住宅用地地价的驱动因素,进一步探讨区域内城市地价空间分异的机制。结果表明:唐山市住宅用地地价呈东低西高、南低北高的趋势,是明显的“倒U型”结构,且具有显著的空间聚集特征;唐山市住宅地价以“丰南区-滦州市”为轴,表现为西北高东南低的特征;住宅用地地价主要受人口密度、人均GDP、道路通达度、交通通达度和重点中学的影响显著,且存在显著的空间差异性。Based on the average transaction price of land transfer in Tangshan from 2010 to 2019,the spatial correlation characteristics and spatial distribution pattern of residential land price in Tangshan had been explored by using spatial autocorrelation analysis,global trend analysis and Kriging interpolation method.The driving factors of residential land price in Tangshan had been analyzed and calculated by using multi-scale geographically weighted regression model.The mechanism of spatial differentiation of urban land price in the region was further investigated.The results show that the residential land price in Tangshan City tends to be low in the east and high in the west,low in the south and high in the north,which is an obvious"inverted U"structure with significant spatial aggregation characteristics.Taking“Fengnan District and Luanzhou City”"as the axis,the residential land price of Tangshan City shows the characteristics of high in the northwest and low in the southeast.The residential land price is mainly affected by population density,per capita GDP,road accessibility,traffic accessibility and key middle schools,and there are significant spatial differences.

关 键 词：城市地价 克里金插值 多尺度地理加权回归模型 空间分异 

分 类 号：TU984[建筑科学—城市规划与设计]