西部中小城市住宅地价空间分异规律及影响因素研究——以天水市为例  

Spatial variation and influencing factors of residential land prices of medium and small-sized cities in western China——Taking Tianshui city as an example

作　　者：吕志芳[1] 陈英[1] 

机构地区：[1]甘肃农业大学资源与环境学院,甘肃兰州730070

出　　处：《甘肃农业大学学报》2017年第5期112-120,共9页Journal of Gansu Agricultural University

基　　金：国家自然科学基金项目"村民关联度与农地利用的关系研究-以甘肃河西走廊为例"(71263003);国家自然科学基金项目"农民土地价值观:测度;变迁与影响"(71563001)

摘　　要：【目的】对西部中小城市住宅地价的空间分异规律和影响因素进行研究,为城市土地的科学管理提供依据.【方法】以天水市秦州区为例,采用地统计分析法探究住宅地价空间分异规律,构建GWR模型分析住宅地价影响因素.【结果】天水市秦州区住宅地价的空间分异模式属于从中心向外围逐渐降低的单核空间结构,局部区域出现跳跃现象.各影响因素的影响程度排序为:容积率>与主干道距离>与医院距离>与绿地距离>与公交站点距离>距生活设施的距离>距学校距离.从GWR模型回归结果来看,主干道、学校、医院及容积率对住宅地价贡献度的区位差异较大.【结论】GIS工具将GWR模型回归结果可视化,清晰显示住宅地价影响因素空间差异性,侧面反映了研究区的区域规划控制力度、交通状况、医疗状况、环境状况等,为政府的土地规划、城市基础建设投资和房地产开发提供决策依据.【Objective】To explore spatial variation and influencing factors of residential land prices in medium and small-sized city.【Method】Taking Qinzhou district of Tianshui city as an example,by applying geostatistical analysis and building GWR model.【Result】1）Spatial distribution of residential land prices in Qinzhou show a single central structure in general and show diminishing circle outward style in the core of the center.2）In the geographically weighted regression（GWR）model,the order of the average marginal contribution on the land premium from high to low is volume rate,the distance from the main road,hospitals,urban green space,bus stations,living facilities,schools.3）The main road,schools,hospitals,volume rate have significantly geographical differences contribution to residential land prices.【Conclusion】GIS tools make GWR regression results visualized,clearly indicating the residential land price factors spatialdifferences,by which we can understand area planning efforts to control,traffic conditions,medical conditions,environmental conditions,etc.which can be provide decision-making basis for the government＇s land planning,urban infrastructure investment and real estate development.

关 键 词：住宅地价 GWR模型 GIS 空间分异 天水市 

分 类 号：F301.2[经济管理—产业经济]