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徐州市住宅地价空间分异及影响因素 被引量:3

Spatial differentiation and influencing factors of the residential land price in Xuzhou
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摘要 研究城市住宅地价空间分异及其成因对于城市政府科学制定房地产市场调控政策和促进土地资源优化配置具有重要意义.以徐州市主城区为例,采用克里金法和地理加权回归等方法,对徐州市住宅地价的空间分异及其影响因素进行研究.结果表明:徐州市住宅地价总体呈单中心空间结构和空间向心性;容积率是提升徐州住宅地价的主导因素,医疗资源、公园绿地和教育资源对徐州市住宅地价也有较大的提升作用,且对地价影响具有显著的空间差异性.在主城区范围内,合理布局各影响因素,能够促进土地资源的优化配置和城市土地整体价值的有效发挥,建议适度提高容积率、均衡布局基础设施、科学把握住宅用地供应规模和出让价格. Researching spatial differences of urban residence price and its formed reasons have significance to the city government scientifically formulate the real estate market regulation policies.Taking the main district of Xuzhou as an example,the spatial differentiation of residential land price and its influencing factors are studied by geographical weighted regression(GWR)model,Kriging method and others.The results indicate that the residential land price of Xuzhou city presents a single center spatial structure and a spatial centripetal property.The plot ratio is a dominant factor in increasing residential land prices in Xuzhou.Next,medical resources,park green space and education resources all have significant effects on raising residential land prices in Xuzhou,and them also have significant spatial differences in the impact on land prices.Within the urban area,the rational distribution of various influencing factors can promote the optimal allocation of land resources and the effective development of the overall value of urban land.It should improve the plot ratio moderately,balance the layout of infrastructure,scientifically grasp the supply scale and transfer price.
作者 邵洪琪 雍新琴 练婧雯 程光兰 张梦婕 Shao Hongqi;Yong Xinqin;Lian Jingwen;Cheng Guanglan;Zhang Mengjie(School of Geography,Geomatics&Planning,Jiangsu Normal University,Xuzhou 221116,Jiangsu,China)
出处 《江苏师范大学学报(自然科学版)》 CAS 2020年第1期23-28,共6页 Journal of Jiangsu Normal University:Natural Science Edition
基金 国家自然科学基金资助项目(41601087) 江苏省大学生实践创新训练计划项目(201810320175X) 江苏高校优势学科建设工程项目。
关键词 住宅地价 空间分异 克里金法 地理加权回归 徐州市 residential land price spatial differentiation Kriging method geographical weighted regression(GWR) Xuzhou
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