基于ArcGIS对南京市房价分析  

Analysis of the housing price in Nanjing based on ArcGIS

作　　者：周超 周亚男[1] ZHOU Chao;ZHOU Ya-nan(School of Eartli Sciences and Engineering,Hehai University,Nanjing 211100,China)

机构地区：[1]河海大学地球科学与工程学院,南京211100

出　　处：《黑龙江科学》2018年第18期10-13,共4页Heilongjiang Science

基　　金：国家自然科学基金项目(41501453);中央高校基本科研业务费项目(2016B11414)

摘　　要：自住房商品化制度确定后,房价一直是人们关注的热点。基于南京市房价数据,通过克里格插值法得到南京市房价分布图,研究南京市房价分布规律及差异,并挖掘影响南京市房价分布的关键因素。结果表明:南京市房价在空间分布上具有连续性,除局部地区呈现异质性;主城区房价远比郊区高得多,并且房价从峰值区向四周随距离增大而减少,其中房价峰值区向四周房价衰减梯度较大,郊区外围房价衰减梯度较小;房子与地铁站距离影响平均价格,而与优质中小学的距离是影响南京市高房价的关键因素。Since the establishment of the commercialization of housing system,housing price has been a hot topic.Basing on the housing price data in Nanjing,this paper obtains the distribution map of housing price through the method of Kriging Interpolation. This paper researches the pattern of housing price and differences,and focus on mining the key factors influencing the distribution of housing price. The results show that the housing price has continuity in spatial distribution,except for the regional heterogeneity in Nanjing; Housing price in the main districts of Nanjing are much higher than those in the suburbs,and the housing price decreases with the distance increasing. Among them,the attenuation gradient of the housing price in the peak area is large,while the attenuation gradient of the housing price outside the suburb is small; The distance between the house and the subway station and the primary and secondary schools will affect the housing price. However,the distance from the subway station affects the average price of houses,while the distance from high-quality primary and secondary schools is the key factor affecting the high housing price in Nanjing.

关 键 词：南京市 克里格插值 房价分析 规律及差异 因子 

分 类 号：F293.3[经济管理—国民经济]