大数据下面向房地产便利性的综合指数模型  

A comprehensive index model of real estate convenience in big data era

作　　者：孙华涛[1] 尹章才[1] 陈雪菲[1] 刘清全[2] 

机构地区：[1]武汉理工大学资源与环境工程学院,武汉430070 [2]武汉大学中国南极测绘研究中心,武汉430070

出　　处：《测绘科学》2017年第2期100-104,109,共6页Science of Surveying and Mapping

基　　金：国家自然科学基金项目(41071283;41171319);公益性行业科研专项(201412014)

摘　　要：针对房地产便利性描述信息缺少量化和难以比较的问题,该文提出了一种利用大数据测度房地产便利性的综合指数模型。房地产便利性的描述信息往往是定性描述的、单一或单方面的,缺乏综合或整体的定量化评价,从而给不同房地产之间在便利性方面的横向比较造成了困难。该文在引入步行指数概念基础上,通过对便利设施的分类、分级以及便利设施与房地产之间步行距离的定量计算,获得综合衡量房地产便利性的一种实数型指数。基于百度在线地图的实验结果表明:所提模型可以自动测度任一房地产的便利性指数。There is no quantification for descriptions of real estate conveniences, and it is difficult to compare the conveniences between different real estates. To solve these problems, a comprehensive index model measuring the real estate conveniences using big data was proposed in this article. In general, the descriptions of real estate conveniences are qualitative and simplex, lacking of comprehensive quantitative evaluation, which causes difficulties to conveniences comparison of different real estates. Walk score was introduced in this paper through classification of ancillary facilities and quantitative calculation of walking distance between real estate and ancillary facilities, then a real type index measuring real estate conveniences synthetically was found. Results of experiment based on Baidu online map showed that the proposed model could measure the convenience index of any real estate automatically.

关 键 词：房地产 便利设施 步行指数 大数据 

分 类 号：P208[天文地球—地图制图学与地理信息工程]