基于网络大数据的城市二手房空间分布格局研究  

Research on Spatial Distribution Patterns of Urban Second-Hand Housing Based on Big Network Data

作　　者：卢方涛 张晓瑞[1,2] 张奇智 刘洋[1] Lu Fangtao;Zhang Xiaorui;Zhang Qizhi;Liu Yang(School of Urban Planning,Hefei University of Technology,Hefei Anhui 230601,China;Laboratory of Digital Human Habitual Studies,Hefei University of Technology,Hefei Anhui 230601,China)

机构地区：[1]合肥工业大学城市规划系,安徽合月巴230601 [2]合肥工业大学数字人居环境研究实验室,安徽合肥230601

出　　处：《城市建筑》2020年第11期7-10,共4页Urbanism and Architecture

基　　金：合肥市市长重点研究项目(JS2017HKRK0199)。

摘　　要：城市二手房的空间分布研究对于城市居住空间的优化布局和住宅产业发展具有重要意义。文章以网络大数据为基础,综合应用空间分析技术探讨了二手房的总体空间分布格局和价格、建筑年代的空间分布特点,构建了城市二手房空间分布研究的新思路。合肥市二手房的案例研究显示:合肥市总体上形成"中心集聚,外围分散"的二手房空间分布格局;价格具有显著的空间正相关性;价格等级和建筑年代等级均呈现出单中心或多中心的空间分布状态。研究表明,网络开源大数据具有数据量大、获取迅速的特点,其可为城市二手房空间分布研究提供更加精确高效的工具与方法。The research on the spatial distribution of urban second-hand housing is of great significance to the optimal layout of urban residential space and the development of residential industry. Based on the large data of the network, the spatial distribution characteristics, price and building times of the second-hand house are discussed with the spatial analysis technology, and a new idea for the study of the spatial distribution of the second-hand house in the city is constructed. The case study of the second-hand houses in Hefei shows that the spatial distribution pattern of "central agglomeration and peripheral dispersion" has been formed on the whole;the price have significant positive spatial correlation;the price grade and building time grade all present single-center or multi-center spatial distribution state. At the same time, it puts forward some suggestions for planning and design. The research shows that the network open source large data has the characteristics of large amount of data and fast acquisition, which will provide more accurate and efficient tools and methods for the study of the spatial distribution of urban second-hand housing.

关 键 词：大数据 二手房 空间分布 合肥市 

分 类 号：TU984[建筑科学—城市规划与设计]