基于社会感知空间大数据的城市功能区识别方法探析

A STUDY OF URBAN FUNCTIONAL AREA IDENTIFICATION METHODS BASED ON BIG DATA OF SOCIAL SENSING

随着大数据时代的来临,位置服务的迅速发展使城市各类空间大数据不断涌现。海量数据的深入挖掘分析是智慧城市建设的基础,同时也为城市功能区的自动识别带来新的途径。在社会感知理论视角下,利用空间大数据识别城市功能区,亦成为定量理解城市空间结构的新观测手段。目前,国内外已经有利用分时定位数据、兴趣点等开展城市功能区识别的探索,然而相关研究在数据使用、技术方法与准确度上仍然存在一定的提升空间。本文对目前国内外城市功能区识别方法的研究进展进行了系统梳理,并以上海市中心城区为例,提出了利用社会感知空间大数据来构建城市功能区识别方法的新途径。

With the arrival of the age of big data, Geospatial Big Data （GBD） is springing up constantly due to the rapid development of Location Based Services （LBS）. As the foundation of smart city construction, analysis of massive data also brings new approaches to the identification of urban functional area. From the perspective of social sensing theory, the identification of urban functional area with GBD becomes a new measuring method of the quantitative understanding of the urban spatial structure. Currently, there have been some new explorations of the identification of urban functional area with locating data and Point of Interest （POI） at home and abroad, however, there is still room for improvement concerning the data, method and accuracy of related researches. Therefore, a new preliminary method of urban functional area identification is proposed based on the spatial big data of social sensing by the case of Shanghai.