基于POI数据的城市功能区识别及主要交通枢纽空间分析  

Identifying Urban Functional Regions Based on POI Data and Spatial Analysis of Main Transit Hubs

作　　者：赵家瑶 李宏伟[1] 邓圣乾 姜晶莉 ZHAO Jiayao;LI Hongwei;DENG Shengqian;JIANG Jingli(Information Engineering University,Zhengzhou 450001,China)

机构地区：[1]信息工程大学

出　　处：《测绘与空间地理信息》2019年第12期38-42,共5页Geomatics & Spatial Information Technology

基　　金：国家自然科学基金项目——空间数据流的概念漂移问题研究项目(41571394)资助

摘　　要：研究利用机器学习中的TF-IDF统计方法,基于POI数据识别北京五环范围内的城市用地功能区。实验从道路网和格网两个层面开展,首先,将两结果与相同地区的遥感影像进行对比与验证,并从中提取属于交通用地范畴中的主要交通枢纽;其次,基于空间服务范围和空间连接强度两个视角对火车站和机场的地理特征进行分析,具体包括空间分布范围的特点、受区域影响的强弱、空间联系强度的差异等内容;最后,进一步对比各重要交通枢纽所在空间单元作为出租车行程起始点和终止点的共性和差异性。This paper uses the statistical method named TF-IDF in machine learning to identify the urban functional regions based on POI data within the Beijing Five-ring range. The experiment was carried out based on the road network and the grid. First,the two results were compared and verified in the same area of remote sensing image. Meanwhile,the main transportation hubs belonging to the traffic land were extracted. Second,this article analyzed the geographic feature of railway stations and airports based on the two perspectives of space service scope and spatial connection strength. Specifically,it includes the characteristics of spatial distribution range,the strength affected by the region,and the differences in the strength of spatial connections,etc. Last,further compare the commonality and difference between the space unit of each important transit hub as the starting point or the ending point of the taxi itinerary.

关 键 词：兴趣点数据 城市功能区识别 TF-IDF模型 交通枢纽 空间分析 

分 类 号：P208.1[天文地球—地图制图学与地理信息工程]