利用社交媒体数据探测细粒度城市子区域  

Detecting Fine-grained Urban Sub-region Using Social Media Data

作　　者：武善梅 王艳东[1,2] 乔梦玲 邵世维 刘辉[3] WU Shanmei;WANG Yandong;QIAO Mengling

机构地区：[1]武汉大学,测绘遥感信息工程国家重点实验室,湖北武汉430079 [2]地球空间信息技术协同创新中心,湖北武汉430079 [3]武汉市国土资源和规划信息中心,湖北武汉430014

出　　处：《地理空间信息》2020年第9期122-125,I0007,共5页Geospatial Information

基　　金：国家重点研发计划资助项目(2016YFB0501403);国家自然科学基金资助项目(41271399);测绘地理信息公益性行业科研专项经费资助项目(201512015)。

摘　　要：对城市中人类活动子区域的精细探测,能为城市资源合理配置和科学管理提供有效依据。提出了一种使用社交媒体数据细粒度分割城市空间区域的方法,基于带有地理位置的社交媒体数据,利用大量用户移动数据构建空间交互网络,利用复杂网络的社区发现算法探测城市子区域。实验结果表明,利用社交媒体数据能较好地探测出反映人们真实活动空间的细粒度城市区域,为城市管理提供参考。The fine detection of human activity sub-region of the city is an effective basis for realizing the appropriate city resource allocation and scientific management.In this paper,we proposed a method of finely dividing the urban area using social media data.Firstly,we built a spatial interactive network based on a large amount of user movement data obtained from geo-tagged social media data.Then,we used the community discovery algorithm in complex networks to detect the community structure.Finally,we revealed the urban sub-regions.The experimental results show that compared with single travel data,social media data cover a wider range of user activity types,which can divide urban space into finegrained sub-regions reflecting people’s real activity space with closer interaction.Compared with other top-down urban structures,such as administrative divisions,the fine-grained urban sub-region structure detected in this paper can provide a more detailed basis for urban management.

关 键 词：社交媒体 空间交互 社区发现 城市子区域 

分 类 号：P208[天文地球—地图制图学与地理信息工程]