基于位置数据和POI的聚类方法  

Clustering Method Based on Location Data and POI

作　　者：刘辉[1] 黄新[1] 王京晶[1] 

机构地区：[1]武汉市国土资源和规划信息中心,湖北武汉430013

出　　处：《地理空间信息》2017年第11期46-49,共4页Geospatial Information

基　　金：国家自然科学基金资助项目(41271399);国家科技支撑计划课题资助项目(2013BAJ05B00)

摘　　要：提出了一种基于自适应迭代的空间聚类方法,以探索城市空间设施与人们出行行为的内在关系。基于位置数据和POI,先将微博数据进行格网化,转化为连续的格网数据;再利用自适应迭代的聚类方法和相关性分析探索微博的空间分布和城市公共服务设施的时间活跃度。实验结果表明,微博数据和服务设施之间具有较强的相关性,并从大数据分析角度为城市规划布局的优化提供了辅助决策;但将其应用到实际规划中还有待进一步验证和完善。An spatial clustering method based on adaptive iteration was proposed,in order to explore the relationship between urban public facilities and people's travel behavior. Combined with microblogs and POIs, the mircoblogs were divided into continuous grid surface data at first. And then, the adaptive iterative clustering method and correlation analysis were used to explore the spatial distribution of microblogs and the temporal activity of urban public facilities. The experimental result shows that there is a strong correlation between microblogs and public facilities. And this study can provide a support for optimizaiton of the layout of urban planning on the view of big data analysis.

关 键 词：位置数据 聚类分析 POI 公共服务设施 

分 类 号：P208[天文地球—地图制图学与地理信息工程]