基于多视图协同的时空数据可视分析方法  

Spatio-Temporal Data Visual Analysis Method Based on Multiple-View Collaboration

作　　者：刘明超[1] 吴升[1] 余劲松弟 LIU Mingchao WU Sheng YU Jinsongdi(Spatial Information Research Center of Fujian, Fuzhou University, Fuzhou 350003, Chin)

机构地区：[1]福州大学福建省空间信息工程研究中心,福建福州350003

出　　处：《测绘科学技术学报》2017年第2期211-214,220,共5页Journal of Geomatics Science and Technology

基　　金：海西政务大数据应用协同创新中心资助(闽教科[2015]75号);福建省科技创新平台项目(2015H2001);国家863重大项目(2012AA12A208)

摘　　要：针对时空数据可视分析中存在的问题,提出了由可视分析模型(VAM)和交互协同模型(ICM)组成的多视图协同可视分析模型,将可视分析过程划分为数据变换、数据分析、可视映射和可视绘制4个过程;以可视分析过程中的参数作为协同主题,利用观察者模式,实现关联视图在交互过程中的协同一致;设计了Web环境下,基于"图数协同"和"图图协同"交互模式的多视图协同可视分析架构;构建了犯罪时空数据可视分析原型系统,并利用系统分析了福州市扒窃案的时空分布规律,对涉案价值较高的扒窃案进行了犯罪模式分析。According to requirements of crime visual analysis, a multi-view collaborative visual analysis model is proposed which contains a Visual Analysis Model （VAM） and a Interactive Collaborative Model （ICM）. The corresponding process is divided into four steps which include data transformation, data analysis, visual mapping and visual drawing. Accordingly, the observer pattern is applied to realize the coordination of the related views in this interactive process. Furthermore, the architecture of multiple-view collaboration is designed based on ＂view-to-da- ta＂ and ＂view-to-view＂ interaction Web patterns. Finally, a prototype system of spatio-temporal data visual analysis for crime in Fuzhou is designed and implemented which is used to analyze the spatiotemporal distribution of pickpocketing and a crime pattern for the high-value cases involving pickpocketing.

关 键 词：多视图协同 时空数据 可视分析 交互协同 犯罪数据 

分 类 号：P209[天文地球—测绘科学与技术]