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Visualization Analysis of Multivariate Spatial-Temporal Data of the Red Army Long March in China

机译:中国红军三月多元空间数据的可视化分析

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Recently, the visualization of spatial-temporal data in historic events is emphasized by more and more people. To provide an efficient and effective approach to meet this requirement is the duty of Geo-data modeling researchers. The aim of the paper is to ground on a new perspective to visualize the multivariate spatial-temporal data of the Red Army Long March, which is one of the most important events of the Chinese modem history. This research focuses on the extraction of relevant information from a 3-dimensional trajectory, which captures object locations in geographic space at specified temporal intervals. However, existing visualization methods cannot deal with the multivariate spatial-temporal data effectively. Thus there is a potential chance to represent and analyze this, kind of data in the case study. The thesis combines two visualization methods, the Space-Time-Cube for spatial temporal data and Parallel Coordinates Plots (PCPs) for multivariable data, to develop conceptual GIS database model that facilitates the exploration and analysis of multivariate spatial-temporal data sets in the combination with 3D Space-Time-Path and 2D graphics. The designed model is supported by the geo-visualization environment and integrates diverse sets of multivariate spatial-temporal data and built-up the dynamic process and relationships. It is concluded that this way of geo-visualization can effectively manipulate a large amount of distributed data, realize the high efficient transmission of quantitative and qualitative information and also provide a new research mode in the field of the History of CPC and military affairs.
机译:最近,越来越多的人强调了历史事件中的空间数据的可视化。提供有效有效的方法来满足此要求是地理数据建模研究人员的责任。本文的目的是在一个新的视角下,以可视化红军长征的多变量空间数据,这是中国调制解调器历史中最重要的事件之一。本研究侧重于从三维轨迹中提取相关信息,以指定的时间间隔捕获地理空间中的对象位置。然而,现有的可视化方法无法有效地处理多变量空间数据。因此,在案例研究中存在潜在的机会来代表和分析这种情况。本文结合了两个可视化方法,用于多变量数据的空间时间数据和并行坐标(PCP)的空间 - 时分立方体,以开发概念GIS数据库模型,其促进了组合中多变量空间数据集的探索和分析使用3D时空路径和2D图形。地理可视化环境支持设计的模型,并集成了不同集多元空间数据数据并建立了动态​​过程和关系。结论是,这种地理可视化方式可以有效地操纵大量分布式数据,实现了定量和定性信息的高效传输,并在CPC和军事历史中提供了一种新的研究模式。

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