14 October 2009 Visualization analysis of multivariate spatial-temporal data of the Red Army Long March in China
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Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74920X (2009) https://doi.org/10.1117/12.838550
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Abstract
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.
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Ding Ma, Zhimin Ma, Lumin Meng, Xia Li, "Visualization analysis of multivariate spatial-temporal data of the Red Army Long March in China", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74920X (14 October 2009); doi: 10.1117/12.838550; https://doi.org/10.1117/12.838550
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