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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.
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