Microscopic Visual Analysis of High-Density Group Trajectory Data

People’s daily life is surrounded by Spatio-temporal trajectory datasets.Exploring and understanding the hidden patterns can help us grasp the characteristics of human productivity and improve management efficiency.Most previous works focused on the macroscopic analysis of trajectory datasets and lacked in-depth analysis of individual behaviors within high-density trajectory datasets in a small region.In this paper,we proposed a visual analysis system to analyze the high-density trajectory datasets.The method consists of four components,a small-multiples based feature statistical view for showing the features of various dimensions within dataset,a glyph-embedded multi-stream view for displaying overall evolution patterns and highlight critical modes,a projection view for illustrating the relative correlation among trajectories,and a multi-mode hierarchical spatial map for presenting detailed characteristics in the dataset.The interactive system has been used in two trajectory datasets to provide a solution for visually analyzing high-density trajectory datasets.