Real-Time Animated Visualization of Massive Air-Traffic Trajectories

被引:9
|
作者
Buschmann, Stefan [1 ]
Trapp, Matthias [1 ]
Doellner, Juergen [1 ]
机构
[1] Hasso Plattner Inst, Comp Graph Syst, Potsdam, Germany
关键词
spatio-temporal visualization; trajectory visualization; 3D visualization; visual analytics; real-time rendering; SPACE; CUBE;
D O I
10.1109/CW.2014.32
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
With increasing numbers of flights world-wide and a continuing rise in airport traffic, air-traffic management is faced with a number of challenges. These include monitoring, reporting, planning, and problem analysis of past and current air traffic, e.g., to identify hotspots, minimize delays, or to optimize sector assignments to air-traffic controllers. Interactive and dynamic 3D visualization and visual analysis of massive aircraft trajectories, i.e., analytical reasoning enabled by interactive cyber worlds, can be used to approach these challenges. To facilitate this kind of analysis, especially in the context of real-time data, interactive tools for filtering, mapping, and rendering are required. In particular, the mapping process should be configurable at run-time and support both static mappings and animations to allow users to effectively explore and realize movement dynamics. However, with growing data size and complexity, these stages of the visualization pipeline require computational efficient implementations to be capable of processing within real-time constraints. This paper presents an approach for real-time animated visualization of massive air-traffic data, that implements all stages of the visualization pipeline based on GPU techniques for efficient processing. It enables (1) interactive spatio-temporal filtering, (2) generic mapping of trajectory attributes to geometric representations and appearances, as well as (3) real-time rendering within 3D virtual environments, such as virtual 3D airport and city models. Based on this pipeline, different visualization metaphors (e.g., temporal focus+context, density maps, and overview+detail visualization) are implemented and discussed. The presented concepts and implementation can be generally used as visual analytics and data mining techniques in cyber worlds, e.g., to visualize movement data, geo-referenced networks, or other spatio-temporal data.
引用
收藏
页码:174 / 181
页数:8
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