Animated visualization of spatial–temporal trajectory data for air-traffic analysis

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• 作者：Stefan Buschmann ; Matthias Trapp ; Jürgen Döllner
• 关键词：Spatio ; temporal visualization ; Trajectory visualization ; 3D visualization ; Visual analytics ; Real ; time rendering
• 刊名：The Visual Computer
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：32
• 期：3
• 页码：371-381
• 全文大小：3,189 KB
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• 作者单位：Stefan Buschmann (1)
  Matthias Trapp (1)
  Jürgen Döllner (1)
  
  1. Hasso Plattner Institute, University of Potsdam, Prof.-Dr.-Helmert-Str. 2-3, 14482, Potsdam, Germany
  
• 刊物类别：Computer Science
• 刊物主题：Computer Graphics
  Computer Science, general
  Artificial Intelligence and Robotics
  Image Processing and Computer Vision
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-2315

文摘

With increasing numbers of flights worldwide 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. To cope with these challenges, cyber worlds can be used for interactive visual analysis and analytical reasoning based on aircraft trajectory data. However, with growing data size and complexity, visualization requires high computational efficiency to process that data within real-time constraints. This paper presents a technique for real-time animated visualization of massive trajectory data. It enables (1) interactive spatio-temporal filtering, (2) generic mapping of trajectory attributes to geometric representations and appearance, and (3) real-time rendering within 3D virtual environments such as virtual 3D airport or 3D city models. Different visualization metaphors can be efficiently built upon this technique such as temporal focus+context, density maps, or overview+detail methods. As a general-purpose visualization technique, it can be applied to general 3D and 3+1D trajectory data, e.g., traffic movement data, geo-referenced networks, or spatio-temporal data, and it supports related visual analytics and data mining tasks within cyber worlds.