Data visualization techniques for airspace flow modeling

Abstract

Abstract-With the predicted growth of air traffic, traffic flow managers need new tools to access information to support their decision making processes. Recent progress with information visualization tools enables users to explore large data sets and extract decisive knowledge. Their advantages for air traffic applications are presented in this paper. They can provide high level information to aggregate trajectories. With constant feedback due to human perception, a flow model of the airspace, reflecting its intrinsic structure, is elaborated and can be used for further research.

Large-scale data-based collaborative air traffic optimization for congestion management

“…This is also a way to reduce the solve times and to add stochastic features with various uncertainties, such as weather perturbations. Similar work had been done by the authors on smaller instances in size and reported in [23].…”

“…Many flow characteristics are listed in [20] to describe flow patterns, such as the number of flows, the major flows and their size, etc. To the best of the authors' knowledge, the only existing work on data-based network synthesis for the air transportation system was produced by [21] and by the authors themselves [22,23]. These papers were either based on scheduled 1C2-3 flight plans or flown trajectories, and used various data-mining techniques, such as clustering and principal component analysis.…”

Attribute-driven edge bundling for general graphs with applications in trail analysis

“…The same query idea is used to extract trajectory parts in [15,2]. Eye tracking exploration: Density maps tackle the visual scalability problem by aggregating spatially close information for eye track analysis [2,1,34]. Burch et al transform eye tracks into a dynamic graph to help exploration [4].…”

Dynamic Multiscale Visualization of Flight Data

“…The FROMDADY system allows interactive linking and brushing of airplane trails to support complex queries in the entire attribute space recorded in the data set (Hurter et al, 2009). Density maps are effective to tackle the visual scalability problem, by aggregating spatially close information for trajectory analysis Andrienko et al, 2012;Marzuoli et al, 2012). Multimodal interactions help users in posing complex queries with little effort (Letondal et al, 2013).…”