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Analysis of flight variability: A systematic approach

: Andrienko, N.; Andrienko, G.; Garcia, J.M.C.; Scarlatti, D.


IEEE transactions on visualization and computer graphics 25 (2019), Nr.1, S.54-64
ISSN: 1077-2626
European Commission EC
H2020-EU.2.1.1.; 687591; datACRON
ig Data Analytics for Time Critical Mobility Forecasting
European Commission EC
H2020-EU.2.1.1.; 688380; VaVeL
Variety, Veracity, VaLue: Handling the Multiplicity of Urban Sensors
European Commission EC
H2020-EU.2.1.1.; 780754; Track and Know
Big Data for Mobility Tracking Knowledge Extraction in Urban Areas
Fraunhofer IAIS ()

In movement data analysis, there exists a problem of comparing multiple trajectories of moving objects to common or distinct reference trajectories. We introduce a general conceptual framework for comparative analysis of trajectories and an analytical procedure, which consists of (1) finding corresponding points in pairs of trajectories, (2) computation of pairwise difference measures, and (3) interactive visual analysis of the distributions of the differences with respect to space, time, set of moving objects, trajectory structures, and spatio-temporal context. We propose a combination of visualisation, interaction, and data transformation techniques supporting the analysis and demonstrate the use of our approach for solving a challenging problem from the aviation domain.