OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Interactive image-based information visualization for aircraft trajectory analysis

Hurter, Christophe and Conversy, Stéphane and Gianazza, David and Telea, Alexandru Interactive image-based information visualization for aircraft trajectory analysis. (2014) Transportation Research Part C: Emerging Technologies, 47. 207-227. ISSN 0968-090X

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
5MB

Official URL: http://dx.doi.org/10.1016/j.trc.2014.03.005

Abstract

Objectives: The objective of the presented work is to present novel methods for big data exploration in the Air Traffic Control (ATC) domain. Data is formed by sets of airplane trajectories, or trails, which in turn records the positions of an aircraft in a given airspace at several time instants, and additional information such as flight height, speed, fuel consumption, and metadata (e.g. flight ID). Analyzing and understanding this time-dependent data poses several non-trivial challenges to information visualization. Materials and methods: To address this Big Data challenge, we present a set of novel methods to analyze aircraft trajectories with interactive image-based information visualization techniques.As a result, we address the scalability challenges in terms of data manipulation and open questions by presenting a set of related visual analysis methods that focus on decision-support in the ATC domain. All methods use image-based techniques, in order to outline the advantages of such techniques in our application context, and illustrated by means of use-cases from the ATC domain. Results: For each considered use-case, we outline the type of questions posed by domain experts, data involved in addressing these questions, and describe the specific image-based techniques we used to address these questions. Further, for each of the proposed techniques, we describe the visual representation and interaction mechanisms that have been used to address the above-mentioned goals. We illustrate these use-cases with real-life datasets from the ATC domain, and show how our techniques can help end-users in the ATC domain discover new insights, and solve problems, involving the presented datasets

Item Type:Article
Additional Information:Thanks to Elsevier editor. The definitive version is available at http://www.sciencedirect.com The original PDF of the article can be found at Transportation Research Part C: Emerging Technologies website : http://www.sciencedirect.com/science/journal/0968090X/47/supp/P2
HAL Id:hal-01120557
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Ecole Nationale de l'Aviation Civile - ENAC (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > University of Groningen (NETHERLANDS)
Laboratory name:
Statistics:download
Deposited By: IRIT IRIT
Deposited On:26 Feb 2015 07:26

Repository Staff Only: item control page