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Interactive flights visualisation

Welcome to Arthur, Brice and Caroline's visualisation

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ABOUT THE PROJECT

flight

This data visualisation project was realised as part of the "Data Visualisation" course at Claude Bernard University (Lyon, France).

We had to create data visualisations from a subject on the theme of mobility and transport. This design also includes searching and preprocessing the data and writing a scientific article. You can find the whole project on: https://github.com/DatavisuProject/US_Flights

We would like to address special thanks to Romain Vuillemot for providing the idea for this visualisation.

Welcome to our project web page! We provide an interactive visualisation in time and space of flights in the United States at single-plane resolution. There exist a wide variety of flight route visualisations based on maps, showing in many cases the global trends in air traffic. Here we take a different perspective, showing air traffic patterns from a plane's eye view. The flights are domestic flights in the whole of US over the month of January 2015.

10 mini-maps are shown at a time each representing one aircraft's flight pattern. Over 4,000 aircraft trajectories can be viewed in this way. To the right is a Marey map showing the detailed flight trajectory of the selected plane. You can ask questions such as: how do different planes move around? Over what timescales? What are the central hubs? Tying these patterns to economic efficiency can also be of interest for airline companies and airports. By hovering over the circles and lines on the Marey map you can access airport names, flight distances and durations. The colors make it possible to highlight the punctuality of the different flights for a given plane.

Two types of filters are available: one to visualize any aircraft by tail number and the other to focus on airports of origin. Note that the airport of origin corresponds to the airport through which the plane flies the most.

Arthur Aubret
M2 computer science
Github page
Brice Letcher
M2 bioinformatics
Github page
Caroline Gaud
M2 bioinformatics
Github page