Flight Patterns

(Video requires QuickTime)

Last year, a three-minute video depicting air traffic patterns in the U.S. garnered quite a bit of attention across the internet. It was created by Aaron Koblin (who also gives credit to Scott Hessels and Gabriel Dunne), using actual FAA data, thus resulting in a visualization of flight paths into, out of, and throughout the country. As the video begins, these paths are first depicted as light streaks against a dark background, while the time of day and total number of airborne planes shows up at the bottom of the screen. As it progresses, the data is represented in different ways to show the emergence of various patterns. Immediately, as the first paths begin to form, the viewer sees a network take shape, with the busiest nodes corresponding to major airports in large cities. The video notes that patterns form even without geographical features; indeed, the viewer can make out continental borders and familiar cities without any such markings.

While the video has received more appreciation for its stylistic rather than purely scientific merits, it is suggestive for our study of networks and their applications. For example, it is clear the presence of connecting edges between cities is time-dependent; as night gradually turns to day, activity slowly picks up starting in the east, and ending in the west. It would be interesting to consider the consequences of having a network (not necessarily flight patterns) that might have some explicit cyclical time dependence, and what that means for each of the nodes, for the idea of betweenness, or for power held by each of the nodes. For instance, early on in the class we saw a graph representing relationships between high school students. However, the graph didn’t contain information about the duration of relationships, or when they happened, only that they happened. Other suggestions which come to mind are paths through which diseases might spread (through infected passengers), or how air pollution might be concentrated (in areas of dense activity).