Connected World: Untangling the Air Traffic Network

People travel not just more frequently, but increasingly far and quickly. Mapping the connections between all the airports worldwide is a fascinating network visualization exercise.
A network, in its very essence, is already a map. And the global transportation maps that represent the flight connections rarely make this network intelligible: on a world map, Europe is often a very dense area where it’s almost impossible to distinguish the dots/airports. Ultimately, these maps (sometimes very beautiful objects), do not represent the data itself, but some idea of the complexity and quantity.
This post (which may be followed by further experimentations in this area) is an attempt to make explicit the network behind air transport. The structure of the relationships has an impact on the spatial distribution of nodes in a graph. Let’s see how this landscape is reorganized without geographical constraints.


Full size GIF



airports network

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 This “map” is the result of the application of a force-directed layout algorithm on a graph of 3.275 airports (37.153 single routes – the weighted total is higher because many airlines take the same route), based on data. Naturally, network geography is not completely disrupted: the continents are mostly visible and regions are generally in their original position (with the exception of the Pacific islands that connect Asia and America – imagine this graph in three dimensions, with the Pacific Ocean behind). Major observations: India is more connected to the Middle East than to South and East Asia. The Russian cluster is very visible, connecting airports in Russia but also in many former Soviet republics. Latin america is clearly divided between a South cluster and a Central American cluster very connected with the U.S.

Bonus, the geographical layout of the same graph.


airports map small

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CC-BY-SA Freely reusable with a link to this post