Cluster Analysis to optimize your maps
Hierarchical Agglomerative Clustering
Taking the community world map as a example
- HAC is a machine learning algorithm
- The algorithm recursively merges the pair of clusters that minimally increases the linkage distance
- The linkage distance is the average euclidean distance of the airport radian coordinates
- More information about HAC on Wikipedia
Airports of the cluster center in the example
- Stockholm Skavsta Airport, Sweden
- Rennes Saint-Jacques Airport, France
- Kota Kinabalu International, Malaysia
- Ankara Esenboga International, Turkey
- Halifax Stanfield International, Canada
- Queen Beatrix International, Aruba
World Map with all flights
Stockholm Cluster
Avg Distance: 964 KM
Rennes Cluster
Avg Distance: 1372 KM
Kota Kinabalu Cluster
Avg Distance: 1907 KM
Ankara Cluster
Avg Distance: 1332 KM
Halifax Cluster
Avg Distance: 1572 KM
Oranjestad Cluster
Avg Distance: 1770 KM
Long Haul Flights above 9000 KM
North Atlantic Ocean
Gulf Super Connectors
Within the 48 Contiguous States
Within Europe
