Flow Maps are a useful way to display changing values in geocraphical context. By combining edges as far as adequate the designer can reduce the noise on the map in contrast to show every edge on its own. One well known example is Charles Minard’s visualization of French wine exports arount 1864.
A team of researchers (Doantam Phan, Ling Xiao, Ron Yeh, Pat Hanrahan and Terry Winograd) from Stanford University have published a paper back in 2005 about their approach to computer generated Flow Maps. Here’s a brief extcerpt from the abstract of the paper
Cartographers have long used flow maps to show the movement of objects from one location to another, such as the number of people in a migration, the amount of goods being traded, or the number of packets in a network. The advantage of flow maps is that they reduce visual clutter by merging edges. We present a method for generating flow maps using hierarchical clustering given a set of nodes, positions, and flow data between the nodes. Our techniques are inspired by graph layout algorithms that minimize edge crossings and distort node positions while maintaining their relative position to one another.