Geoff Boeing has created a cool Python package called OSMnx. It imports data from Open Street Map (OSM) and turns it into a network to calculate properties like betweenness centrality, average street length, and average circuity.
In this image, each node is colored by its betweenness centrality. If you make the shortest path between every node, the betweenness centrality of a node is the proportion of all those paths that have to pass through the node.
The red node has the highest betweenness centrality. 55% of the shortest paths go through that node.
The second cool thing that OSMnx does is produce images of the street networks with building footprints. Here are some images of Ann Arbor.
Downtown Ann Arbor:
North Campus:
Ypsilanti Township:
Detroit:
Downtown Detroit:
