Comparing bike networks and street networks through network orientation entropy
We present a method for comparing bike networks and their associated street networks using network orientation entropy. This involved extracting the distribution of angles that the edges in the network made with respect to north and comparing the bike distributions with its street distribution using KL divergence. We also measured how much of the streets are covered by bike lanes by looking at its relative node density and length coverage. We used these to analyze the bike network of Metro Manila and compare it against five other cities with their own bike infrastructures. Using these methods, we find that while less than 11% of the street network is tagged for bikes, the bike orientation distribution still matches the street orientation distribution well. This is likely due to the bike lanes being present along major roads in the cities.