  We propose a quantitative method to classify cities according to their street
pattern. We use the conditional probability distribution of shape factor of
blocks with a given area, and define what could constitute the `fingerprint' of
a city. Using a simple hierarchical clustering method, these fingerprints can
then serve as a basis for a typology of cities. We apply this method to a set
of 131 cities in the world, and at an intermediate level of the dendrogram, we
observe 4 large families of cities characterized by different abundances of
blocks of a certain area and shape. At a lower level of the classification, we
find that most European cities and American cities in our sample fall in their
own sub-category, highlighting quantitatively the differences between the
typical layouts of cities in both regions. We also show with the example of New
York and its different Boroughs, that the fingerprint of a city can be seen as
the sum of the ones characterising the different neighbourhoods inside a city.
This method provides a quantitative comparison of urban street patterns, which
could be helpful for a better understanding of the causes and mechanisms behind
their distinct shapes.
