English

A typology of street patterns

Physics and Society 2014-10-09 v1 Disordered Systems and Neural Networks

Abstract

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.

Keywords

Cite

@article{arxiv.1410.2094,
  title  = {A typology of street patterns},
  author = {Rémi Louf and Marc Barthelemy},
  journal= {arXiv preprint arXiv:1410.2094},
  year   = {2014}
}

Comments

9 pages, 6 figures