A typology of street patterns
Author(s) -
Rémi Louf,
Marc Barthélemy
Publication year - 2014
Publication title -
journal of the royal society interface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.655
H-Index - 139
eISSN - 1742-5689
pISSN - 1742-5662
DOI - 10.1098/rsif.2014.0924
Subject(s) - typology , dendrogram , hierarchical clustering , sample (material) , fingerprint (computing) , geography , set (abstract data type) , cluster analysis , cluster (spacecraft) , computer science , distribution (mathematics) , artificial intelligence , cartography , pattern recognition (psychology) , mathematics , sociology , demography , archaeology , mathematical analysis , population , chemistry , chromatography , genetic diversity , programming language
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 four 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 characterizing 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.
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