at BigThink: “Thanks to Big Data, a new “Science of Cities” is emerging. Urban processes that until now could only be perceived subjectively can finally be quantified. Point in case: two French scientists have developed a mathematical formula to ‘fingerprint’ cities.
Take a good, close look at your fingertips. The pattern of grooves and ridges on your skin there [1] is yours alone. Equally unique is the warp and weft of urban road networks. No two cities’ street grids are exactly alike. Some are famously distinct. The forensic urbanist in all of us can probably recognise a blind map of New York, London and a few other global metropolises.
Rémi Louf and Marc Barthelemy examined the street patterns of 131 cities around the world. Not to learn them by heart and impress their fellow scientists at the Institut de Physique Théorique near Paris – although that would be a neat parlor trick. They wanted to see if it would be possible to classify them into distinct types. The title of their paper, A Typology of Street Patterns, is a bit of a giveaway: the answer is Yes.
Before we get to the How, let’s hear them explain the Why:
“[Street and road] networks can be thought as a simplified schematic view of cities, which captures a large part of their structure and organization and contain a large amount of information about underlying and universal mechanisms at play in their formation and evolution. Extracting common patterns between cities is a way towards the identification of these underlying mechanisms. At stake is the question of the processes behind the so-called ‘organic’ patterns – which grow in response to local constraints – and whether they are preferable to the planned patterns which are designed under large scale constraints”.
There have been attempts before to classify urban networks, but the results have always been colored by the subjectivity of what Louf and Barthelemy call the ‘Space Syntax Community’. That’s all changed now: Big Data – in this case, the mass digitization of street maps – makes it possible to extract common patterns from street grids in an objective manner, as dispassionately as the study of tree leaves according to their venation. …
Read their entire paper here.“