Multidimensional urban segregation: An exploratory case study

Abstract

Segregation phenomena have long been a concern for policy makers and urban planners, and much attention has been devoted to their study, especially in the fields of quantitative sociology and geography. Perhaps the most common example of urban segregation corresponds to different groups living in different neighbourhoods across a city, with very few neighbourhoods where all groups are represented in roughly the same proportions as in the whole city itself. The social groups in question are usually defined according to one variable: ethnic group, income category, religious group, electoral group, age… In this paper, we introduce a novel, multidimensional approach based on the Self-Organizing Map algorithm (SOM). Working with public data available for the city of Paris, we illustrate how this method allows one to describe the complex interplay between social groups' residential patterns and the geography of metropolitan facilities and services. Further, this paves the way to the definition of a robust segregation index through a comparison between the Kohonen map and the actual geographical map.