When Clustering the Multiscalar Fingerprint of the City Reveals Its Segregation Patterns

Madalina Olteanu, Jean-Charles Lamirel

Abstract: The complexity of urban segregation challenges researchers to develop powerful and complex mathematical tools for assessing it. With more and more fine-grained and massive data becoming available these last years, individual-based models are now made possible in practice. Very recently, a mathematical object called multiscalar fingerprint [1], containing all possible and all scale individual trajectories in a city, was introduced. Here, we use clustering combined with specific measures for assessing features contributions to clusters, to explore this complex object and to single out hotspots of segregation. We illustrate how clustering allows to see where, how and to which extent segregation occurs.