ABSTRACT
Urban scaling laws linking socio-economic and infrastructural features to population size imply that a more concentrated population corresponds to better socio-economic performances and less costly infrastructural investments. Quantifying urban microstructure and its evolution over multiple spatio-temporal scales has become a scientific priority with direct practical implications for the sustainable management of increasingly growing cities. In this chapter a short description is offered of how density-based clustering algorithms involving spatio-temporal long-range correlation among urban features can be linked to scaling laws of the population size.
