Abstract
Scaling laws between urban indicators and the population are one of the most striking and universal findings of recent urban studies. However, several government reports and academic works still ignore these nonlinearities when investigating rates or per capita values of urban indicators – a practice that introduces biases towards small or large cities. This chapter revisits an alternative approach capable of accounting for these biases by simply calculating differences between actual values of urban indicators and the values expected by the scaling laws – the so-called scale-adjusted metrics.
Type
Haroldo Valentin Ribeiro
Associate Professor
Ervin Kaminski Lenzi
Associate Professor
