Combining travel and population data through a bivariate spatial analysis to define Functional Urban Regions

Abstract

The aim of this paper is to provide support to the issue of defining Functional Urban Regions (FURs). We carried out an exploratory study in which both commuting trips and population data were used in a combined setting. To do this, Bivariate Exploratory Spatial Data Analysis was used, enabling permuted analyses of the variables considered. The municipalities of São Paulo state, Brazil, were used in the case study investigated in this research. We observed that this combined analysis has more satisfactory results when compared to the analyses of variables in an isolated way. There is also a greater correlation of the results obtained from bivariate analysis with the official delimitations. Considering the possible permuted analyses, which are travel data versus population or population versus travel data, the first showed more reliable results in terms of identifying municipalities with strong correlations between the two variables. This can be observed both in areas within official FURs and throughout the territory, highlighting the areas of regional influence.