Dependent in their own way: Spatial analysis of car dependence patterns in Lombardy region using bivariate classification

Car dependence is an increasing concern in the current urban and territorial challenges, generating significant environmental and social impacts. As a complex, multidimensional, and processual phenomenon, it requires analysis through interrelated, place-based indicators that reveal the driving forces behind its various dimensions. While existing literature offers a solid framework of predominantly quantitative approaches, it also highlights the need for interpretative methods that consider socio-spatial contexts, the system of preferences, and opportunities. To deal with the processual and multi-dimensional nature of car dependence, this paper explores the drivers and outcomes of car dependence across diverse socio-spatial settings in the Lombardy region (Italy) through two key concepts: car dependence level, which measures the alignment between driver and outcome variables (e.g., low density with high car use); and car dependence dissonance, which captures deviations from expected literature patterns. Using bivariate classification and spatial analysis of its maps, the study identifies the regional and multidimensional nature of car dependence, followed by a cluster analysis that categorises different territorial dynamics. The findings show that while major urban centres tend to display consistent low car dependence, scattered or peripheral zones present greater heterogeneity, challenging common assumptions and suggesting the need for nuanced, context-sensitive mobility strategies. • Car dependence is a multifaceted phenomenon lacking geographical approaches. • Car dependence is assessed spatially using bivariate classification-based methods. • The interaction of car dependence's drivers and outcomes unveils nuanced patterns. • Contexts with greater car dependence diverge more from established literature. • Car dependence requires a place-based approach, especially far from cities.