Beyond the built-up form/mobility relationship: Spatial affordance and lifestyles

The aim of the paper is to explore the interplay of spatial affordance and lifestyles within a metropolitan context. The reorganisation of urban regions in integrated metropolitan areas generates new lifestyles based on hyper-mobility (often in the form of car dependency) and poly-topic practice of space. At the same time, the physical and functional characteristics of urban and rural components of space are modified. Within a quantitative approach, spatial indicators are used to describe the different facets of spatial affordance and of lifestyles of the resident population. The case study is the French Riviera metropolitan area, in south-eastern France. The indicators are used within a Bayesian Network model to identify typologies of place in the metropolitan area. Two typologies are produced. The first one identifies seven classes of spatial affordance ranging from regularly planned, dense and mixed urban cores to less accessible peripheral rural villages under metropolitan influence. The second one looks for profiles of place based on the prevalent lifestyles of its population (dwelling regimes). Once again seven classes are determined, including urban, suburban and metropolitan-rural lifestyles. The correspondence between spatial affordance and lifestyles is later explored to compose a more thorough description of places. The research confirms the need to enlarge the view of the built-up form/mobility relationship, shows the usefulness of the concepts of spatial affordance and dwelling regimes and explores new methodologies for identifying profiles of place. The probabilistic framework of Bayesian Networks proves particularly well suited to capture the fuzzy relationship between spatial affordance and lifestyle. •The concepts of spatial affordance and dwelling regime (prevailing lifestyle) are defined.•Within a quantitative approach, indicators are used to describe spatial affordance and dwelling regimes.•Indicators are calculated for spatial units in the metropolitan area of the French Riviera.•Bayesian Networks are used to infer typologies of place based on spatial affordance and dwelling regime indicators.•Cross-analysis of the two typologies is performed and new insight on the study area is gained going beyond the built-up form/mobility relationship.•All combinations of spatial affordance and dwelling regime types are not possible, as concordance relationships bind these two aspects of place.