Perception of socio-economic conditions of London highstreets

Urban visual environments often signal the wider social context we are in. Economic inequality – the uneven distribution of income and wealth – has been shown to undermine democratic behaviour, deteriorate social cohesion, and damage people’s wellbeing. Although it appears that perceived inequality (rather than its objective magnitude) has a mediating effect on its impact (Willis et al., 2022), the daily experiences and the environmental features signalling inequality to the observer are not understood. We are aiming to investigate how the visual appearance of urban locations varies within London (UK), and whether known image statistics may provide a visual signal of social perception (safety, affective response, willingness to engage, etc.) and economic inequality, which might be detected by observers. In our pilot, we captured over 2500 colour-calibrated images from 12 high streets across four different London boroughs (Brent, Ealing, Islington, Richmond) and calculated low- and mid-level image statistics relating to their visual features. We found that streets varied in terms of the naturalness of their colour distribution (after Maule et al., 2024), greenness, mean chromaticity, their Fourier amplitude spectral slope, and the presence of visual clutter (after Rosenholtz et al., 2007). We obtained a street-level economic inequality metric (Gini coefficient) from publicly available data on house prices (Suss, 2023). We found that inequality varied with several image statistics, indicating there may be low- or mid-level visual correlates of economic inequality which could inform observers’ perception of the socio-economic characteristics of a neighbourhood. Results from the pilot demand further investigation for evidence of a possible sensory route by which economic inequality can be detected, and therefore affect our behaviour and well-being, even in the absence of direct social interactions.