Mapping Regional Variability Using a Perceived Urbanization Gradient: Beyond the Urban-Rural Binary with the Visual Self-Placement Scale

This paper focuses on how novel conceptions of urbanization, rurality and its measurement can aid in the detection of regional variability in social indicators such as well-being. While prevailing objective, categorical and text-based typologies of space tend to be limited by issues of zoning and scaling of space, this paper sets out to validate the newly developed visual Self-Placement Scale (SPS) by comparing its tracking of the regional distribution of well-being with that of objective spatial typologies. For this purpose, a nationwide online survey was conducted in Japan, gathering respondents from urban (n = 1500) and rural (n = 1000) municipalities, contrasting the distribution of several well-being measures across administrative, structural, and SPS typologies. Generalized Additive Models revealed that the subjective SPS best predicts various well-being aspects, even when controlling for sociodemographic covariates. The quasi-metric scale helped confirm non-linear distributions of well-being aspects across the urban-rural range of environments invisible to binary spatial typologies. Lastly, merits and issues of the new typology are discussed in light of current cross-regional research. We conclude that while the SPS grapples with limitations related to its subjectivity, it complements and surpasses the binary typologies in predicting wellbeing by quantitatively mapping well-being variability across a broad range of real-world human environments with an intuitive visual self-grading scale. The SPS thus offers easy access to granular spatial information when spatial data availability or resolution are limited, opening the door for future research on the regional variability of other social indicators.