A multi-scale analysis of factors influencing perceived urban safety: A case study of Helsingborg, Sweden

Perceived safety in urban areas depends on factors operating across multiple spatial scales. Nevertheless, most studies address only one scale at a time. The methodological contribution of this work lies on the introduction of a multi-scale approach for the analysis of perceived in urban areas. This approach includes city, neighbourhood, and individual scales. The overall goal is to identify the key determinants of perceived safety and to characterise perception bias (the mismatch between perceived and actual safety). Using Helsingborg (Sweden) as a case study, we integrate public health survey data (n = 5,697), the ScOut environmental database, police-defined vulnerable area classifications, a shooting incident database, and socio-demographic statistics. The case study shows that police-identified vulnerable areas predicted perceived safety better than the number of shootings. Low voter turnout and high unemployment showed the strongest socio-economic associations with lower perceived safety, while serenity (green space) and neighbourhood coherence (sense of community) were the most prominent correlated characteristics. At the individual scale, women, adults aged 65 and over, and people experiencing economic hardship reported the lowest perceived safety. This framework demonstrates how scale-sensitive predictive models can support targeted urban interventions.