Unequal Exposure to Safer-Looking Streets in Shanghai: A City-Scale Perception Model with Demographic Vulnerability

Visual cues in urban street environments shape residents’ perceived safety, and these perceptions often differ across social groups. Using Shanghai as a case study, this research focuses on two vulnerable populations: older adults and migrants. In the context of rapid urban transformation and increasingly fine-grained governance, perceived safety not only reflects environmental experience but also relates to whether different social groups can receive equitable perceptual support and access to opportunities for public-space use. We trained a deep learning model and rated perceived safety using over 160,000 street-level images, integrated with demographic census data at the neighborhood level, to systematically examine inequalities in visual environment perception and underlying group-specific mechanisms. However, existing studies have largely relied on small-sample surveys or average-effect analyses, and systematic evidence remains limited that can simultaneously characterize city-scale inequalities in perceived safety, disparities in group exposure, and group-specific mechanisms, while translating findings into actionable guidance for targeted governance. Firstly, we quantified spatial inequality in perceived safety using the Gini coefficient and the Theil T index. Decomposition results indicate that the remaining disparity is primarily associated with between-group differences linked to social structure. Nonparametric tests and multiple linear regression further identified significant interactions between demographic characteristics (the share of older adults and the migrant proportion) and visual environmental features, confirming group-differentiated responses to comparable streetscape conditions. In addition, we developed a priority governance index that combines perceived safety scores with vulnerability indicators to spatially identify neighborhoods requiring targeted interventions. Results suggest relatively low overall spatial inequality in perceived safety at the city scale, while decomposition analyses reveal clear group-structured disparities between central and peripheral areas and between local residents and migrants. Migrants are more frequently concentrated in neighborhoods with lower perceived safety. Priority intervention areas are primarily older-adult communities in central districts and migrant settlements in peripheral areas, characterized by lower perceived safety and higher demographic vulnerability. These findings underscore the need to shift urban renewal from uniform improvements toward differentiated strategies that account for perceptual equity and social identity. Our main contribution is not the development of a new network architecture but the alignment of image-based perception estimates with demographic vulnerability at the neighborhood scale. By combining inequality decomposition with tests of interaction mechanisms, we provide governance-relevant evidence for identifying priority intervention areas and advancing fine-grained renewal decisions oriented toward visual justice.