Assessing the Psychologically Restorative Effects of Urban Streetscapes: A Street-View Imagery and Semantic Segmentation Approach

Urban streets are critical public spaces that support residents’ daily psychological recovery, and their landscape quality is directly related to pedestrians’ physical and mental well-being. In the rapid urbanization process, numerous urban streets have exhibited problems such as excessive building density, cluttered visual interfaces, a lack of natural elements, and an absence of regional characteristics, leading to a continuous decline in the psychological restorative capacity of street spaces and failure to meet residents’ demands for a healthy urban environment. Existing research mostly employs qualitative assessment methods to evaluate walking experiences and psychological restoration levels of street environments, lacking high-precision, pixel-level quantification of street landscape elements and rarely incorporating regional cultural elements into the analytical framework of restorative environments. This study takes Foshan, a famous historical and cultural city in China, as the research object, and selects five typical streets in the main urban area, including comprehensive streets, living streets, landscape streets, commercial streets, and historical–cultural streets, to construct a technical route of “data collection–element quantification–model construction–effect analysis.” Leveraging the pre-trained Mask2Former semantic segmentation model and pedestrian-perspective street-view images (SVIs), combined with field research, the study quantifies 22 street landscape elements across five dimensions: environment, transportation, social interaction, facilities, and culture. Through PCA principal component analysis and K-means clustering, 20 typical photos were objectively sampled, and public psychological evaluations were conducted using the Perceived Restorativeness Scale (PRS). A stepwise multiple linear regression model was then employed to construct an exploratory explanatory model for street psychological restoration, identifying key influencing factors and their effect intensities. The results indicate the following: (1) Environmental and cultural elements are the core characteristics associated with pedestrians’ psychological restoration, whereas transportation, social, and facility elements are correlated only with certain restoration dimensions and show no significant association with the overall psychological restoration level. (2) Among the 22 element indicators, the Green View Index showed the strongest positive association with psychological restoration (β = 0.681, p < 0.001); historical memory markers and the Blue View Index also exhibited significant positive associations. (3) By integrating the elements associated with pedestrians’ psychological restoration and their association strengths, an exploratory explanatory model of the psychological restoration benefits of urban street landscapes was constructed, with an adjusted coefficient of determination of 69.8%, accounting for 69.8% of the variation in street psychological restoration levels. The findings establish an exploratory analytical framework and furnish empirical evidence for healthy city planning and street renewal in similar historical and cultural cities.