China faces rapid and significant challenges due to its rapidly increasing older population, prompting active efforts to promote the development of age-friendly environments. However, changes in the characteristics of these environments over time remain underexplored. Streets, as important spaces for the daily activities of older adults, are crucial to their health and quality of life. This study proposes a novel research framework utilizing time-series street view imagery to systematically assess the evolution of age-friendliness in the street environments of Shanghai’s central urban area between 2013 and 2019 and explores factors influencing this evolution. We extracted visual elements from Baidu Map street view images through semantic segmentation techniques and calculated five perceptual indicators, namely, greenness, walkability, safety, enclosure, and imageability, to evaluate age-friendliness scores. The results indicate that the age-friendliness of Shanghai’s streets has significantly improved, especially in greenness, enclosure, and walkability. At the subdistrict level, streets in the southern and eastern parts of the study area exhibited significant improvements in age-friendliness scores, yet they still lag behind the central areas. A clustering analysis identified two types of subdistricts that warrant focused attention. An analysis of street view elements revealed that trees, sidewalks, and buildings positively influence age-friendliness, whereas sky and roads have negative impacts. Our findings provide scientific evidence to inform intervention strategies in urban planning decision-making, and the proposed research methodology can be applied to explore other urban aspects and evaluate other cities.
Kuang et al. (Thu,) studied this question.