Assessing Street Environments for Older Adults in Urban Villages Using POIs and Street View Images—A Case Study of Guangzhou, China

In China’s urban villages, typically low-income communities, the living environments of older adults are often overlooked. Furthermore, quantitative research in these areas has been limited by the complexity of their street environments. This research bridges these gaps through an innovative interdisciplinary quantitative approach, integrating points of interest (POIs) and street view images (SVIs) to assess the street environments for older adults using ArcGIS and deep learning-based Fully Convolutional Networks. Specifically, Huangcun in Guangzhou, China, was selected for its typicality, with features like high density, complex street environments, and a significant older adult population. The findings reveal that while most age-friendly facilities meet basic needs, there are significant deficiencies in accessibility, comfort, and safety which call for targeted environmental improvements. This study contributes to sustainable urban development by providing street-by-street insights that empower urban planners to rectify spatial inequalities and to foster environments conducive to aging in place. By developing and applying a novel methodology that enhances urban age-friendliness assessments, this research extends the application of such models across diverse urban settings globally, promoting the integration of sustainability in urban planning.