Measuring the age-friendliness of streets' walking environment using multi-source big data: A case study in Shanghai, China

The rapidly aging population demands more public and academic attention to both the physical and psychological needs of older adults. Walking is one of the most favored forms of transportation and exercise for older adults. Hence, the conditions of walkways and the built environment are critical for the development of an older adults-friendly society. In this research, considering six indicators of greenness, walkability, safety, imageability, enclosure, and complexity, a novel quantitative evaluation model based on multi-source geospatial big datasets is proposed for assessing the age-friendliness of streets' walking environment from both the older adults' and experts' perspectives and has also been successfully applied in the case study of Xuhui District in Shanghai, China. Based on the survey with both groups of older adults and experts, the age-friendliness of the streets' walking environment from both perspectives was obtained, analyzed, and compared. The results show that among all sub-districts in Xuhui District, Tianping Road Sub-district and Hunan Road Sub-district have the best walking environment; and the roads surrounding expressways or arterial roads typically have lower levels of age-friendliness, while sub-arterial roads and access roads generally exhibit higher levels of age-friendliness according to both older adults and experts. It is also noted that streets with high age-friendliness for older adults tend to be outstanding in walkability and greenness, whereas experts prefer streets with high safety and walkability. In addition, the comprehensive analysis of the impact factors on age-friendliness further reveals a series of hidden significant influencing factors associated with the different preferences between older adults and experts. It is believed that our findings are useful for supporting policy-makers on how to improve the age-friendliness of streets and build age-friendly cities.