Exploring non-linear effects of environmental factors on the volume of pedestrians of different ages using street view images and computer vision technology

Abstract

Creating pedestrian-friendly neighborhoods and encouraging walking activities not only improves urban liveliness but also delivers health and environmental benefits. Previous research has largely focused on individual walking behavior, which often exhibits stronger associations with personal traits than with built environment characteristics. Pedestrian volume, a significant indicator of urban vitality and collective walking behavior, may have a stronger relationship with environmental characteristics. Moreover, prior studies often hypothesize a linear relationship between built environmental determinants and walking behavior. The exploration of potential non-linear influences may help policy makers and urban planners by identifying minimum, maximum, and optimal values of built environmental variables conducive for walking. Furthermore, studies focusing on the collective walking of older pedestrians remain scarce in the context of aging societies.In this study, we utilize street view imagery and advanced computer vision algorithms to estimate citywide pedestrian volumes and their corresponding age classifications (older adults vs. all). Additionally, we assessed both micro and macro built environmental factors. The possible non-linear impact is examined using Gradient Boosting Decision Tree (GBDT). Our findings reveal disparities in the influence of environmental determinants on the volume of older pedestrians versus that of all pedestrians. Also, the significance of environmental elements exhibits variations across different spatial resolutions. Further, both eye-level vegetation and building level show an inverted U-shaped influence on the pedestrian count.