期刊名称：ISPRS International Journal of Geo-Information
电子版ISSN：2220-9964
出版年度：2021
卷号：10
期号：9
页码：596
DOI：10.3390/ijgi10090596
语种：English
出版社：MDPI AG
摘要：Population aging has become a notable and enduring demographic phenomenon worldwide. Older adults’ walking behavior is determined by many factors, such as socioeconomic attributes and the built environment. Although a handful of recent studies have examined the influence of street greenery (a built environment variable readily estimated by big data) on older adults’ walking behavior, they have not focused on the spatial heterogeneity in the influence. To this end, this study extracts the socioeconomic and walking behavior data from the Travel Characteristic Survey 2011 of Hong Kong and estimates street greenery (the green view index) based on Google Street View imagery. It then develops global models (linear regression and Box–Cox transformed models) and local models (geographically weighted regression models) to scrutinize the average (global) and location-specific (local) relationships, respectively, between street greenery and older adults’ walking time. Notably, green view indices in three neighborhoods with different sizes are estimated for robustness checks. The results show that (1) street greenery has consistent and significant effects on walking time; (2) the influence of street greenery varies across space—specifically, it is greater in the suburban area; and (3) the performance of different green view indices is highly consistent.
