Author:
Zang Peng,Qiu Hualong,Zhang Haifan,Chen Kaihan,Xian Fei,Mi Jianghui,Guo Hongxu,Qiu Yanan,Liao Kaihuai
Abstract
The increased ageing of the population is a vital and upcoming challenge for China. Walking is one of the easiest and most common forms of exercise for older people, and promoting walking among older people is important for reducing medical stress. Streetscape green visibility and the normalised difference vegetation index (NDVI) are perceptible architectural elements, both of which promote walking behaviour. Methodologically we used Baidu Street View images and extracted NDVI from streetscape green visibility and remote sensing to scrutinize the nonlinear effects of streetscape green visibility and NDVI on older people’s walking behaviour. The study adopted a random forest machine learning model. The findings indicate that the impact of streetscape green visibility on elderly walking is superior to NDVI, while both have a favourable influence on senior walking propensity within a particular range but a negative effect on elderly walking inside that range. Overall the built environment had a non-linear effect on the propensity to walk of older people. Therefore, this study allows the calculation of optimal thresholds for the physical environment, which can be used by governments and planners to formulate policies and select appropriate environmental thresholds as indicators to update or build a community walking environment that meets the needs of local older people, depending on their own economic situation.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province
Subject
Ecology,Ecology, Evolution, Behavior and Systematics
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献