Urban environments offer a wealth of opportunities for residents to respite from their hectic life.Outdoor running or jogging becomes increasingly popular of an option.Impacts of urban environments on outdoor running,...Urban environments offer a wealth of opportunities for residents to respite from their hectic life.Outdoor running or jogging becomes increasingly popular of an option.Impacts of urban environments on outdoor running,despite some initial studies,remain underexplored.This study aims to establish an analytical framework that can holistically assess the urban environment on the healthy vitality of running.The proposed framework is applied to two modern Chinese cities,i.e.,Guangzhou and Shenzhen.We construct three interpretable random forest models to explore the non-linear relationship between environmental variables and running intensity(RI)through analyzing the runners'trajectories and integrating with multi-source urban big data(e.g.,street view imagery,remote sensing,and socio-economic data)across the built,natural,and social dimensions,The findings uncover that road density has the greatest impact on RI,and social variables(e.g.,population density and housing price)and natural variables(e.g.,slope and humidity)all make notable impact on outdoor running.Despite these findings,the impact of environmental variables likely change across different regions due to disparate regional construction and micro-environments,and those specific impacts as well as optimal thresholds also alter.Therefore,construction of healthy cities should take the whole urban environment into account and adapt to local conditions.This study provides a comprehensive evaluation on the influencing variables of healthy vitality and guides sustainable urban planning for creating running-friendly cities.展开更多
Regular evaluation of street space is essential for achieving sustainable development and dynamic maintenance of historic areas.Although quantitative evaluations using street view imagery are precise and efficient,the...Regular evaluation of street space is essential for achieving sustainable development and dynamic maintenance of historic areas.Although quantitative evaluations using street view imagery are precise and efficient,they often fall short in capturing pedestrians’visual experience,largely because images are collected from vehicles.Accordingly,this paper acquires street view imagery in the human visual field before and after the street space renovation by adjusting relevant parameters,and performs image semantic segmentation.From a pedestrian’s viewpoint,the paper develops street space evaluation indicators across four dimensions:comfort,identity,diversity,and walkability.The mean square deviation method is applied to assign weights to these indicators,enabling a comprehensive evaluation of street space in historic areas.In addition to evaluating the renovation results,it proposes improvement suggestions that may provide insights into the evaluation practices of street space renovations in historic areas and contribute to improving street space quality.展开更多
基金National Natural Science Foundation of China,No.42171455The Hong Kong RGC Research Impact Fund,No.R5011-23The Hong Kong General Research Fund,No.15204121。
文摘Urban environments offer a wealth of opportunities for residents to respite from their hectic life.Outdoor running or jogging becomes increasingly popular of an option.Impacts of urban environments on outdoor running,despite some initial studies,remain underexplored.This study aims to establish an analytical framework that can holistically assess the urban environment on the healthy vitality of running.The proposed framework is applied to two modern Chinese cities,i.e.,Guangzhou and Shenzhen.We construct three interpretable random forest models to explore the non-linear relationship between environmental variables and running intensity(RI)through analyzing the runners'trajectories and integrating with multi-source urban big data(e.g.,street view imagery,remote sensing,and socio-economic data)across the built,natural,and social dimensions,The findings uncover that road density has the greatest impact on RI,and social variables(e.g.,population density and housing price)and natural variables(e.g.,slope and humidity)all make notable impact on outdoor running.Despite these findings,the impact of environmental variables likely change across different regions due to disparate regional construction and micro-environments,and those specific impacts as well as optimal thresholds also alter.Therefore,construction of healthy cities should take the whole urban environment into account and adapt to local conditions.This study provides a comprehensive evaluation on the influencing variables of healthy vitality and guides sustainable urban planning for creating running-friendly cities.
文摘Regular evaluation of street space is essential for achieving sustainable development and dynamic maintenance of historic areas.Although quantitative evaluations using street view imagery are precise and efficient,they often fall short in capturing pedestrians’visual experience,largely because images are collected from vehicles.Accordingly,this paper acquires street view imagery in the human visual field before and after the street space renovation by adjusting relevant parameters,and performs image semantic segmentation.From a pedestrian’s viewpoint,the paper develops street space evaluation indicators across four dimensions:comfort,identity,diversity,and walkability.The mean square deviation method is applied to assign weights to these indicators,enabling a comprehensive evaluation of street space in historic areas.In addition to evaluating the renovation results,it proposes improvement suggestions that may provide insights into the evaluation practices of street space renovations in historic areas and contribute to improving street space quality.
