北京
空格(标点符号)
城市绿地
水平设计
建筑环境
地理
TRIPS体系结构
环境卫生
绿色基础设施
社会经济学
运输工程
中国
环境规划
计算机科学
医学
社会学
土木工程
工程类
考古
游戏设计
操作系统
人机交互
作者
Jiayu Wu,Zike Xu,Yunhan Jin,Yanwei Chai,Joshua Newell,Na Ta
标识
DOI:10.1016/j.landurbplan.2022.104381
摘要
Urban green space is conducive to the physical and mental health of residents. However, exposure to green space is often highly unequal. This research addresses a major gap in the green space literature: how daily mobility patterns lead to differential exposure to green space among residents and how this varies by gender. The study uses travel data (7,800 trips) from 662 residents in Beijing (Haidan District), in combination with high-resolution street-view data and machine learning, to measure exposure to green space. The results show that there are significant disparities with respect to exposure to green space during daily travel, with men having advantages in terms of this exposure. This is, in part, due to the fact that their travel patterns varied more widely. Women had more exposure to green space, in terms of overall travel time, but it was more constrained to selected routes. Reasons for these disparities are complex, with age, occupation, household type and travel mode (e.g., car, bus, by foot) all important factors that intertwine with gender. In addition to revealing gender disparities associated with exposure to green space, this study provides a novel mixed method to capture daily travel patterns that can be used for a broad array of inquiries related to mobility in the built environment.
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