人类感知到的城市绿地如何有助于心理健康:一种机器学习方法
Enqi Cheng1, Yuejing Rong2, Yan Yan2
1State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
Journal of environmental management
|January 20, 2026
概括
城市绿地是城市的绿色空间.
科学领域:
- 城市绿地 (UGS) 研究
- 人类在景观生态中的感知
- 心理健康 (MWB) 研究研究
背景情况:
- 城市化增加了对心理健康 (MWB) 的UGS的关注.
- 宏观UGS研究缺乏微观感知洞察力,用于细粒度设计.
- 传统方法在UGS-MWB链接中与复杂的非线性关系作斗争.
研究的目的:
- 确定影响MWB的关键微规模UGS感知特征.
- 描述非线性关联轨迹和这些特征的相互作用.
- 将生态系统服务供需理论应用于UGS-MWB关系.
主要方法:
- 基于Landsenses的生态学和生态系统服务供需理论.
- 在北京奥林匹克森林公园使用可解释的机器学习 (随机森林和SHAP).
- 系统地确定了影响MWB的微环境因素.
主要成果:
- 自然UGS属性 (58%) 显著影响MWB,超过人口因素 (1.1%).
- 关键因素显示了与MWB的正面,非线性关联,具有加速/减速模式.
- UGS因素的主要影响比对互动更强,尽管存在一些协同效应/权衡.
结论:
- 多感官UGS感知与MWB密切相关.
- 结果指导UGS研究优先级和实验设计.
- 提供了优化UGS的证据,通过更好的生态资源分配来增强MWB.
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