随着城市化进程加速,城市绿地的健康促进功能逐渐成为可持续发展和城市生态学研究的核心议题。现有研究普遍证实绿地暴露与居民生理、心理、社交健康及整体福祉存在显著关联,但对不同类型绿地暴露方式的量化表征及其健康效应尚缺乏系统性解析。基于国内外最新文献,围绕城市绿地的可视性、可用性与可达性三大绿地暴露量化指标展开综述。在量化方法层面,绿地可视性、可用性和可达性在不同时空尺度及地理空间数据获取条件下存在显著敏感性,未来可结合大数据与多源传感器技术提升测量精度;在健康效应层面,绿地暴露产生的健康效益受到人口背景和社会环境的显著影响,需建立涵盖城市生态学、社会经济学、建筑环境、个体行为的多维度分析框架;在实际应用层面,健康导向的绿地空间配置需要通过科学量化指导绿地选址、规模布局与配套设施建设,以实现健康公平。相关研究应着重构建城市形态多尺度模拟的绿地暴露-健康响应的因果推断模型,为优化城市绿地规划与公共卫生决策提供更加完善的理论基础与科学依据。
Abstract
As urbanization accelerates, the health-promoting functions of urban green spaces have increasingly emerged as a central focus in sustainable development and urban ecology research. Existing studies have consistently demonstrated significant associations between green space exposure and the physical, mental, social health, and overall well-being of residents. However, there remains a paucity of systematic analyses regarding the quantitative characterization of various types of green space exposure and their associated health effects. Based on the latest literature at home and abroad, this review focuses on three main quantitative indicators of urban green space exposure: visibility, availability, and accessibility. In terms of quantification methods, green visibility, availability, and accessibility exhibit significant sensitivity across different spatial-temporal scales and geospatial data acquisition conditions. Thus, future research could integrate big data and multi-source sensor technologies to improve measurement accuracy. In terms of health effects, the health benefits derived from green exposure are significantly influenced by demographic backgrounds and social environments. Therefore, it is necessary to establish a multi-dimensional analytical framework encompassing urban ecology, socioeconomics, built environments, and individual behaviors. In terms of practical applications, health-oriented green space planning requires scientifically quantified guidelines for green space site selection, scale layout, and facility construction to achieve health equity. Relevant studies should emphasize the construction of causal inference models for green exposure-health responses based on multi-scale simulations of urban forms, providing a more comprehensive theoretical foundation and scientific evidence for optimizing urban green planning and public health decision-making.
关键词
绿色空间 /
绿地暴露 /
城市规划 /
公众健康
Key words
green space /
green space exposure /
urban planning /
public health
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