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适应高温天气的绿色空间营造优先级研究——以北京中心城区为例
陈麦尼,党安荣*,李翔宇,翁阳,黄竞雄
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作者简介:陈麦尼 1993年生/男/浙江温州人/清华大学建筑学院在读博士研究生/研 究方向为城乡规划技术科学(北京 100084)
摘要:
加剧的高温天气是全球气候变化的主要气候风险之一,绿色空间营造是适应高温天气的有效举措。诸多城市在绿地建设方面已取得显著成效,但高温脆 弱群体的降温需求与城市绿地的有效供给之间仍存在一定的空间错配。以北京市中心城区为例,在以风险评估为核心的传统研究框架基础上创新性地引入了可行 性和有效性2个维度,提出了综合“风险-可行性-有效性”的绿色空间营造优先级评估框架,结合高时空分辨率的遥感数据开展高精度实证分析,旨在识别需要优 先营造绿色空间的区域,以有效降低高温脆弱群体的风险。研究表明:北京中心城区绿色空间营造优先级呈现出“核心区低、四环内高”的空间格局,高优先级 区域主要集中于南四环周围,并对不同优先级提出针对性规划响应策略。与传统方法相比,通过引入可行性和有效性2个维度,不仅关注高温健康风险,还综合考 虑了绿色空间扩增的可实施性与非线性降温效能差异。这一框架不仅适用于北京市的案例研究,同时也为其他城市在资源有限的条件下优化绿色空间配置提供了 有价值的模型方法和策略支持
关键词:  风景园林  韧性城市  高温健康风险  绿色基础设施  生态系统服务  空间优化
DOI:10.19775/j.cla.2025.07.0038
投稿时间:2024-12-28修订日期:2025-04-22
基金项目:国家自然科学基金重点项目(52130804)
Prioritization Study on Green Space Planning for High-temperature Adaptation: A Case Study ofBeijing's Central Urban Districts
CHEN Maini,,DANG Anrong*,,LI Xiangyu,,WENG Yang,,HUANG Jingxiong
Abstract:
Intensifying high-temperature weather has become a key climate risk globally, exacerbated by urbanization and anthropogenic climate change. Green space development is widely recognized as an effective adaptation strategy due to its proven capacity to mitigate urban heat islands and reduce health risks associated with extreme heat. While significant progress has been made in urban greening initiatives globally, a persistent spatial mismatch exists between the cooling needs of heat-vulnerable populations and the equitable provision of urban green spaces. Addressing this mismatch requires a nuanced understanding of localized priorities for green infrastructure investment. This study focuses on Beijing's central urban area, a region characterized by rapid urbanization, high population density, and escalating heat-related vulnerabilities. Building upon the traditional risk assessment framework, we innovatively integrate feasibility and effectiveness dimensions to propose a comprehensive "risk-feasibility-effectiveness" evaluation framework for prioritizing green space development. Methodologically, this research leverages multi-source, highresolution spatiotemporal data to enhance analytical precision. High-temperature hazard parameters are derived from ECOSTRESS satellite thermal imagery (70 m resolution) and Landsat data, capturing diurnal variations in surface temperature to quantify heatwave intensity and frequency. Population exposure is mapped using WorldPop 2020 demographic data (100 m resolution), while vulnerability is assessed through indicators such as elderly population density, socioeconomic status (derived from NPP-VIIRS nighttime light data), and healthcare accessibility (based on OpenStreetMap POI analysis). Feasibility is evaluated using GF-2 satellite imagery (2 m resolution) to identify available land resources (e.g., grasslands, bare land, and vacant plots), constrained by permanent basic farmland boundaries. Effectiveness is quantified through Meta's Global Canopy Height dataset (1 m resolution), enabling precise modeling of nonlinear cooling efficiencies linked to tree canopy coverage. The findings reveal a distinct spatial pattern in green space prioritization across Beijing's central urban area: low-priority zones dominate the historic core due to land scarcity, while high-priority areas cluster within the Fourth Ring Road, particularly southward. These high-priority regions exhibit synergistic advantages – elevated heat-health risks, sufficient land availability, and high marginal cooling efficiency. For instance, neighborhoods near the southern Fourth Ring Road demonstrate acute vulnerabilities (e.g., dense elderly populations and limited healthcare access) alongside underutilized land parcels suitable for afforestation. In contrast, the urban core, despite its high risk and cooling potential, ranks lower due to infrastructural constraints. This study advances traditional frameworks by embedding practical considerations of implementation feasibility and ecological effectiveness into risk-based assessments. Unlike conventional approaches that prioritize risk hotspots alone, our tripartite framework ensures that green space interventions are both actionable and optimized for maximum cooling returns. For example, marginal cooling efficiency analysis reveals that incremental tree canopy increases in low-coverage areas (e.g., 10% to 20%) yield disproportionately higher temperature reductions compared to saturated zones. Such insights are critical for cities like Beijing, where land scarcity demands strategic resource allocation. The implications extend beyond local contexts. By providing a scalable model for integrating high-resolution data, multi-criteria decision-making, and spatial optimization, this framework offers a blueprint for cities worldwide grappling with climate adaptation under resource constraints. Future applications could incorporate dynamic population mobility data and seasonal thermal variations to refine prioritization further. Policymakers and planners are urged to adopt tiered strategies: directing immediate investments to high-priority zones, integrating green mandates into urban renewal plans for medium-priority areas, and deploying complementary measures (e.g., building retrofits) in low-priority yet high-risk locales.
Key words:  landscape architecture  resilient city  heat-health risk  green infrastructure  ecosystem services  spatial optimization

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