The role of green space (GS) in mitigating the urban heat island (UHI) effect is well-recognized. However, practical research on GS optimization in high-density built-up areas, where land resources are scarce, remains limited. This study proposes a GS optimization method specifically designed for such areas, utilizing cooling simulations to establish a complete and feasible workflow. High-resolution remote sensing is employed to identify potential renewal parcels, with potential grading leading to various GS optimization scenarios. Cooling simulations and quantitative analysis at unit and block scales, conducted using the InVEST Urban Cooling Model (UCM) and ArcGIS, inform targeted GS strategies. A case study in Xi'an demonstrates the practical applicability of this approach, revealing temperature reductions of 0.25 %, 1.53 %, and 2.29 % as parcels progress from first- to third-level renewal. As a result, 40 %, 60 %, and 70 % of blocks experience effective UHI mitigation. The study further proposes GS optimization from both time-series and spatial strategies, enhancing the scientific accuracy and practical feasibility of GS strategies. This method offers a robust reference for GS construction in other high-density built-up areas facing ecological and land resource challenges where the UHI effect is significant.

中文翻译：

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基于降温模拟的高密度建成区绿地优化——以习安为例


绿地 （GS） 在缓解城市热岛效应 （UHI） 方面的作用是公认的。然而，在土地资源稀缺的高密度建成区，GS 优化的实践研究仍然有限。本研究提出了一种专门为此类区域设计的 GS 优化方法，利用冷却模拟来建立完整且可行的工作流程。高分辨率遥感用于识别潜在的更新宗地，潜在的分级会导致各种 GS 优化方案。使用 InVEST 城市供冷模型 （UCM） 和 ArcGIS 进行单元和块级的冷却模拟和定量分析，为有针对性的 GS 策略提供信息。习安的一个案例研究证明了这种方法的实际适用性，揭示了随着包裹从一级更新到三级更新，温度降低了 0.25%、1.53% 和 2.29%。因此，40%、60% 和 70% 的区块都获得了有效的 UHI 缓解措施。该研究进一步从时间序列和空间策略两方面提出了 GS 优化，提高了 GS 策略的科学准确性和实际可行性。该方法为其他面临 UHI 效应显著的生态和土地资源挑战的高密度建成区的 GS 建设提供了有力的参考。