Optimization of green space in high-density built-up areas based on cooling simulations: A case study in Xi'an, China

Abstract

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.