Systematic overestimation of urban Parks’ cooling effects may mislead heat-governance-oriented park planning

Abstract

Urban parks play a crucial role in mitigating the urban heat island effect, and their cooling effects have been widely studied. However, data resolution limitations hinder the accurate capture of micro-scale temperature variations, leading to assessment biases. This study analyzed 36 parks within Beijing’s Fourth Ring Road, employing a downscaling model based on Landsat 8 and Sentinel-2 imagery to generate high-resolution land surface temperature (LST) data. Using maximum and cumulative cooling indicators alongside an improved threshold value of efficiency (TVoE) method, we examined how enhanced data resolution influences park cooling assessment outcomes. Results indicated that low-resolution LST data fail to accurately capture the first turning point (FTP) of the cooling curve, leading to varying degrees of overestimation in park cooling effects depending on the cooling indicator and park size. Specifically, park cooling distance (PCD), area (PCA), and efficiency (PCE) were overestimated by factors of 2.35, 1.80, and 6.21, respectively, with smaller parks showing more pronounced biases. Conversely, park cooling intensity (PCI) remained stable across resolutions. This anomaly may obscure overestimation issues and lead to underestimation of the TVoE (with the PCI-based TVoE being significantly lower than that derived from PCD and PCA), thereby misleading the practical planning, hindering the precise implementation of heat governance policies, and weakening the effectiveness of urban heat risk management. Therefore, future research should prioritize verifying PCD accuracy refine both data resolution and methodology to improve the precision of park cooling assessments, thereby providing more scientifically grounded guidance for urban park planning aimed at heat governance.