Cooling island effect in urban parks from the perspective of internal park landscape

Abstract Urban parks can effectively reduce surface temperatures, which is an important strategic approach to reducing the urban heat island effect. Quantifying the cooling effect of urban parks and identifying their main internal influencing factors is important for improving the urban thermal environment, achieving maximum cooling benefits, and improving urban sustainability. In this study, we extracted data frobut this is often unrealisticm 28 urban parks in Zhengzhou, China. We combined multivariate data, such as Landsat 8 data, to retrieve the land surface temperature (LST), extract the park interior landscape, and quantify the cooling effect using three cooling indices: park cooling distance ( L ∆max ), temperature difference magnitude (∆ T max ), and temperature gradient ( G temp ). Furthermore, the relationship between the internal landscape characteristics of the park and the average LST and cooling indices of the park was analyzed. The results showed that different buffer ranges affect the LST-distance fitting results of urban parks, and a 300-m buffer zone is the optimal fitting interval. However, specific parks should be analyzed to select the optimal buffer range and reduce the cooling index calculation errors. Additionally, the mean values of LST, ∆ T max , L ∆max , and G temp for the 28 parks in Zhengzhou were 34.11, 3.22 °C, 194.02 m, and 1.78 °C/hm, respectively. Park perimeter (PP), park area, internal green area (GA), and landscape shape index (LSI) were both significantly correlated with ∆ T max and the main factors associated with maintaining a low LST in parks. L ∆ max was mainly affected by the GA, LSI, and perimeter-area ratio, whereas G temp was positively correlated with PP. Finally, the threshold value of efficiency for parks in Zhengzhou was 0.83 ha, and comprehensive parks showed optimal cooling in every aspect.