Impact of urban greenspace spatial pattern on land surface temperature: a case study in Beijing metropolitan area, China

Context Urban greenspace can significantly decrease the land surface temperature (LST). The spatial characteristics and vegetation composition of urban greenspace have a great influence on its cooling capacity. Objectives We sought to distinguish the cooling effect by different spatial pattern factors of greenspace and by the interaction of these factors, which may be useful in understanding cooling effect and designing urban greenspace. Methods Both the greenspace derived from SPOT6 and LST retrieved from Landsat-8 images are employed to identify the dominant factors influencing LST and investigate the interaction between any two dominant factors in the Beijing metropolitan area. Results The results indicate that the dominant spatial factors affecting LST vary by greenspace type, i.e., for grass, the number of patches (NP) and patch density (PD) have a significant effect on LST while for coniferous forest, the landscape shape index (LSI) is the dominant spatial factor. And the NP and percentage of landscape are the dominant spatial factors for broad-leaved forest and mixed forest, respectively. The interaction of any two dominant factors is larger than their individual effects, and the interaction between the NP and LSI of greenspace is not as strong as the interaction between the NP and PD. Conclusions Urban greenspace design and planning need to consider the spatial pattern of different types of greenspace. On this basis, we proposed a pattern effective in cooling LST in cities climatically similar to Beijing, which could provide theoretical reference for the design and planning of urban greenspace.