► We examined the effects of spatial resolution on relationship between LST and urban greenspace. ► Landscape metrics of greenspace varied by spatial resolution. ► Relationship between LST and abundance of greenspace was consistent across spatial resolution. ► Relationship between LST and spatial configuration of greenspace varied by spatial resolution. Urban heat island (UHI) is a worldwide phenomenon, which causes many ecological and social consequences. Urban greenspace can decrease environmental temperature and thus alleviate UHI effects. Spatial pattern of greenspace, both composition and configuration, significantly affects land surface temperature (LST). Results from previous studies, however, showed inconsistent, or even contradictory relationships between LST and spatial pattern of greenspace, suggesting these relationships may be scale dependent (sensitive to spatial resolution). But few studies have explicitly addressed this issue. This paper examines whether the spatial resolution of the imagery used to map urban greenspace affect the relationship between LST and spatial pattern of greenspace, using Beijing, China as a case study. Spatial pattern of greenspace was measured with seven landscape metrics at three spatial resolutions (2.44m, 10m, and 30m) based on QuickBird, SPOT, and TM imagery. LST was derived from thermal band of Landsat TM imagery. The relationship between LST and spatial pattern of greenspace was examined by Pearson correlation and partial Pearson correlation analysis using census tract as analytical unit. Results showed that landscape metrics of greenspace varied by spatial resolution. Imagery with higher spatial resolution could more accurately quantify the spatial pattern of greenspace. The relationship between LST and abundance of greenspace was consistently negative, but the relationship between LST and spatial configuration of greenspace varied by spatial resolution. This study extended our scientific understanding of the effects of spatial pattern, especial spatial configuration of greenspace on LST. In addition, it can provide insights for urban greenspace planning and management.