Abstract: With rapid urbanization and industrialization, more attention has been paid to atmosphere quality in China. PM_2.5, an important atmospheric pollutant, has attracted widespread public attention. Urban greenspace as a semi-natural surface landscape can affect the concentration and distribution of PM_2.5. Current studies mainly focus on micro-scale, with few on landscape scale. In this study, land use regression (LUR) model was used to densify monitoring points. Based on ordinary Kriging interpolation method, the spatial distribution of PM_2.5 concentration was simulated with high precision. We quantitatively analyzed the impacts of urban greenspace landscape characteristics and quality on PM_2.5 concentration by coupling urban greenspace interpreted by remote sensing. The results showed that PM_2.5 concentration decreased from central area to periphery. The impacts of greenspace on PM_2.5 concentration varied with greenspace types. The shape of greenspace had no effect on PM_2.5 concentration, while the area and quality of greenspace were significantly negatively correlated with PM_2.5 concentration. In general, the greenspace had an obvious PM_2.5 reduction effect in the distance of less than 100 m. Within the reduction distance, the closer to the greenspace, the lower the PM_2.5 concentration was. The reduction distance of the affiliated and park greenspace was larger than other greenspace types.