The frequently breaking out fog and haze has attracted widespread public attention in China recently. PM_2.5 is considered to be main cause of it. Recent studies show that PM_2.5 is mainly controlled by the meteorological conditions in short temporal scale, for example, daily, but strongly affected by land cover, especially vegetation in long temporal scale such as yearly, seasonal. It is a challenge for landscape ecology to couple vegetation landscape pattern and PM_2.5 spatial information in order to quantitatively analyze the impacts. New idea and method are required to cope with it. Based on the assumption of a stable meteorological conditions within a season, this paper first used the land use regression (LUR) model to precisely simulate the spatial distribution of seasonal PM_2.5 concentration. Secondly, based on the pixel dichotomy model, the vegetation coverage of the study area was estimated for four seasons and the spatial distribution was determined. Finally, the impacts of vegetation landscape on PM_2.5 and the scale effects were discovered by means of pixel random sampling and regression models. The results showed as follows. 1) There existed a significant negative correlation between vegetation coverage and PM_2.5 concentration in the spatial scales adopted in this study. The influences not only varied from season to season, but also changed at different scales within the same season. 2) The forms of the effects of vegetation coverage on concentration were complicated. In general, the curve regression models were better than the linear ones, indicating that the relationship between vegetation coverage and PM_2.5 concentration was non-linear. 3) The higher the PM_2.5 concentration, the sharper the constructed curve model, and the stronger influence the vegetation coverage had on PM_2.5 concentration. This study puts forward a new idea to couple vegetation coverage and PM_2.5 to discover their relationship and scale effects in regional scale. It is expected to provide a reference for mitigating atmospheric pollution by optimizing urban vegetation landscape.