PM_2.5 pollution presents a significant risk to urban habitability. The urban landscape pattern (ULP) serves as a crucial regulator that profoundly influences the spatiotemporal distribution features of PM_2.5. Analysis of the driving mechanisms of the ULP is therefore essential for optimizing urban ecological spatial planning. However, the driving mechanism is dynamic and exhibits seasonal variations. This study selected four landscape metrics and four control variables, developed a geographically and temporally weighted regression (GTWR) model, and examined the spatiotemporal and seasonal effects of ULP on PM_2.5 concentrations in the central urban area of Urumqi (CUA) from 2003 to 2023. The results show the following: (1) Over the past two decades, the four ULP metrics have shown an increasing trend in the CUA. (2) The spatial distribution of PM_2.5 concentrations follows a latitudinal gradient, with higher concentrations observed in the northern regions and lower concentrations in the southern regions, initially increasing and then declining over time. (3) The driving mechanisms of ULP on PM_2.5 exhibited significant variations across different locations and time scales. (4) Seasonal variations arise from pronounced meteorological contrasts and intensified pollution from central heating, which is particularly evident in central CUA.