In recent years, the red turpentine beetle (RTB), an invasive pest species, has caused extensive pine mortality in North China. Although some studies have theoretically clarified the interference mechanism of multi-level factors with the development of RTB damage, knowledge about this mechanism from the empirical research is still limited. The aim of this study was to determine whether the primary factors influencing RTB occurrence change during different periods of RTB invasion. Stand-level variables of sample plots were obtained through field investigation and the forest resource survey data including forest stand characteristics, topographic characteristics, and soil properties. Remote sensing classified images were to develop the characteristic variables related to landscape composition and configuration around the sample plots at multiple scales. Generalized linear models (GLMs) and generalized linear mixed models (GLMMs) were used to explore the relative importance of stand-level and landscape-level variables in explaining the severity of RTB damage. Result showed that two stand-level factors, aspect and canopy density, were the best predictors of damage in the early stage of RTB invasion. The landscape-level factor, the proportion of Chinese pine (Pinus tabuliformis) patches, was the main predictor of damage in the middle stage of RTB invasion. The most effective spatial scale at which RTB responded to landscape pattern was 250 m. With the increasing severity of RTB damage, the factors driving RTB invasion have shifted from the stand-level to the landscape-level. This calls for an urgent consideration of multi-scale processes to address the changing disturbance regimes in ecosystem management.