Soil erosion is a global ecological problem. Its accurate monitoring is necessary for safeguarding regional ecological safety and assessing ecological protection effectiveness. Accurately obtaining high temporal-resolution vegetation coverage information and matching it with precipitation dynamics plays a critical role in accurate soil erosion monitoring. However, limited by satellite sensors, large-area remote sensing data with both high temporal-resolution and high spatial-resolution cannot be acquired at the same time. To solve this problem, this study proposes an approach to acquire green vegetation coverage with high spatial-temporal resolution (semi-month scale, 2 m spatial resolution) based on the fusion of multi-source remote sensing data. Then, the temporal-series green vegetation coverage dataset is utilized in Chinese Soil Loss Equation (CSLE) through matching with the semi-month precipitation factor to evaluate its effectiveness. Rainfall and vegetation coverage factors were highly variable within a year. The average value of the semi-month rainfall was 43.32 mm, and the coefficient of variation was 150%. The mean green vegetation coverage was 54.74%, and the coefficient of variation was 54.74%. The fusion approach of high spatial and temporal resolution data is feasible to obtain vegetation dynamics at high spatial resolution, which provides an effective means for soil erosion monitoring. Precipitation and vegetation factors are highly dynamic during the year, and the range and intensity of soil erosion were highly correlated with these dynamic factors. CSLE using vegetation and precipitation factors with high temporal and spatial resolution can better reflect the intensity of soil erosion in the study area. The coefficient of determination between CSLE estimations and field observations of soil erosion can reach 0.88, whereas it is only 0.097 between CSLE estimations using static vegetation coverage and field observations. Our results suggest that incorporating high temporal and spatial resolution green vegetation coverage could improve soil erosion monitoring accuracy.