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Monitoring soil erosion risk is an important part of soil conservation practices. It is usually estimated with the Universal Soil Loss Equation, and the C-factor (vegetation cover) is derived from optical satellite images. However, because of lack of data and resources, or in rapid assessments, C-factor is estimated using one or a few satellite observations, despite being temporally variable according to plants' phenology. The aim of this work was to study the effect of seasonality in estimating C-factor. This was achieved by demonstrating first that there is a difference when estimating soil erosion with Universal Soil Loss Equation at variable time steps in a year, namely once, seasonally and monthly. Using Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index images and statistical analysis at subcatchment scale, it was shown that there is a significant difference when estimating mean annual soil loss with the aforementioned temporal options. The highest differences were observed between monthly and annual time steps. The second objective was to identify which is the optimum time to estimate C-factor in a year. The results show that November, October and March are the optimum months for single image estimation of annual soil erosion. Statistical analysis with a random point dataset suggested that the spatial variability of the results was influenced by the land cover type, especially in areas with variable leaf cover where a single date estimation of C-factor was not representative of the whole year, such as annual crops and deciduous trees. Copyright © 2013 John Wiley & Sons, Ltd.