Detecting year-to-year variability of the timing of the start of the growing season (SGS) and the end of the growing season (EGS) is an important task in accurately evaluating ecosystem functions and services under climate change in vulnerable ecosystems in Siberia. We constructed a degree-day model for estimating the SGS and EGS dates at a deciduous coniferous forest site in Siberia, based on the relationship between daily phenology images and daily mean air temperature between 2013 and 2017. We tested the model by applying it to another similar site in Siberia. The model successfully estimated the SGS and EGS dates from the cumulative effective temperature, derived from daily mean air temperatures exceeding a best-fit threshold value of 2 degrees C (root mean square error: RMSE = 1.00) and falling below a best-fit threshold value of 1 degrees C, 0 degrees C or -1 degrees C (RMSE = 2.29), respectively. The modelled SGS and EGS dates closely matched the observed dates of leaf flush and leaf fall, respectively, in the larch overstory.