As climate change accelerates, understanding the mechanisms of ecosystem phenology in vulnerable regions is crucial for terrestrial environments. This research systematically used remote sensing data to study the dynamic changes in vegetation phenology in the upper and middle Yellow River Basin (UMYRB), examined the effects of environmental shifts on vegetation phenology, and quantified the contributions of different driving factors. The key findings are as follows: (1) As elevation and latitude increase, the start of the growing season (SOGS) is generally delayed, particularly in the northwest and northeast, where it typically occurs between days 140 and 180. The end of the growing season (EOGS) shifts later from west to east, with 86.66 % of the area experiencing EOGS between days 260 and 300. From 1981 to 2016, approximately 61.35 % of the area exhibited a trend of advancing SOGS (-0.09 days/year), while 60.10 % of the area showed a delay in EOGS (0.08 days/year). (2) Both SOGS and EOGS exhibit significant spatial variability influenced by climatic factors, with the primary pre-season impact period ranging from 1 to 4 months. SOGS is typically negatively correlated with precipitation and temperature, whereas EOGS often shows a positive correlation with precipitation and temperature. Temperature and solar radiation are the primary climatic drivers influencing vegetation phenology in the study region. Temperature accounts for 53.57 % of SOGS and 50.73 % of EOGS, advancing them by 0.18 and 0.22 days, respectively. Solar radiation also significantly influences SOGS and EOGS, advancing them by 0.14 and 0.13 days, respectively. While the impact of diurnal temperature range (DTR) and precipitation is less pronounced, DTR is notably important in high-altitude regions. (3) Vegetation phenology varies significantly across various vegetation types. Forests usually experience an earlier SOGS and a later EOGS, while shrubs in high-altitude areas tend to have a delayed SOGS due to a greater diurnal temperature range. The growing season of grasslands and wetlands is more significantly affected by precipitation and temperature, particularly in the eastern and northern regions. Solar radiation significantly impacts the entire growing season in croplands and grasslands in the central and southern regions. Uncertainty in vegetation phenology was assessed through Bootstrap analysis, and the spatial adaptability of climate driving factors was optimized using the ridge regression model. The results indicate that despite certain sources of uncertainty, the analysis demonstrates high accuracy and stability, providing a reliable scientific basis for ecological management and restoration.