Vegetation phenology is an important biological indicator for monitoring terrestrial ecosystems and global climate change. The monitoring of land surface phenology based on classical remote sensing vegetation indices is more challenging in terms of accurate analysis of different vegetation types. Solar-Induced Chlorophyll Fluorescence （SIF） is more sensitive to the seasonal dynamics of vegetation and can more accurately portray the interannual variability of vegetation. Based on the 2001~2020 GOSIF dataset， this study extracted the vegetation phenology parameters in Northeast China by D-L fitting function and dynamic threshold method， combined with unitary linear regression analysis， stability and sustainability analysis， this study analyzed the spatiotemporal evolution characteristics， stability and sustainability of vegetation phenology in Northeast China from 2001 to 2020 at multiple spatiotemporal scales， and explored the response mechanism of vegetation phenology to climate change. The results showed that SOS， EOS， LOS， and POP showed advanced， delayed， prolonged and advanced， respectively. The trend of SOS advance and EOS delay in grassland was significant， and EOS of coniferous forests was advanced. The advance of SOS and the delay of EOS led to the prolongation of LOS. Except for coniferous forest， all vegetation types showed an extended trend of LOS. All vegetation types POP showed an advance trend， except for grassland and steppe. The changes of SOS， EOS， LOS and POP were relatively stable in the past 20 years， and the coefficients of variation were all less than 0.1. The H values of SOS， EOS， LOS and POP in most regions ranged between 0.35 and 0.5， indicating that the trend was opposite to the past and would show a slight trend of delay， advance， shortening and delay. Overall， the influence mechanism of temperature and precipitation was opposite on vegetation phenology， that is， higher temperature （increased precipitation） led to advance （delay） of SOS and POP， delay （advance） of EOS， and lengthen （shorten） of LOS. There was a negative correlation between relative humidity and vegetation phenological parameters. The results of this study help to understand the spatiotemporal pattern changes of photosynthesis in vegetation and the response mechanism to climate change， and also provide reference for the assessment and management of ecological environment in Northeast China.