Poyang Lake Wetland is an internationally important lake wetland and is of great significance to the healthy and green development of the entire Yangtze River Basin. However， in recent years， the impact of human activities and global climate change has caused rapid changes in the community structure and spatial distribution of Poyang Lake wetland vegetation， and the ecological functions are at risk of degradation. Therefore， timely and accurate knowledge of the spatial distribution of wetland vegetation communities is of great significance for the protection and restoration of Poyang Lake wetland. In view of the characteristics of seasonal changes in the Poyang Lake Wetland， this study uses the 2019 time series Sentinel-2 images as the data source and proposes a random forest classification method that combines statistical and temporal features based on the GEE platform to classify the Poyang Lake National Reserve Wetland. Typical vegetation communities were extracted. The research results show that： （1） Poyang Lake wetland vegetation is affected by periodic flooding and differences in growth phenology， and the differences in vegetation communities are more obvious in autumn and winter. （2） Sentinel-2 images based on time series can better identify vegetation communities， tidal flats and water bodies， among which time features contribute greatly to the identification of vegetation communities. （3） The overall identification accuracy of wetland vegetation communities based on statistical-temporal features combined with random forest classification algorithm reaches 86.21%， and the Kappa coefficient is 0.83. The method proposed in this article can timely and accurately extract the spatial distribution of wetland vegetation communities， and has good application prospects in wetland research. It can provide scientific acquisition and management of wetland resources in Poyang Lake Wetland National Nature Reserve， evaluation of ecological environment， and Repair provides important data support.