A deep-learning-based experiment for benchmarking the performance of global terrestrial vegetation phenology models

#The code enclosed in this repository includes the novel model stracture associated with manuscript, you can regenerate the training model according to different input data or researches.

#The model file includes the training models associated with manuscript, you can directly use them to predict regional/global vegetation phenology metrics with multiyear.

#The output file includes predicted results on a pixel level (i.e. modeling results of test data (2000 pixels)) associated with our manusctipt.

#The input file includes the demo of input data (train/test data) which offer a reference for the format style. (PS: the memories of input data on regional or global scale are too big to upload, and the data preprocessing detials can be found in manusctipt)