Data and code for pre-processed Sentinel-2 time series
You can find the numpy files corresponding to the time series here.
Associated papers :
Frion, A., Drumetz, L., Tochon, G., Dalla Mura, M. & Aïssa El Bey, A. (2023). Learning Sentinel-2 reflectance dynamics for data-driven assimilation and forecasting. EUSIPCO 2023. arXiv:2305.03743.
Frion, A., Drumetz, L., Dalla Mura, M., Tochon, G., & Aïssa El Bey, A. (2023). Neural Koopman prior for data assimilation. arXiv preprint arXiv:2309.05317.
File "KoopmanAE.py" contains the implementation of the Koopman auto-encoder model discussed in the papers.
Files "Fontainebleau_trained_model.pt" and "Fontainebleau_trained_K.pt" contain weights for the model which gave Sentinel-2 results in the papers.
The notebook "Fontainebleau_forecasting.ipynb" shows how the Fontainebleau data can be loaded and forecasted in various ways by our trained model.