The researchers developed new ways to make deep learning models better at predicting changes in land cover. They focused on areas that had changed recently and gave them more importance in the model. By doing this, they were able to improve the accuracy of their predictions for multiple years. This approach helped reduce errors and make the forecasts more reliable. The study shows that these new methods can help address the challenges of using deep learning for predicting changes in land cover over time.