Multi-Year Geospatial Reasoning using Interannually-Consistent Historical Predictions as a Free Input Modality
Machine learning, and deep networks in particular, are increasingly used to derive higher-level Earth observation (EO) products such as annual land-cover and crop-type maps. Many are generated operationally: each year a new acquisition is processed, typically with the same model, extending a multi-year archive. In the...