Transferability and operational reliability of a Prithvi crop classification foundation model under phenological and geographic shift across three continents
Fine-tuned geospatial foundation models (GeoFMs) pretrained on large satellite archives have been shown to improve crop classification accuracy and geographic transferability. However, their operational performance beyond the training distribution remains poorly characterized. We evaluated the out-of-distribution perfo...