Do Foundation Model Embeddings Improve Cross-Country Crop Yield Generalisation? A Leave-One-Country-Out Evaluation in Sub-Saharan Africa

This paper evaluates whether geospatial foundation model embeddings improve cross-country maize yield predictions in Sub-Saharan Africa. It finds that while within-country predictions are moderate, all feature sets, including foundation model embeddings, perform poorly under cross-country testing, indicating a significant generalisability gap.