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Beyond Accuracy: Testing Geospatial AI Under Distribution Shift

A machine-learning model can achieve an impressive test score and still fail when it encounters data from a different geographic region. This is especially important in Earth observation, where satellite imagery varies with geography, season, atmospheric conditions, and sensor characteristics. In t…

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  1. 2026-10-13 19:02 · DEV Community — Machine Learning
    Beyond Accuracy: Testing Geospatial AI Under Distribution Shift

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