Transferability and operational reliability of a Prithvi crop classification foundation model under phenological and geographic shift across three continents
Not provided in the abstract
Abstract
The study evaluates the operational performance of the Prithvi crop classification model across different continents, highlighting significant accuracy declines due to phenological misalignment.
Reality Card
The Prithvi crop classification model's accuracy significantly declines when observation windows do not align with local crop phenology, but adjustments can recover accuracy without retraining.
Consolidating 13 classes into 10 raised the mean overall accuracy by 8.4 percentage points.
The model's performance is highly sensitive to the alignment of observation windows with local growing seasons, which may limit its reproducibility across different regions.
Paper to code
Verified implementation resources so builders can test the paper’s claims instead of stopping at the abstract.