Our Embedding Fields Model is a geospatial foundation model that is trained on multi-source Earth Observation data streams using self-supervised representation learning techniques. This model generates Embedding Fields, which we surface as a dataset by running the model at scale that can be used to quickly develop remote sensing classifications, regressions, and other analyses
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