Geoscience Foundation Models
Link to section 'What is Geoscience Foundation Models' of 'Geoscience Foundation Models' What is Geoscience Foundation Models
Geoscience foundation models (GFMs) are large-scale, general-purpose artificial intelligence models pre-trained on vast, multi-modal datasets related to Earth systems. They learn a broad base of knowledge about the planet's dynamics and can be adapted (fine-tuned) for a wide range of downstream geoscience tasks, such as weather forecasting, climate modeling, and remote sensing applications.
Link to section 'Deployed GFMs' of 'Geoscience Foundation Models' Deployed GFMs
Prithvi-EO-2.0
Prithvi-EO-2.0 is the second generation EO foundation model jointly developed by IBM, NASA, and Jülich Supercomputing Centre.
The models were pre-trained at the Jülich Supercomputing Centre with NASA's HLS V2 product (30m granularity) using 4.2M samples with six bands in the following order: Blue, Green, Red, Narrow NIR, SWIR, SWIR 2.
They are four models (300M, 300M-TL, 600M, and 600M-TL) which varies on the number of parameters and with/without temporal and location embeddings.
Check their Model Card here