IBM and NASA’s Marshall Space Flight Center are to collaborate in using IBM’s AI technology to discover new insights in NASA’s massive trove of Earth and geospatial science data.
The joint work will apply AI foundation model technology to NASA’s Earth-observing satellite data for the first time.
Earth observations that allow scientists to study and monitor the planet are being gathered at unprecedented rates and volume.
IBM and NASA plan to develop several new technologies to extract insights from Earth observations. One project will train an IBM geospatial intelligence foundation model on NASA’s Harmonized Landsat Sentinel-2 (HLS) dataset, a record of land cover and land use changes captured by Earth-orbiting satellites.
By analyzing petabytes of satellite data to identify changes in the geographic footprint of phenomena such as natural disasters, cyclical crop yields and wildlife habitats, this foundation model technology will help researchers provide critical analysis of the planet’s environmental systems.
“The beauty of foundation models is they can potentially be used for many downstream applications,” said Rahul Ramachandran, Senior Research Scientist at NASA’s Marshall Space Flight Center in Huntsville, Alabama.
“Applying foundation models to geospatial, event-sequence, time-series and other non-language factors within Earth science data could make enormously valuable insights and information suddenly available to a much wider group of researchers, businesses and citizens,” said Raghu Ganti, Principal Researcher, IBM.
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