IBM, NASA release actual open source AI model – for grokking sat images
IBM and NASA have put together and released Prithvi: an open source foundation AI model that may help scientists and other folks analyze satellite imagery.
The vision transformer model, released under an Apache 2 license, is relatively small at 100 million parameters, and was trained on a year's worth of images collected by the US space boffins' Harmonized Landsat Sentinel-2 program. As well as the main model, three variants of Prithvi are available, fine-tuned for identifying flooding; wildfire burn scars; and crops and other land use.
Essentially, it works like this: you feed one of the models an overhead satellite photo, and it labels areas in the snap it understands. For example, the variant fine-tuned for crops can point out where there's probably water, forests, corn fields, cotton fields, developed land, wetlands, and so on.This collection, we imagine, would be useful for, say, automating the study of changes to land over time – such as tracking erosion from flooding, or how drought and wildfires have hit a region.
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