An AI To Identify The Environment A Grain Of Sand Came From

If you were given a bucket of sand and asked to determine where it came from, you’d probably have a hard time guessing if it was from a beach, a riverbank, the playground down the street, or a Saharan sand dune.

There are experts who can make a guess at that sort of ID, using a categorization process that takes skill, a scanning electron microscope, and hours of time. Now, however, researchers report in the Proceedings of the National Academy of Sciences that they’ve developed an AI model that can quickly judge whether a sample of sand came from a beach, a river, a glacial deposit, or a wind-blown dune.

That type of identification isn’t just of interest to geologists. Sand is one of the world’s most in-demand resources, second only to water in use. And different applications need different types of sand—for instance, making concrete and mortar requires angular sand for good adhesion and stability. These kinds of needs have given rise to illicit sand mining, sand theft, and sand smuggling. A way of rapidly identifying the origins of a sample of sand could be useful to investigators, or to companies seeking to ensure sustainability goals.

Michael Hasson, a PhD candidate in Stanford’s Department of Earth and Planetary Sciences, joins SciFri’s Charles Bergquist to discuss the new SandAI, and the challenges of tracking grains of sand.

Further Reading

• Learn more about sand-related crimes from a 2018 SciFri episode.

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