Researchers use AI to measure snow depth with images from space
Published: Thursday, Dec 14th 2023, 11:30
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Snow data from space: with the help of artificial intelligence (AI), researchers can read snow depths in Switzerland from satellite images. This method is more accurate and faster than previous methods, as announced by ETH Zurich on Thursday.
According to the Swiss Federal Institute of Technology in Zurich (ETH Zurich), data on snow depth is an important basis for winter tourism, hydropower and for assessing the risk of avalanches caused by winter sports enthusiasts.
Until now, snow monitoring in Switzerland has mainly been based on data from measuring stations, ETH Zurich said in the press release. As there are only around 400 stations for the whole of Switzerland, the snow data for many locations is rather inaccurate.
AI trained with data
The researchers from ETH Zurich and the Swiss company Exolabs used images from the Sentinel-2 satellites of the European Space Agency (Esa) for the measurements based on satellite images. Every five days, these satellites record images for every location on Earth. In addition to the satellite images, the researchers therefore fed the AI with comprehensive terrain data for Switzerland.
Using this satellite and terrain data, they trained the AI to derive the snow depth for any given point. To do this, they used a method called supervised learning. They had the system estimate the snow depths and compared the results with real snow measurements. "At each grid point, we determined how far off the mark the AI was with its estimate and gradually adjusted the system so that the errors became smaller," explains Konrad Schindler in the ETH press release.
"New standard for snow depth measurement"
"While the best existing snow maps in Switzerland have an effective resolution of around 250 by 250 meters, you can zoom in on our maps down to 10 by 10 meters to see the snow depth," says Schindler. "We believe that we are setting a new standard for snow depth measurement in Switzerland."
In addition to satellite images from Sentinel-2 satellites, the researchers also use images from other satellite missions, which are less spatially accurate but provide daily images.
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