NEW DELHI, Nov 25: The American space research agency the National Aeronautics and Space Administration (NASA) has started using supercomputers and Artificial Intelligence (AI) for the first time to count trees from space.
By using this technique, the NASA would also know how much carbon the Earth can store and how it changes over time without requiring counting a bewildering number of trees and tracking their growth over time.
Scientists from NASA’s Goddard Space Flight center in Maryland recently partnered with an international team of researchers to map the trees using high-resolution satellite images—more than 1.8 billion trees that are found outside of forests, over a swath of more than a half million square miles.
NASA has started to use the fastest supercomputer in the world and it is best enough to perform deep learning analysis on terrain images from across large sections of West Africa. NASA’s scientists have found that now NASA can count the trees and be able to assess the carbon storage potential of those trees at the same time. NASA’s satellites were not able to count the trees from the space before.
Much of the world’s effort to assess large numbers of trees has focused on well-forested regions. This is why the NASA team sought to focus on isolated trees in drylands and semi-arid regions in West Africa—for a fuller picture.
Lead author of this project – Martin Brandt said “These dry areas are white on maps—they are basically masked out because normal satellites just don’t see the trees. They see a forest, but if the tree is isolated, they can’t see it. Now we’re on the way to filling these white spots on the maps. And that’s quite exciting.”
Martin Brandt is also professor of geography at the University of Copenhagen.
To train the machine-learning algorithms Brandt marked nearly 90,000 trees spanning different terrains personally—giving the software different shapes and shadows to learn the difference.
With the right training in place, a job that may have taken trained eyes several years to complete took only a few weeks for artificial intelligence.
In the future, assessments of this kind will more effectively track deforestation around the world for conservationists. The overhead data from one year will also be compared to later years for scientists to assess whether conservation efforts are working or not.
Accurate, automated tree counting should also further the ability of landowners to monetize unused space they may have for planting new trees—to quantify how much carbon they are storing for carbon credits.
Ultimately, improving the ability of researchers to spot trees where they couldn’t before with satellite images and to gauge the carbon storage of those trees—will eventually enable climate scientists to make global measurements of carbon storage on land.
(Vinayak Barot)
