Crew members aboard the International Space Station collect imagery during studies like Crew Earth Observations and Hurricane-Visual, pointing cameras at interesting features on our planet. Once a picture is taken, it often needs further processing to enhance its scientific usefulness. Historically, this step has been a manual task, but now researchers are assigning it to artificial intelligence (AI).
The Earth Science and Remote Sensing Unit at NASA’s Johnson Space Center in Houston, Texas, is using machine learning to sort through and identify photos taken from the orbital laboratory, making them more searchable and useful to scientists. The Gateway to Astronaut Photography of Earth service contains nearly 4 million astronaut-captured images. Using AI, researchers have categorized over 2 million photos of Earth’s geographic features, 250,000 images of auroras, 37,000 lightning photos, and 18,000 images of 64 different cities around the world.
While the technology to capture imagery of Earth from satellites has existed since the 1960s, use of AI in image processing is a recent development. After training the AI model on satellite imagery of Earth, NASA scientists began using it to process significant quantities of imagery at a rate far faster than any human cataloger.