Side view of the Moltke crater taken from Apollo 10. Credit: Public Domain
A team of researchers at various institutions in China, one from Italy and one from Iceland, used an artificial intelligence machine learning application to count and record the location of more than 100,000 craters on the moon. In their paper published in the journal Nature communication, the group describes programming their system to spot craters by training it with data collected from Chinese lunar orbits.
Previous work identifying and mapping craters on the moon has usually been a slow process – it was generally done by hand, with researchers studying photos and transferring those observations to maps or lunar globes. In this new effort, the researchers have found a way to dramatically speed up the process by teaching a computer to identify craters and then count them.
Teaching a computer to recognize craters on the moon was a difficult process because of the many shapes that craters can take. Not all are round and are of different ages, which means that the defining features have been eroded for a long time. Scientists would want to map all the craters on the moon and date them all – that could be a unique way to study the history of the solar system.
The new approach of the team working in China involved training a machine learning application on the basics of craters. It was then trained to see craters with a broader perspective with data from China’s Chang’e-1 and Chang’e-2 lunar orbits. Once the system learned what to look for, the researchers used it to analyze data from the Chang’e 5 lander, which was part of the Chinese mission that retrieved rocks from the lunar surface. The AI app used that data to identify and count craters in the middle and low latitudes of the moon. The new system had 109,956 craters – many more than have ever been counted on the Moon. It also tracked the location of each of the craters it found, placing each in a predetermined geologic time period based on how much the crater had eroded.
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Chen Yang et al. Identification of the lunar impact crater and age estimation with Chang’E data through deep learning and transfer, Nature Communications (2020). DOI: 10.1038 / s41467-020-20215-y
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Quote: Using AI to Count and Map Craters on the Moon (2020, December 23) Retrieved December 24, 2020 from https://phys.org/news/2020-12-ai-craters-moon.html
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