The scientists used data from 7,895 previously identified craters and 1,411 dated craters and were able to apply machine learning to train a deep neural network. Using information from China’s first and second lunar orbits – Chang’e 1 and Chang’e 2 – the network identified 109,956 new craters. The two unmanned spacecraft were launched in 2007 and 2010 respectively.
Impact craters (are) the most diagnostic features of the lunar surface. That is in stark contrast to the surface of the Earth. It is very difficult to trace the history of the Earth of the impact of asteroids and comets over the past 4 billion years. , ‘said study author Chen Yang, from the College of Earth Sciences at Jilin University and the Key Laboratory of Lunar and Deep Space Exploration at the Chinese Academy of Sciences.
“The Earth and the Moon have been hit by the same impact craters over time, but large lunar craters have undergone limited deterioration over billions of years. Therefore, impact craters on the Moon can track Earth’s evolution,” she said via email. .
The craters on the moon lack water, an atmosphere and tectonic plate activity – three forces that erode Earth’s surface, meaning that all but the most recent meteor impacts are not visible.
This latest study is not the first to use machine learning to detect craters of the moon, said Mohamad Ali-Dib of the Institute for Research on Exoplanets at the University of Montreal.
“Machine learning can be used to detect craters on the Moon,” he said via email. Craters are ‘a window into the dynamic history of the solar system.