A new AI can finally illuminate the Moon’s darkest places

So far, the team has investigated more than a half-dozen potential Artemis landing sites. The findings of the study could have immediate implications for future missions, such as Intuitive Machines Mission 2, which will be conducted commercially by a start-up.

Before the astronauts arrive on the Moon in the spring of 2023, this robotic mission will collect and analyze the first soil samples from the Moon’s shadowed south pole.

“These new research findings will allow for precise planning of routes into and through the permanently shadowed regions, which will greatly reduce the risks to which Artemis astronauts and robotic explorers are exposed,” says ETH Zürich.

Study abstract

The Artemis program will send a crew to explore the south polar region of the Moon, preceded by and integrated with robotic missions. One of the main scientific goals of future exploration is the characterization of polar volatiles, which are concentrated in and near regions of permanent shadow. The meter-scale cryogeomorphology of shadowed regions remains unknown, posing a potential risk to missions that plan to traverse or land in them. Here, we deploy a physics-based, deep learning-driven post-processing tool to produce high-signal and high-resolution Lunar Reconnaissance Orbiter Narrow Angle Camera images of 44 shadowed regions larger than ∼40 m across in the Artemis exploration zone around potential landing sites 001 and 004. We use these images to map previously unknown, shadowed meter-scale (cryo)geomorphic features, assign relative shadowed region ages, and recommend promising sites for future exploration. We freely release our data and a detailed catalog of all shadowed regions studied.

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