Cryogeomorphic characterization of shadowed regions in the Artemis exploration zone

Abstract

In the next couple of years a large number of robotic missions and payloads will be delivered to the Moon, ultimately culminating in crewed missions. Those missions aim at characterizing lunar polar volatiles, which are concentrated in regions of permanent shadow. However, the small-scale surface properties of shadowed regions remain largely unknown. The lack of knowledge poses a potential risk to future ground-based missions that seek to enter shadowed regions. Here, we use a machine learning-driven algorithm to remove noise from previously largely unusable satellite images of shadowed regions. We use those de-noised images to study the surface properties of 44 small, shadowed regions in the Artemis exploration zone close to the lunar south pole for the first time, identifying potential hazards, and recommending sites for future exploration missions. We freely release our images along with a detailed catalog of the shadowed regions studied.