Abstract
AbstractDry granular flows are ubiquitous, yet poorly understood mass wasting features on the Moon. Above all, their global distribution, relation to the physical environment, and drivers are poorly understood. Here, we build and deploy a convolutional neural network and map 28,101 flow features between 60°N and S by scanning through ∼150,000 Lunar Reconnaissance Orbiter images. We observe that flows are heterogeneously distributed over the Moon, where all major hotspots are located in craters and almost all hotspots are located in the nearside maria. We further observe that younger surfaces feature higher flow feature densities, while pre‐Nectarian terranes can still host flows, remaining subject to active erosion billions of years after their formation. Our observations suggest that impacts at various scales have been—and likely still are—acting as the main, global‐scale, long‐ and short‐term driver of flow occurrence, strongly influenced by the properties of the target rock material.
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