A Global Perspective on Lunar Granular Flows
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Date
2022-06-28
Publication Type
Journal Article
ETH Bibliography
yes
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Abstract
Dry 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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Publication status
published
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Book title
Journal / series
Volume
49 (12)
Pages / Article No.
Publisher
American Geophysical Union
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
moon; granular flows; machine learning; erosion; mass wasting; weathering
Organisational unit
09599 - Farinotti, Daniel / Farinotti, Daniel
03465 - Löw, Simon (emeritus) / Löw, Simon (emeritus)
Notes
Funding
Related publications and datasets
Is supplemented by: https://doi.org/10.3929/ethz-b-000550395