Mapping Planetary Surface Ages at Ultimate Resolutions with Machine Learning: The Moon
Access Status
Open access
Date
2023Supervisor
Gretchen Benedix
Anthony Lagain
Type
Thesis
Award
PhD
Metadata
Show full item recordFaculty
Science and Engineering
School
School of Earth and Planetary Sciences
Collection
Abstract
The density of impact craters upon a terrestrial surface can give an accurate estimate of the surface's formation age. The Moon has hundreds of millions of impact craters scattered across its surface. Through the power of machine learning, we can automatically count those craters to date any surface on the Moon!
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