Deriving Surface Ages on Mars Using Automated Crater Counting Article Swipe
G. K. Benedix
,
Anthony Lagain
,
Kevin Chai
,
Shiv Meka
,
Seamus Anderson
,
C. Norman
,
P. A. Bland
,
Jonathan Paxman
,
M. C. Towner
,
Tele Tan
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1029/2019ea001005
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1029/2019ea001005
Impact craters on solar system bodies are used to determine the relative ages of surfaces. The smaller the limiting primary crater size, the higher the spatial resolution in surface/resurfacing age dating. A manually counted database (Robbins & Hynek, 2012, https://doi.org/10.1029/2011JE003966 ) of >384,000 craters on Mars >1 km in diameter exists. But because crater size scales as a power law, the number of impact craters in the size range 10 m to 1 km is in the tens of millions, a number making precise analysis of local variations of age, over an entire surface, impossible to perform by manual counting. To decode this crater size population at a planetary scale, we developed an automated Crater Detection Algorithm based on the You Only Look Once v3 object detection system. The algorithm was trained by annotating images of the controlled Thermal Emission Imaging System daytime infrared data set. This training data set contains 7,048 craters that the algorithm used as a learning benchmark. The results were validated against the manually counted database as the ground truth data set. We applied our algorithm to the Thermal Emission Imaging System global mosaic between ±65° of latitude, returning a true positive detection rate of 91% and a diameter estimation error (~15%) consistent with typical manual count variation. Importantly, although a number of automated crater counting algorithms have been published, for the first time we demonstrate that automatic counting can be routinely used to derive robust surface ages.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1029/2019ea001005
- OA Status
- gold
- Cited By
- 39
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3008411065
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3008411065Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1029/2019ea001005Digital Object Identifier
- Title
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Deriving Surface Ages on Mars Using Automated Crater CountingWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-02-20Full publication date if available
- Authors
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G. K. Benedix, Anthony Lagain, Kevin Chai, Shiv Meka, Seamus Anderson, C. Norman, P. A. Bland, Jonathan Paxman, M. C. Towner, Tele TanList of authors in order
- Landing page
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https://doi.org/10.1029/2019ea001005Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1029/2019ea001005Direct OA link when available
- Concepts
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Impact crater, Mars Exploration Program, Geology, Remote sensing, Population, Ground truth, Data set, Surface (topology), Algorithm, Computer science, Artificial intelligence, Geometry, Mathematics, Astrobiology, Physics, Sociology, DemographyTop concepts (fields/topics) attached by OpenAlex
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39Total citation count in OpenAlex
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2025: 11, 2024: 5, 2023: 9, 2022: 6, 2021: 7Per-year citation counts (last 5 years)
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44Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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