Deriving Surface Ages on Mars using Automated Crater Counting
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)...
| Main Authors: | , , , , , , , , , |
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| Format: | Journal Article |
| Language: | English |
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AMER GEOPHYSICAL UNION
2020
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| Subjects: | |
| Online Access: | http://purl.org/au-research/grants/arc/DP170102972 http://hdl.handle.net/20.500.11937/90815 |
| _version_ | 1848765436148056064 |
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| author | Benedix, Gretchen Lagain, Anthony Chai, Kevin Meka, S. Anderson, S. Norman, C. Bland, Phil Paxman, Jonathan Towner, Martin Tan, Tele |
| author_facet | Benedix, Gretchen Lagain, Anthony Chai, Kevin Meka, S. Anderson, S. Norman, C. Bland, Phil Paxman, Jonathan Towner, Martin Tan, Tele |
| author_sort | Benedix, Gretchen |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T11:35:13Z |
| format | Journal Article |
| id | curtin-20.500.11937-90815 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:35:13Z |
| publishDate | 2020 |
| publisher | AMER GEOPHYSICAL UNION |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-908152023-04-20T05:35:18Z Deriving Surface Ages on Mars using Automated Crater Counting Benedix, Gretchen Lagain, Anthony Chai, Kevin Meka, S. Anderson, S. Norman, C. Bland, Phil Paxman, Jonathan Towner, Martin Tan, Tele Science & Technology Physical Sciences Astronomy & Astrophysics Geosciences, Multidisciplinary Geology CHRONOLOGY 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. 2020 Journal Article http://hdl.handle.net/20.500.11937/90815 10.1029/2019EA001005 English http://purl.org/au-research/grants/arc/DP170102972 http://creativecommons.org/licenses/by-nc/4.0/ AMER GEOPHYSICAL UNION fulltext |
| spellingShingle | Science & Technology Physical Sciences Astronomy & Astrophysics Geosciences, Multidisciplinary Geology CHRONOLOGY Benedix, Gretchen Lagain, Anthony Chai, Kevin Meka, S. Anderson, S. Norman, C. Bland, Phil Paxman, Jonathan Towner, Martin Tan, Tele Deriving Surface Ages on Mars using Automated Crater Counting |
| title | Deriving Surface Ages on Mars using Automated Crater Counting |
| title_full | Deriving Surface Ages on Mars using Automated Crater Counting |
| title_fullStr | Deriving Surface Ages on Mars using Automated Crater Counting |
| title_full_unstemmed | Deriving Surface Ages on Mars using Automated Crater Counting |
| title_short | Deriving Surface Ages on Mars using Automated Crater Counting |
| title_sort | deriving surface ages on mars using automated crater counting |
| topic | Science & Technology Physical Sciences Astronomy & Astrophysics Geosciences, Multidisciplinary Geology CHRONOLOGY |
| url | http://purl.org/au-research/grants/arc/DP170102972 http://hdl.handle.net/20.500.11937/90815 |