Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC and Kaguya TC Images

Dating young lunar surfaces, such as impact ejecta blankets and terrains associated with recent volcanic activities, provides critical information on the recent events that shaped the surface of the Moon. Model age derivation of young or small areas using a crater chronology is typically achieved th...

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Main Authors: Fairweather, John, Lagain, Anthony, Servis, Konstantinos, Benedix, Gretchen
Format: Journal Article
Published: 2023
Online Access:http://hdl.handle.net/20.500.11937/94367
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author Fairweather, John
Lagain, Anthony
Servis, Konstantinos
Benedix, Gretchen
author_facet Fairweather, John
Lagain, Anthony
Servis, Konstantinos
Benedix, Gretchen
author_sort Fairweather, John
building Curtin Institutional Repository
collection Online Access
description Dating young lunar surfaces, such as impact ejecta blankets and terrains associated with recent volcanic activities, provides critical information on the recent events that shaped the surface of the Moon. Model age derivation of young or small areas using a crater chronology is typically achieved through manual counting, which requires a lot of small impact craters to be tediously mapped. In this study, we present the use of a Crater Detection Algorithm (CDA) to extract crater populations on Lunar Reconnaissance Orbiter—Narrow Angle Camera (LRO-NAC) and Kaguya Terrain Camera images. We applied our algorithm to images covering the ejecta blankets of four Copernican impact craters and across four young mare terrains, where manually derived model ages were already published. Across the eight areas, 10 model ages were derived. We assessed the reproducibility of our model using two populations for each site: (a) an unprocessed population and (b) a population adjusted to remove contaminations of secondary and buried craters. The results showed that unprocessed detections led to overestimating crater densities by 12%–48%, but “adjusted” populations produced consistent results within <20% of published values in 80% of cases. Regarding the discrepancies observed, we found no significant error in our detections that could explain the differences with crater densities manually measured. With careful processing, we conclude that a CDA can be used to determine model ages and crater densities for the Moon. We also emphasize that automated crater datasets need to be processed, interpreted and used carefully, in unity with geologic reasoning. The presented approach can offer a consistent and reproducible way to derive model ages.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-943672024-04-04T07:31:40Z Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC and Kaguya TC Images Fairweather, John Lagain, Anthony Servis, Konstantinos Benedix, Gretchen Dating young lunar surfaces, such as impact ejecta blankets and terrains associated with recent volcanic activities, provides critical information on the recent events that shaped the surface of the Moon. Model age derivation of young or small areas using a crater chronology is typically achieved through manual counting, which requires a lot of small impact craters to be tediously mapped. In this study, we present the use of a Crater Detection Algorithm (CDA) to extract crater populations on Lunar Reconnaissance Orbiter—Narrow Angle Camera (LRO-NAC) and Kaguya Terrain Camera images. We applied our algorithm to images covering the ejecta blankets of four Copernican impact craters and across four young mare terrains, where manually derived model ages were already published. Across the eight areas, 10 model ages were derived. We assessed the reproducibility of our model using two populations for each site: (a) an unprocessed population and (b) a population adjusted to remove contaminations of secondary and buried craters. The results showed that unprocessed detections led to overestimating crater densities by 12%–48%, but “adjusted” populations produced consistent results within <20% of published values in 80% of cases. Regarding the discrepancies observed, we found no significant error in our detections that could explain the differences with crater densities manually measured. With careful processing, we conclude that a CDA can be used to determine model ages and crater densities for the Moon. We also emphasize that automated crater datasets need to be processed, interpreted and used carefully, in unity with geologic reasoning. The presented approach can offer a consistent and reproducible way to derive model ages. 2023 Journal Article http://hdl.handle.net/20.500.11937/94367 10.1029/2023EA002865 http://creativecommons.org/licenses/by-nc-nd/4.0/ fulltext
spellingShingle Fairweather, John
Lagain, Anthony
Servis, Konstantinos
Benedix, Gretchen
Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC and Kaguya TC Images
title Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC and Kaguya TC Images
title_full Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC and Kaguya TC Images
title_fullStr Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC and Kaguya TC Images
title_full_unstemmed Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC and Kaguya TC Images
title_short Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC and Kaguya TC Images
title_sort lunar surface model age derivation: comparisons between automatic and human crater counting using lro-nac and kaguya tc images
url http://hdl.handle.net/20.500.11937/94367