Martian Impact Crater Database Down to 100M: a Tool for Surface Age Dating
Abstract
Impact craters on rocky and icy bodies of the solar system are widely used to determine the ages of planetary surfaces. Absolute dating of meteorites or in-situ geochronology provide a few essential reference points, but these techniques rare not yet applicable at the planetary scale. Therefore, the impact crater counting techniques will remain for several decades the major tool of "celestial geologists" to decipher the history of planetary surfaces. This approach requires a tedious mapping and morphological inspection of a large number of circular features to distinguish true and primary impact craters from other surface features and secondary impact craters ; in particular on Mars whose the surface exhibit a large variety of pseudo-circular features. To access to a smaller size range of craters at a planetary scale, the automation of the counting process is essential.
We created a Crater Detection Algorithm (CDA) by using a few thousands of impact craters ≥1km contained in the [1] database as a training dataset superposed on the THEMIS mosaic (100m/px) [2,3,4]. Encouraged by the quality of the detection, we applied the algorithm on the Murray Lab global CTX mosaic [5] over a latitudinal band between 45 degrees of North and South [6]. Around 17 M of detection have been compiled on this run from 50m to 60km in diameter, performed on only two months. A good consistency between this database and the Robbins' one between 1 and 10 km is observed. Above 1km, the completeness and the accuracy of the detection have been estimated by the comparison of the CSFD and the age inferred from them from manual counting already published in the aim to derive a surface model age at different spatial scales [6]. The final database contains nevertheless misidentified structures and secondary impact craters. Examples of some dating will be presented as well as a technique to clean the database from secondaries. This version of the database is ready to be shared by simple asking.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.P43E3514L
- Keywords:
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- 1942 Machine learning;
- INFORMATICS;
- 6094 Instruments and techniques;
- PLANETARY SCIENCES: COMETS AND SMALL BODIES;
- 5794 Instruments and techniques;
- PLANETARY SCIENCES: FLUID PLANETS;
- 5494 Instruments and techniques;
- PLANETARY SCIENCES: SOLID SURFACE PLANETS