Machine-Learning-Driven New Geologic Discoveries at Mars Rover Landing Sites: Jezero and NE Syrtis
Murat Dundar, Bethany L. Ehlmann, Ellen K. Leask
(Submitted on 5 Sep 2019)
A hierarchical Bayesian classifier is trained at pixel scale with spectral data from the CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) imagery. Its utility in detecting rare phases is demonstrated with new geologic discoveries near the Mars-2020 rover landing site. Akaganeite is found in sediments on the Jezero crater floor and in fluvial deposits at NE Syrtis. Jarosite and silica are found on the Jezero crater floor while chlorite-smectite and Al phyllosilicates are found in the Jezero crater walls. These detections point to a multi-stage, multi-chemistry history of water in Jezero crater and the surrounding region and provide new information for guiding the Mars-2020 rover’s landed exploration. In particular, the akaganeite, silica, and jarosite in the floor deposits suggest either a later episode of salty, Fe-rich waters that post-date Jezero delta or groundwater alteration of portions of the Jezero sedimentary sequence.
Subjects: Earth and Planetary Astrophysics (astro-ph.EP); Machine Learning (cs.LG); Machine Learning (stat.ML)
Cite as: arXiv:1909.02387 [astro-ph.EP]
(or arXiv:1909.02387v1 [astro-ph.EP] for this version)
Submission history
From: Murat Dundar
[v1] Thu, 5 Sep 2019 13:22:16 UTC (738 KB)
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