Machine-Learning-Driven New Geologic Discoveries at Mars Rover Landing Sites: Jezero and NE Syrtis
This work addresses the challenge of identifying rare minerals for planetary geology and rover guidance, but it is incremental as it applies an existing method to new data for specific discoveries.
The researchers tackled the problem of detecting rare mineral phases on Mars using a hierarchical Bayesian classifier trained on spectral data, resulting in new discoveries of akaganeite, jarosite, silica, chlorite-smectite, and Al phyllosilicates at Jezero crater and NE Syrtis, which reveal a multi-stage water history and inform rover exploration.
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.