Machine-Learning-Driven New Geologic Discoveries at Mars Rover Landing Sites: Jezero and NE Syrtis

TL;DR

This paper presents a hierarchical Bayesian classifier trained on spectral data to detect rare minerals on Mars, leading to new geologic discoveries that inform the Mars-2020 rover's exploration strategy.

Contribution

It introduces a novel pixel-scale spectral classification method that uncovers previously unknown mineral deposits on Mars, revealing complex water history.

Findings

Detection of akaganeite, jarosite, and silica in Jezero and NE Syrtis

Evidence of multi-stage water history in Jezero crater

Guidance for Mars-2020 rover exploration based on mineral discoveries

Abstract

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.