Mineralogical Mapping of Gale Crater: Integrating MRO and Curiosity via Machine Learning clustering Algorithm
Moline, Mia Jane
Moline, Mia Jane
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Abstract
Gale Crater is a geochemically diverse impact feature located just south of the Martian equator, selected for study by the Mars Science Laboratory due to observed geomorphic features potentially resulting from lacustrine and/or fluvial processes. Absent the possibility to perform field investigations, we rely on the combination of remote observation and limited rover analyses to determine the composition of the Martian regolith. As such, we have developed a machine learning protocol which combines MRO (Mars Reconnaissance Orbiter) hyperspectral imagery with mineralogical analyses of the regolith samples acquired by the Curiosity Rover to generate mineralogical map of Gale Crater along the rover traverse. We selected 8 key spectral products based on the 554 bands acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) instruments and applied a localized clustering algorithm to determine the spectral signature of over 1,000,000 individual 18x18m pixels, corresponding to ca. 350 km2 of Martian regolith. By integrating the mineralogy of 37 samples characterized by the CheMin X-Ray diffractometer into the algorithm-produced dendrograms, we identified 3 distinct mineralogical signatures along the path corresponding to iron oxides, iron carbonates and sulfates, and igneous mineralogies. The areologic processes responsible for these distinct mineralogies are yet to be determined. Our method provides a blueprint for the integration of orbital and rover investigation in the process of exploring remote extraterrestrial objects.
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Date
1/1/2026
Student Status
Senior (Graduating in 2026)
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Poster
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Geosciences (CAS), Environmental Science (RSENR)
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College of Arts and Sciences
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Physical Science