Dissertation/Thesis Abstract

The author has requested that access to this graduate work be delayed until 2021-04-18. After this date, this graduate work will be available on an open access basis.
Quantifying Lithochemical Diversity of Martian Materials Using Hierarchical Clustering and a Similarity Index for Classification
by Bouchard, Michael Conner, Ph.D., Washington University in St. Louis, 2019, 198; 13861370
Abstract (Summary)

We are currently living in the golden age of robotic exploration of Mars, with a continued robotic presence there since 1997. Next to Earth, Mars is the planet about which we have gathered the most geologic information. Unlike Earth, Mars does not appear to have plate tectonics, and the planet’s primary and secondary crust is dominated by basalts. Understanding the compositional diversity of the materials that make up the martian crust will give us a better insight into the geologic processes that formed the planet and its subsequent evolution. One large and growing source of martian surface compositions is the Alpha Particle X-Ray Spectrometer, an in-situ instrument that has been carried on three Mars rovers, Spirit, Opportunity, and Curiosity. This instrument has measured elemental compositions for martian rocks and soils across three separate terrains on Mars. This dissertation seeks to characterize the diversity and quantify the similarities of compositions of rocks and rock suites as reported in the APXS datasets as well as published compositions of the martian meteorites. The careful application of multivariate statistics allows for a rigorous assessment of these diverse compositions to explore possible compositional groupings and primary and secondary relationships. To this end, a statistical grouping model comprised of hierarchical clustering and a similarity index, informed by image analysis and ground-truth in-situ Mars exploration, is applied to the data.

Verification of models is essential as statistics can provide spurious results. In Chapter 2, I apply the statistical grouping model to a set of well characterized Opportunity APXS data. These datasets have significant covariant information, such as geographic relationships, rock textures, geologic context, Pancam spectra, and established working hypotheses about local geology. Chapter 2 also explores how the statistical model works relative to compositions of rocks that have undergone different surface treatment by the rock abrasion tool (RAT) on Opportunity. I also test the model sensitivity to dust/soil contamination. The model is able to reproduce several well-known relationships among the Endeavour crater and Meridiani Planum lithologies, as well as produce some new geologic interpretations. New interpretations include: The Meridiani Plains Burns formation is compositionally diverse enough to parse into two superclusters, mostly along the lines of surface coatings. Analysis of the data by excluding S and Cl, some Burns formation rock compositions are similar to the Endeavour crater Shoemaker impact breccias. The clastic Grasberg formation is compositionally homogenous across two temporally distinct units and is most similar to the Shoemaker impact breccia in the Endeavour crater rim segments. These relationships support a local erosional origin instead of a distal ash origin. The lowest member of the Shoemaker breccia, the Copper Cliff unit, is compositionally similar to the pre-Endeavour Matijevic formation and contains Matijevic-type spherules, indicating that this unit contains eroded Matijevic materials. The Matijevic formation is compositionally distinct from other Endeavour materials but is similar to the “blue” (in Pancam false color) basaltic rocks Marquette Island and Margaret Brush. As a final example, the new regolith breccia class of martian meteorites (NWA 7034/7475) is the only class of martian meteorite to represent common martian surface compositions in the APXS data sets.

Chapter 3 expands the analysis to data collected by Opportunity within Perseverance Valley, using the statistical grouping model to classify lithologies and compare them to rock suites examined elsewhere along the Endeavour crater rim. The model establishes four rock lithologies within the valley, making it the most lithologically diverse location since the rover’s first exploration of Endeavour crater at Cape York. The lithologies include: a clast-poor impact breccia that forms the walls of the valley, an outcrop of resistant basaltic rocks that appear “blue” in false color Pancam imagery, an outcrop of pitted rocks that are some of the most silica-rich materials examined by Opportunity, and the valley floor material that comprises a loose regolith mixture of impact breccia, Meridiani soil, and “blue” rocks, implying a trough filled with locally mass-wasted materials. The “blue” rocks are similar enough in composition and texture to be classified as members of the lithology of “blue” rocks observed on the rim overlooking Marathon Valley, an outcrop that is also co-located with a pitted, silica-rich rock unit. This similarity, combined with the lateral offset of units across the valley, indicates that Perseverance Valley is a graben, formed along a radial impact fault that lowered the “blue” and pitted rocks ~80 meters to their current position. Evidence for aqueous alteration and modern aeolian erosion rounds out the valley’s history, and a formation model for Perseverance Valley, as supported by observations and lithologic relationships exposed by the statistical grouping model, is presented. (Abstract shortened by ProQuest.)

Indexing (document details)
Advisor: Jolliff, Bradley L.
Commitee: Arvidson, Raymond E., Dymek, Robert F., McKinnon, William B., McLennan, Scott M.
School: Washington University in St. Louis
Department: Earth & Planetary Sciences
School Location: United States -- Missouri
Source: DAI-B 80/08(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Statistics, Planetology, Geochemistry
Keywords: APXS, Endeavour crater, Hierarchical clustering, Mars, Opportunity rover, Similarity index
Publication Number: 13861370
ISBN: 9781392069233
Copyright © 2019 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy
ProQuest