University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Masters Theses Graduate School 12-2018 Remote Characterization of Physical Surface Characteristics of Mars Using Diurnal Variations in Apparent Thermal Inertia Cameron Blake McCarty University of Tennessee, [email protected] Follow this and additional works at: https://trace.tennessee.edu/utk_gradthes Recommended Citation McCarty, Cameron Blake, "Remote Characterization of Physical Surface Characteristics of Mars Using Diurnal Variations in Apparent Thermal Inertia. " Master's Thesis, University of Tennessee, 2018. https://trace.tennessee.edu/utk_gradthes/5344 This Thesis is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Masters Theses by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a thesis written by Cameron Blake McCarty entitled "Remote Characterization of Physical Surface Characteristics of Mars Using Diurnal Variations in Apparent Thermal Inertia." I have examined the final electronic copy of this thesis for form and content and recommend that it be accepted in partial fulfillment of the equirr ements for the degree of Master of Science, with a major in Geology. Jeff Moersch, Major Professor We have read this thesis and recommend its acceptance: Joshua P. Emery, Christopher M. Fedo Accepted for the Council: Dixie L. Thompson Vice Provost and Dean of the Graduate School (Original signatures are on file with official studentecor r ds.) Remote Characterization of Physical Surface Characteristics of Mars Using Diurnal Variations in Apparent Thermal Inertia A Thesis Presented for the Master of Science Degree The University of Tennessee, Knoxville Cameron Blake McCarty December 2018 Copyright © 2018 by Cameron Blake McCarty All rights reserved ii Dedication Mom, I'll love you forever, I'll like you for always. Hannah, You are the rock of stability in this ocean of stress that’s been grad school. Laika, Woof. Honor the past, Acknowledge the present, Salute the future. -Ron Anderson iii Acknowledgements I first want to express my appreciation for Jeff Moersch, my research advisor. His rigorous attention to detail has been incredibly valuable over this journey. Chris Fedo and Josh Emery have been a constant source of knowledge and academic advice. Other instructors who have always been available and insightful include: Hap McSween, Devon Burr, Annette Engel, Linda Kah, Larry Taylor, Ed Perfect, Brad Thomson, Nick Dygert, Molly McCanta, and Anna Szynkiewicz. Furthermore, this also couldn’t have been possible without the reviews, discussions, late night study sessions, and general emotional rock provided by Audrey Martin, Michael Phillips, Jessi Ende, Sam Gwizd, Chad Melton, Cameron Hughes, Ariana Boyd, and Emily Neild. Many other friends have helped throughout the years including my second family at the Coca-Cola Space Science Center, specifically Shawn Cruzen and Tina Cross for help above and beyond what was asked. My friends back home: Matt Bartow, Cole Downey, Daniel Kunze, John Hood, David Stillwell, Zach and Cheryl Coker, Matt and Emily Perry, and Quinn and Michelle O’Brien. A huge thank you to my family who have been supportive of me and my dreams of space since I was a small child. And of course, Hannah Klein, who has kept me laughing, focused, and sane ever since I dragged her to Knoxville, so I could pursue my dream. I’m so grateful for my fellows on the Mars Exploration Rover Team who showed me the joys of working on another planet. Finally, I would like to thank the THEMIS team, without whom my research would not have been possible. iv Abstract Analysis of the Martian surface today can provide insight into the processes that may have affected it over its history. Information about the physical surface characterization of a region can help determine the degree of sorting it has experienced and/or its geologic maturity. Sub-resolved “checkerboard” mixtures of materials with different horizontal thermal inertia mixtures can lead to differences in the apparent thermal inertia values inferred from night and day radiance observations. Standard methods for deriving thermal inertia from orbit via the THermal EMission Imaging System (THEMIS) can give values for the same location that vary by as much as 20% between images (Fergason et al., 2006b). Such methods assume that each pixel contains material of a single, uniform thermal inertia. Here, it is proposed that if a mixture of low and high apparent thermal inertias is present within a pixel, the inferred thermal inertia will be strongly dominated by the thermal inertia of whichever surface is warmer at the time of the measurement. This effect will result in a change in thermal inertia values inferred from measurements taken at different times of day and night. Therefore, a correlation is hypothesized between the magnitude of diurnal variations in apparent thermal inertia values and the degree of non-uniformity of thermal inertias present in a given pixel location. Preliminary work has shown that the magnitude of such diurnal variation in inferred thermal inertias is sufficient to detect geologically useful differences in surfaces mixtures. Mapping the difference in apparent thermal inertias from day and night THEMIS observations may prove to be a new way of distinguishing surfaces that have relatively uniform thermal inertias from those that have mixed thermal inertias. v Table of Contents 1. Background .................................................................................................................................................... 1 1.1. Sediments on Mars ....................................................................................................................................... 1 1.2. Radiance and Thermal Inertia ............................................................................................................... 3 1.3. Thermal Inertia Variability ..................................................................................................................... 5 1.4. Opportunity Rover Traverse .................................................................................................................... 7 2. Hypothesis ...................................................................................................................................................... 8 3. Methods ........................................................................................................................................................ 10 3.1. Theoretical Modeling ............................................................................................................................... 10 3.2. Site Selection ............................................................................................................................................... 14 3.3. Data Collection ........................................................................................................................................... 15 3.4. Data Processing with MARSTHERM .................................................................................................. 17 3.5. Data Processing with ENVI ................................................................................................................... 18 3.6. Data Processing with ArcGIS ................................................................................................................ 18 3.7 Processing HiRISE Images ...................................................................................................................... 20 4. Results ........................................................................................................................................................... 23 4.1. Theoretical Model ..................................................................................................................................... 23 4.2. In-situ Analysis ........................................................................................................................................... 24 4.3. Comparison Between 훥퐼 Values and Masked HiRISE image .................................................. 24 5. Discussion .................................................................................................................................................... 26 6. Summary ...................................................................................................................................................... 28 List of References........................................................................................................................................... 31 Appendices ....................................................................................................................................................... 37 Appendix A: Figures .......................................................................................................................................... 38 Appendix B: Theoretical Modeling of Diurnal Thermal Inertia Variations .............................. 49 Vita ...................................................................................................................................................................... 54 vi List of Figures Figure 1. A schematic