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Understanding the Threshold of Detection of Aeolian Features in Magellan Synthetic Aperture Radar Data Using Venusian and Terrestrial Dune Fields

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Understanding the Threshold of Detection of Aeolian Features in Magellan Synthetic Aperture Radar Data Using Venusian and Terrestrial Dune Fields University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Masters Theses Graduate School 8-2020 Understanding the Threshold of Detection of Aeolian Features in Magellan Synthetic Aperture Radar Data Using Venusian and Terrestrial Dune Fields Louisa Xian-Yue Rader University of Tennessee, [email protected] Follow this and additional works at: https://trace.tennessee.edu/utk_gradthes Recommended Citation Rader, Louisa Xian-Yue, "Understanding the Threshold of Detection of Aeolian Features in Magellan Synthetic Aperture Radar Data Using Venusian and Terrestrial Dune Fields. " Master's Thesis, University of Tennessee, 2020. https://trace.tennessee.edu/utk_gradthes/6093 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 Louisa Xian-Yue Rader entitled "Understanding the Threshold of Detection of Aeolian Features in Magellan Synthetic Aperture Radar Data Using Venusian and Terrestrial Dune Fields." 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. Bradley J. Thompson, Major Professor We have read this thesis and recommend its acceptance: Molly C. McCanta, 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.) Understanding the Threshold of Detection of Aeolian Features in Magellan Synthetic Aperture Radar Data Using Venusian and Terrestrial Dune Fields A Thesis Presented for the Master of Science Degree The University of Tennessee, Knoxville Louisa Xian-Yue Rader August 2020 Copyright © 2020 by Louisa Xian-Yue Rader All rights reserved. ii ACKNOWLEDGEMENTS Thank you to my advisor, Brad Thomson, for the opportunity to pursue my graduate degree and support through this journey. Without all your feedback and encouragement, I would not have been able to accomplish this. I would also like to thank Molly McCanta and Chris Fedo for providing advice and edits on my thesis. I would like to thank CJ Leight for always being there to make me smile and encouraging me every step of the way. I could not have done this without the support from Megan Mouser, Laura Breitenfeld, and my office desk pod buddy, Cole Nypaver. They have all cheered me on and provided moral support when I needed it. Finally, thank you to my parents for always supporting and believing in me. They have always encouraged my passions and helped me achieve more than I could ever imagine on my own. iii ABSTRACT The spatial resolution required for the detection of geomorphologic features on planetary surfaces is critical to developing a reproducible process for surface feature mapping and identification. The Magellan synthetic aperture radar (SAR) data of Venus have a spatial resolution of 75 m/pixel, which obfuscates features below about a kilometer in scale, while allowing analysis of larger-scale features (Saunders et al., 1991; Rader et al., 2019). Smaller- scale features, such as aeolian bedforms, are important for understanding erosional processes and the redistribution of sediment on the surface. (Rader et al., 2019). In order to properly detect and describe aeolian features on the surface of Venus and get a handle on their implications (e.g., for long-term wind patterns), we must understand the unique, diagnostic characteristics of aeolian features in low resolution SAR images and how these Magellan images can be interpreted (Rader et al., 2019). Here we show how to identify the diagnostic characteristics of dune fields in both visible and radar wavelength images and quantify the differences between them, using Earth as an analog for Venus. Aeolian features of the scale observed on Venus are also found in hyper- arid desert regions on Earth, with this study focusing on the Simpson Desert in Australia and the Namib Desert in Namibia (e.g., Bristow et al., 2007; Lancaster, 2009). The crestlines of linear dunes at these two terrestrial sites were mapped in optical (VIS) images at high resolution and in both high and low resolution SAR images as analogs for the venusian fields. The five venusian localities selected had a representative population of features mapped and then compared to the terrestrial dune fields (Greeley et al., 1992; Weitz et al., 1994; Rader et al., 2019). The mapped images were compared to identify diagnostic characteristics that can be used to identify other potential aeolian fields. These results demonstrate how dune fields can be identified on Venus and suggest possible reasons for the scarcity of potential venusian aeolian fields. iv TABLE OF CONTENTS 1. Introduction ................................................................................................................................. 1 2. Background ................................................................................................................................. 5 2.1 Synthetic Aperture Radar ...................................................................................................... 5 2.2 Magellan Orbiter ................................................................................................................... 6 2.3 Sentinel-1 .............................................................................................................................. 7 2.4 Optical Imagery ..................................................................................................................... 8 2.5 World Imagery Layer ............................................................................................................ 8 2.6 Jet Propulsion Laboratory Topography Data ........................................................................ 9 2.7 Aeolian Features .................................................................................................................... 9 2.7.1 Dunes ............................................................................................................................ 10 2.7.1.1 Linear Dunes ......................................................................................................... 11 2.7.1.2 Transverse Dunes .................................................................................................. 12 2.7.2 Yardangs ....................................................................................................................... 12 2.7.3 Simpson Desert ............................................................................................................. 14 2.7.4 Namib Desert ................................................................................................................ 15 2.7.5 Venusian Features and Working Hypothesis................................................................ 15 2.8 Identification Resolution ..................................................................................................... 17 3. Methods and Data ..................................................................................................................... 19 3.1 Terrestrial SAR Data Processing......................................................................................... 19 v 3.2 Terrestrial ArcGIS Mapping ............................................................................................... 21 3.3 Magellan SAR Data Processing .......................................................................................... 22 3.4 Magellan ArcGIS Mapping ................................................................................................. 23 3.5 Venusian Topographic ArcGIS Mapping ........................................................................... 24 4. Results ....................................................................................................................................... 26 4.1 Simpson Desert ................................................................................................................... 26 4.1.1 VIS at 0.5 m/pixel ......................................................................................................... 26 4.1.2 SAR at 13.5 m/pixel ..................................................................................................... 27 4.1.3 SAR at 75 m/pixel ........................................................................................................ 28 4.2 Namib Desert....................................................................................................................... 29 4.2.1 Linear Dunes in VIS at 0.5 m/pixel .............................................................................. 29 4.2.2 Linear Dunes in SAR at 13.5 m/pixel ........................................................................... 30 4.2.3 Linear Dunes in SAR at 75 m/pixel .............................................................................. 31 4.2.4 Transverse Dunes in VIS at 0.5 m/pixel ....................................................................... 32 4.2.5 Transverse Dunes in SAR at 13.5 m/pixel ................................................................... 32 4.2.6 Transverse Dunes in SAR at 75 m/pixel
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