Masters Theses

Date of Award

8-2020

Degree Type

Thesis

Degree Name

Master of Science

Major

Geology

Major Professor

Bradley J. Thompson

Committee Members

Molly C. McCanta, Christopher M. Fedo

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.

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