Quantifying Geomorphic Features: Relative Albedos, Skeletonization, and Multifractality
Author
Schaefer, Ethan ImmanuelIssue Date
2018Advisor
McEwen, Alfred S.
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The University of Arizona.Rights
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.Abstract
The qualitative and quantitative components of geomorphology are both essential, and complementary, modes of investigation. In the present work, I present three studies that each illustrate a different relationship between these two vital components. In a case study of transient, relatively dark linear features on the martian surface called recurring slope lineae (RSL), I provide an example in which (semi)qualitative geomorphic observations directly motivate quantitative analyses that in turn provide insights into the enigmatic nature of RSL. Specifically, these analyses suggest that RSL at the study site are more likely formed by dry granular flows than by groundwater. In a second investigation, I describe a new algorithm to derive the skeleton of a geomorphic polygon, such as the centerline for a river. This geomorphic study provides a persuasive illustration that geomorphology in general can benefit from the focused development of quantitative methods specifically tailored for geomorphic applications, especially in view of the continuing proliferation of remotely sensed data. As examples, I discuss the potential of the algorithm to provide broader analysis, and hence insights, into respective large databases of rivers on Earth and dust devil tracks on Mars. In the final study, we critically reevaluate the potential to interpret a lava flow’s type from the meter-scale geometry of its margin. We show that the previously unrecognized scale-dependence of these geometries and other complications (e.g., topographic confinement, transitional flow types) require a revised strategy for interpreting lava flow type remotely. This final study thus illustrates the need for the continual refinement of quantitative geomorphic models, which can underestimate the variability found in nature.Type
textElectronic Dissertation
Degree Name
Ph.D.Degree Level
doctoralDegree Program
Graduate CollegePlanetary Sciences