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Description
A thorough understanding of Europa's geology through the synergy of science and technology, by combining geologic mapping with autonomous onboard processing methods, enhances the science potential of future outer solar system missions. Mapping outlines the current state of knowledge of Europa's surface and near sub-surface, indicates the prevalence of distinctive geologic features, and enables a uniform perspective of formation mechanisms responsible for generating those features. I have produced a global geologic map of Europa at 1:15 million scale and appraised formation scenarios with respect to conditions necessary to produce observed morphologies and variability of those conditions over Europa's visible geologic history. Mapping identifies areas of interest relevant for autonomous study; it serves as an index for change detection and classification and aids pre-encounter targeting. Therefore, determining the detectability of geophysical activity is essential. Activity is evident by the presence of volcanic plumes or outgassing, disrupted surface morphologies, or changes in morphology, color, temperature, or composition; these characteristics reflect important constraints on the interior dynamics and evolutions of planetary bodies. By adapting machine learning and data mining techniques to signatures of plumes, morphology, and spectra, I have successfully demonstrated autonomous rule-based response and detection, identification, and classification of known events and features on outer planetary bodies using the following methods: 1. Edge-detection, which identifies the planetary horizon and highlights features extending beyond the limb; 2. Spectral matching using a superpixel endmember detection algorithm that identifies mean spectral signatures; and 3. Scale invariant feature transforms combined with supervised classification, which examines brightness gradients throughout an image, highlights extreme gradient regions, and classifies those regions based on a manually selected library of features. I have demonstrated autonomous: detection of volcanic plumes or jets at Io, Enceladus, and several comets, correlation between spectral signatures and morphological appearances of Europa's individual tectonic features, detection of ≤94% of known transient events on multiple planetary bodies, and classification of similar geologic features. Applying these results to conditions expected for Europa enables a prediction of the potential for detection and recommendations for mission concepts to increase the science return and efficiency of future missions to observe Europa.
ContributorsBunte, Melissa K (Author) / Bell, Iii, James F. (Thesis advisor) / Williams, David A. (Committee member) / Saripalli, Srikanth (Committee member) / Clarke, Amanda B. (Committee member) / Reynolds, Stephen J. (Committee member) / Christensen, Phillip R. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Meter-resolution topography gathered by LiDAR (Light Detection and Ranging) has become an indispensable tool for better understanding of many surface processes including those sculpting landscapes that record information about earthquake hazards for example. For this reason, and because of the spectacular representation of the phenomena that these data provide, it is appropriate to integrate these data into Earth science educational materials. I seek to answer the following research question: "will using the LiDAR topography data instead of, or alongside, traditional visualizations and teaching methods enhance a student's ability to understand geologic concepts such as plate tectonics, the earthquake cycle, strike-slip faults, and geomorphology?" In order to answer this question, a ten-minute introductory video on LiDAR and its uses for the study of earthquakes entitled "LiDAR: Illuminating Earthquake Hazards" was produced. Additionally, LiDAR topography was integrated into the development of an undergraduate-level educational activity, the San Andreas fault (SAF) earthquake cycle activity, designed to teach introductory Earth science students about the earthquake cycle. Both the LiDAR video and the SAF activity were tested in undergraduate classrooms in order to determine their effectiveness. A pretest and posttest were administered to introductory geology lab students. The results of these tests show a notable increase in understanding LiDAR topography and its uses for studying earthquakes from pretest to posttest after watching the video on LiDAR, and a notable increase in understanding the earthquake cycle from pretest to posttest using the San Andreas Fault earthquake cycle exercise. These results suggest that the use of LiDAR topography within these educational tools is beneficial for students when learning about the earthquake cycle and earthquake hazards.
ContributorsRobinson, Sarah Elizabeth (Author) / Arrowsmith, Ramon (Thesis advisor) / Reynolds, Stephen J. (Committee member) / Semken, Steven (Committee member) / Arizona State University (Publisher)
Created2011