Application of Geologic Mapping Techniques and Autonomous Feature Detection to Future Exploration of Europa

Europa's extremely young surface age, evidence for extensive resurfacing, and indications of a sub-surface ocean elevate its astrobiological potential for habitable environments and make it a compelling focus for study. Knowledge of the global distribution and timing of Europan geologic units is a key step in understanding the history of the satellite and for identifying areas relevant for exploration. I have produced a 1:15M scale global geologic map of Europa which represents a proportionate distribution of four unit types and associated features: plains, linea, chaos, and crater materials. Mapping techniques differ somewhat from other planetary maps but do provide a method to establish stratigraphic markers and to illustrate the surface history through four periods of formation as a function of framework lineament cross-cutting relationships. Correlations of observed features on Europa with Earth analogs enforce a multi-process theory for formation rather than the typical reliance on the principle of parsimony. Lenticulae and microchaos are genetically similar and most likely form by diapirism. Platy and blocky chaos units, endmembers of archetypical chaos, are best explained by brine mobilization. Ridges account for the majority of lineaments and may form by a number of methods indicative of local conditions; most form by either tidal pumping or shear heating. The variety of morphologies exhibited by bands indicates that multiple formation mechanisms apply once fracturing of the brittle surface over a ductile subsurface is initiated. Mapping results support the interpretation that Europa's shell has thickened over time resulting in changes in the style and intensity of deformation. Mapping serves as an index for change detection and classification, aids in pre-encounter targeting, and supports the selection of potential landing sites. Highest priority target areas are those which indicate geophysical activity by the presence of volcanic plumes, outgassing, or disrupted surface morphologies. Areas of high interest include lineaments and chaos margins. The limitations on detecting activity at these locations are approximated by studying similar observed conditions on other bodies. By adapting machine learning and data mining techniques to signatures of plumes and morphology, I have demonstrated autonomous rule-based detection of known features using edge-detection and supervised classification methods. These methods successfully detect ≤94% of known volcanic plumes or jets at Io, Enceladus, and comets. They also allow recognition of multiple feature types. Applying these results to conditions expected for Europa enables a prediction of the potential for detection of similar features and enables recommendations for mission concepts to increase the science return and efficiency of future missions to observe Europa. This post-Galileo view of Europa provides a synthesis of the overall history of this unique icy satellite and will be a useful frame of reference for future exploration of the jovian system and other potentially active outer solar system bodies.