Mineralogy

The power of mineralogical analysis as a descriptive or predictive technique stems from the fact that only a few thousand minerals are known to occur in nature as compared to several hundred thousand inorganic compounds. Further, all of the known minerals have specific stability ranges in pressure, temperature, an composition. A specific knowledge of the mineralogy of a planets surface or interior therefore allows one to characterize the present or past conditions under which the minerals were formed or have existed. For the purposes of this paper, a slightly broader definition of mineralogy was adopted by including not only crystalline materials found on planetary surfaces, but also ices and classes that can benefit from in situ types of analyses. Both visual examination and the various spectroscopies available for robotic probes to planetary surfaces are discussed

Morphology and Composition of the Surface of Mars: Mars Odyssey THEMIS Results

The Thermal Emission Imaging System (THEMIS) on Mars Odyssey has produced infrared to visible wavelength images of the martian surface that show lithologically distinct layers with variable thickness, implying temporal changes in the processes or environments during or after their formation. Kilometer-scale exposures of bedrock are observed; elsewhere airfall dust completely mantles the surface over thousands of square kilometers. Mars has compositional variations at 100-meter scales, for example, an exposure of olivine-rich basalt in the walls of Ganges Chasma. Thermally distinct ejecta facies occur around some craters with variations associated with crater age. Polar observations have identified temporal patches of water frost in the north polar cap. No thermal signatures associated with endogenic heat sources have been identified

Scheduling Results for the THEMIS Observation Scheduling Tool

We describe a scheduling system intended to assist in the development of instrument data acquisitions for the THEMIS instrument, onboard the Mars Odyssey spacecraft, and compare results from multiple scheduling algorithms. This tool creates observations of both (a) targeted geographical regions of interest and (b) general mapping observations, while respecting spacecraft constraints such as data volume, observation timing, visibility, lighting, season, and science priorities. This tool therefore must address both geometric and state/timing/resource constraints. We describe a tool that maps geometric polygon overlap constraints to set covering constraints using a grid-based approach. These set covering constraints are then incorporated into a greedy optimization scheduling algorithm incorporating operations constraints to generate feasible schedules. The resultant tool generates schedules of hundreds of observations per week out of potential thousands of observations. This tool is currently under evaluation by the THEMIS observation planning team at Arizona State University