Representative Image Subsets in Soil Analysis Using the Mars Exploration Rover Microscopic Imager

Details Representative Image Subsets in Soil Analysis Using the Mars Exploration Rover Microscopic Imager Representative Image Subsets in Soil Analysis Using the Mars Exploration Rover Microscopic Imager

Dec 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufm.p43d1460c&link_type=abstract

American Geophysical Union, Fall Meeting 2009, abstract #P43D-1460

Computer Science

Sound

[5400] Planetary Sciences: Solid Surface Planets, [5415] Planetary Sciences: Solid Surface Planets / Erosion And Weathering

Scientific paper

Assessing texture and morphology is a critical step in evaluating the plausible origin and evolution of soil particles. Both are essential to the understanding of martian soils beyond Gusev and Meridiani. In addition to supporting rover operations, what is being learned at both landing sites about soil physical characteristics and properties provides essential keys to model with more precision the nature of martian soils at global scale from the correlation of ground-based and orbital data. Soil and particles studies will improve trafficability predictions for future missions, whether robotic or human, ultimately increasing safety and mission productivity. Data can also be used to assist in pre-mission hardware testing, and during missions to support engineering activities including rover extrication, which makes the characterization of soils at the particle level and their mixing critical. On Mars, this assessment is performed within the constraints of the rover’s instrumentation. The Microscopic Imager allows the identification of particles ≥ 100 µm across. Individual particles of clay, silt and very fine sand are not accessible. Texture is, thus, defined here as the relative proportion of particles ≥ 100 µm. Analytical methods are consistent with standard sedimentologic techniques applied to the study of thin sections and digital images on terrestrial soils. Those have known constraints and biases and are well adapted to the limitations of documenting three-dimensional particles on Mars through the two-dimensional FoV of the MI. Biases and errors are linked to instrument resolution and particle size. Precision improves with increasing size and is unlikely to be consistent in the study of composite soil samples. Here, we address how to obtain a statistically sound and accurate representation of individual particles and soil mixings without analyzing entire MI images. The objectives are to (a) understand the role of particle-size in selecting statistically significant study area for MI images; (b) identify the smallest significant study area that provides accurate information consistent with the final distribution (complete image study); and (c) quantify the variations, if any, between the results from the various increments. During the process of image analysis, representative subsets of images are typically selected using the “geologist’s eye” and the subset size depends on soil type and particle-size. We used a series of MI images on soils at Gusev and Meridiani to test the hypothesis that the subset size for various types of soils and mixings can be quantified and that the experiment can be repeated with similar results both on the analyzed image and on other images containing particles and soil mixings of similar nature. If true, the identification of these subsets could contribute to the future onboard automation of particles and soil mixings interpretation, significantly mission productivity and helping in target selection. The surface area of each MI image was analyzed in 10% increments. While the test is ongoing, current results provide high confidence that there is repeatability; discrepancies are more common in smaller size particles, but those discrepancies do not lead to misinterpretation (i.e., changes in particle class).

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