Computer Science – Learning
Scientific paper
Dec 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011agufm.p33d1784p&link_type=abstract
American Geophysical Union, Fall Meeting 2011, abstract #P33D-1784
Computer Science
Learning
[1942] Informatics / Machine Learning, [3665] Mineralogy And Petrology / Mineral Occurrences And Deposits, [5464] Planetary Sciences: Solid Surface Planets / Remote Sensing, [6225] Planetary Sciences: Solar System Objects / Mars
Scientific paper
The success of a Martian sample collection campaign will hinge on the ability to efficiently identify and characterize the local mineralogy. This process has been well demonstrated on a planetary scale with the OMEGA and CRISM hyperspectral near-infrared imaging cameras. These instruments have identified phyllosilicates, sulfates, mafics and ices among other phases and have been crucial in the MSL landing site selection and the future sample return site. Furthermore, CRISM detections of phyllosilicates around Endeavour crater are being used for the first time in tactical decisions about where to drive the Mars Exploration Rover "Opportunity" to the most fruitful locations for scientific investigations. We present a field simulation study where we demonstrate that a portable ground based hyperspectral near-infrared imager, together with onboard data processing software could be used to drive the scientific analysis from the automatic identification and mapping of the mineralogy of all visible deposits to a preliminary analysis of the specific compositions of target samples. We report on the initial results of a field campaign at the Rio Tinto Mars analog site in Spain. This site is renown for sulfate deposits from an acid mine drainage system, but contains significant deposits of phyllosilicates in the local stratigraphy. In this environment we used a HySpex camera provided by the Norsk Elektro Optikk company and an automatic mineral identification software to simulate a rover traverse driven by mineral identification and mapping. Hyspex set-up combines two high resolution pushbroom imaging spectrometers collectively in the range of 0.4 to 2.5 μm, with 416 channels and 0.3 to 0.7 mrad pixel field of view. We began each run with a panorama of the surrounding terrain. The spectral panorama was then analyzed by an automated program allowing the creation of mineral maps to identify the spatial extant of the minerals of interest, namely sulfates and phyllosilicates and determine the region with highest spectral diversity to drive the traverse to the minerals of interest. The camera was then moved based on the spectral results until we were adjacent to the target deposits (up to a distance of 30 cm from the target). Initial results show that a ground based hyperspectral camera and identification software can be used to successfully drive a sampling mission toward the minerals of highest interest and to appreciate interesting patterns in the identified mineral diversity at different scales.
Baarstad I.
Mustard John F.
Parente Mimmo
Skok John R.
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