Generation and performance of automated jarosite mineral detectors for visible/near-infrared spectrometers at Mars

نویسندگان

  • Martha S. Gilmore
  • Benjamin Bornstein
  • Matthew D. Merrill
  • Rebecca Castaño
  • James P. Greenwood
چکیده

We have developed two automated detectors that can recognize the sulfate mineral jarosite in unknown visible to near-infrared spectra (350– 2500 nm). The two detectors are optimized for use within the terrestrial and martian atmospheres. The detectors are built from Support Vector Machines trained using a generative model to create linear mixtures of library mineral spectra. Both detectors performed with an average ∼90% accuracy on laboratory spectra of single minerals and the laboratory and field spectra of rocks collected in a hydrothermal environment. This type of algorithm will contribute to the efficiency of onboard data analysis of landed and orbital visible/near-infrared spectrometers at Mars. © 2007 Elsevier Inc. All rights reserved.

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تاریخ انتشار 2008