Thermal infrared emissivity measurements under a simulated lunar environment: Application to the Diviner Lunar Radiometer Experiment

Mathematics – Logic

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Planetary Sciences: Solid Surface Planets: Composition (1060, 3672), Planetary Sciences: Solid Surface Planets: Remote Sensing, Planetary Sciences: Solid Surface Planets: Surface Materials And Properties, Planetary Sciences: Solar System Objects: Moon (1221)

Scientific paper

We present new laboratory thermal infrared emissivity spectra of the major silicate minerals identified on the Moon measured under lunar environmental conditions and evaluate their application to lunar remote sensing data sets. Thermal infrared spectral changes between ambient and lunar environmental conditions are characterized for the first time over the 400˜1700 cm-1 (6-25 μm) spectral range for a fine-particulate mineral suite including plagioclase (albite and anorthite), pyroxene (enstatite and augite), and olivine (forsterite). The lunar environment introduces observable effects in thermal infrared emissivity spectra of fine particulate minerals, which include: (1) a shift in the Christiansen feature (CF) position to higher wave numbers (shorter wavelengths), (2) an increase in the overall spectral contrast, and (3) decreases in the spectral contrast of the reststrahlen bands and transparency features. Our new measurements demonstrate the high sensitivity of thermal infrared emissivity spectra to environmental conditions under which they are measured and provide important constraints for interpreting new thermal infrared data sets of the Moon, including the Diviner Lunar Radiometer Experiment onboard NASA's Lunar Reconnaissance Orbiter. Full resolution laboratory mineral spectra convolved to Diviner's three spectral channels show that spectral shape, CF position and band ratios can be used to distinguish between individual mineral groups and lunar lithologies. The integration of the thermal infrared CF position with near infrared spectral parameters allows for robust mineralogical identifications and provides a framework for future integrations of data sets across two different wavelength regimes.

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