Lunar surface roughness derived from LRO Diviner Radiometer observations

Bandfield, J. L.; Hayne, P. O.; Williams, J. P.; Greenhagen, B. T.; Paige, D. A.

doi:10.1016/j.icarus.2014.11.009

Cited by 103 publications

(206 citation statements)

References 58 publications

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“…The probability distribution P for a given slope angle is given in Bandfield et al () as

P ((), θ_{s}) = \frac{tan ((), θ_{s})}{{tan}^{2} ((), θ_{0})} \cdot e^{- \frac{{tan}^{2} ((), θ_{s})}{2 {tan}^{2} ((), θ_{0})}}

where θ 0 is the RMS slope angle and θ s is the angle of the slope from the surface normal. This describes the adirectional distribution of slopes that closely approximates a Gaussian distribution of unidirectional slopes for a RMS slope angle of θ 0 (Bandfield et al, ).…”

Section: Directional Emissivity Modelsmentioning

confidence: 99%

“…The multiple slope Fresnel model used in the previous section (3.3) does not account for view shadowing. When the view shadowing approximation methodology was included in the multiple slope Fresnel model (see Bandfield et al, , for model details), it was still found not to adequately fit the measured DE ( R 2 value of 0.89 as seen in Figure ).…”

Section: Directional Emissivity Modelsmentioning

confidence: 99%

“…This assumed isotropic scattering has previously been shown to be incorrect in the visible by a number of laboratory measurements (Foote & Paige, ; Johnson et al, ; Pommerol et al, ). There is also strong evidence from remote sensing measurements (Bandfield et al, ) and a very limited number of laboratory measurements (Warren et al, ) that the isotropic assumption is also incorrect in the TIR. The assumption of isotropic scattering in both the TIR and visible is believed to be the reason for differences of up to tens of Kelvin in previous 3‐D thermophysical models of the lunar polar surface when compared to infrared remote sensing measurements (Hayne et al, ).…”

Section: Introductionmentioning

confidence: 99%

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Modeling the Angular Dependence of Emissivity of Randomly Rough Surfaces

2019

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Directional emissivity (DE) describes how the emissivity of an isothermal surface changes with viewing angle across thermal infrared wavelengths. The Oxford Space Environment Goniometer (OSEG) is a novel instrument that has been specifically designed to measure the DE of regolith materials derived from planetary surfaces. The DE of Nextel high‐emissivity black paint was previously measured by the OSEG and showed that the measured emissivity decreases with increasing emission angle, from an emissivity of 0.97 ± 0.01 at 0° emission angle to an emissivity of 0.89 ± 0.01 at 71° emission angle. The Nextel target measured was isothermal (<0.1 K surface temperature variation), and the observed change in emissivity was due to Fresnel‐related effects and was not due to nonisothermal effects. Here we apply several increasingly complex modeling techniques to model the measured DE of Nextel black paint. The modeling techniques used here include the Hapke DE model, the Fresnel equations, a multiple slope Fresnel model, and a Monte Carlo ray tracing model. It was found that only the Monte Carlo ray tracing model could accurately fit the OSEG measured Nextel data. We show that this is because the Monte Carlo ray tracing model is the only model that fully accounts for the surface roughness of the Nextel surface by including multiple scattering effects.

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“…The probability distribution P for a given slope angle is given in Bandfield et al () as

P ((), θ_{s}) = \frac{tan ((), θ_{s})}{{tan}^{2} ((), θ_{0})} \cdot e^{- \frac{{tan}^{2} ((), θ_{s})}{2 {tan}^{2} ((), θ_{0})}}

Section: Directional Emissivity Modelsmentioning

confidence: 99%

Section: Directional Emissivity Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling the Angular Dependence of Emissivity of Randomly Rough Surfaces

2019

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“…The current, and only, lunar MIR instrument is the Diviner Lunar Radiometer Experiment (Diviner) on the Lunar Reconnaissance Orbiter. Diviner measures radiance from 0.3 to 400 μm, which can be converted to emissivity to inform us about the bulk silicate mineralogy across the surface of the Moon (Greenhagen et al, ; Paige, Foote, et al, ), as well as the thermophysical properties of the lunar regolith (e.g., Bandfield et al, , ; Elder et al, ; Paige, Siegler, et al, ; Siegler et al, , ; Vasavada et al, ). Diviner has contributed to a better understanding of lunar geology, such as highly silicic features (e.g., Glotch et al, ), crater peak compositions (e.g., Song et al, ), and lunar swirls (e.g., Glotch et al, ) and shown how well Diviner data can complement visible to near‐infrared data, such as the assessment of lunar crystalline plagioclase (e.g., Donaldson Hanna et al, ), examination of volcanics (e.g., Bennett et al, ), and quantification of olivine content (e.g., Arnold et al, ).…”

Section: Introductionmentioning

confidence: 99%

Particle Size Effects on Mid‐Infrared Spectra of Lunar Analog Minerals in a Simulated Lunar Environment

Shirley

Glotch

2019

JGR Planets

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Mid‐infrared spectroscopic analysis of the Moon and other airless bodies requires a full accounting of spectral variation due to the unique thermal environment in airless body regoliths and the substantial differences between spectra acquired under airless body conditions and those measured in an ambient environment on Earth. Because there exists a thermal gradient within the upper hundreds of microns of lunar regolith, the data acquired by the Diviner Lunar Radiometer Experiment are not isothermal with wavelength. While this complication has been previously identified, its effect on other known variables that contribute to spectral variation, such as particle size and porosity, have yet to be well characterized in the laboratory. Here we examine the effect of particle size on mid‐infrared spectra of silicates common to the Moon measured within a simulated lunar environment chamber. Under simulated lunar conditions, decreasing particle size is shown to enhance the spectral contrast of the Reststrahlen bands and transparency features, as well as shift the location of the Christiansen feature to longer wavelengths. This study shows that these variations are detectable at Diviner spectral resolution and emphasizes the need for simulated environment laboratory data sets, as well as hyperspectral mid‐infrared instruments on future missions to airless bodies.

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“…Though the infrared brightness temperatures are influenced by the lunar surface roughness (Bandfield et al, 2015), the proper regions and local time for the infrared brightness temperatures could avoid the interference. Now select the CE-2 TB data for a profile at 33 s N extending from 120°W to 6°E for retrieving the bulk density of lunar subsurface layer.…”

Section: Retrieval Of the Bulk Density Of Lunar Subsurface Layermentioning

confidence: 99%