From Event: SPIE Optical Engineering + Applications, 2016
We measure and describe the angular dependence of field and laboratory hyperspectral reflectance measurements of sediments from the Algodones Dunes, CA using the Goniometer of the Rochester Institute of Technology (GRIT) and compare with NASA G-LiHT hyperspectral imagery. G-LiHT imagery was acquired concurrently during a joint field experiment in March 2015 conducted by NASA Goddard, South Dakota State University, University of Arizona, University of Lethbridge, and Rochester Institute of Technology (RIT). Radiative transfer models1 and our own observations10 demonstrate that the angular dependence observed in the bidirectional reflectance distribution (BRDF)1,2,3,4,5,6 is strongly influenced by factors such as density, grain size distribution, moisture content, and surface roughness.5,6,7,8,9 Hapke’s model applied to a uniform sediment predicts increasing reflectance as density increases, however, we have observed that multiple scattering and the presence of optically contrasting mineral fractions can lead to the opposite trend.9,10 The degree of multiple scattering is influenced by incident illumination zenith angle, which determines whether the Hapke prediction is observed or the opposite trend.10 To better match observations, modifications of the model are necessary.10 In this paper, we consider some initial work showing the relationship between NASA G-LiHT hyperspectral imagery and GRIT10 field and laboratory BRDF and GRIT-Two (GRIT-T)11 laboratory BRDF. We also discuss preliminary work using this data for retrieval of geophysical properties of the sediment such as density from multi-angular measurements.
Charles M. Bachmann, Brittany Ambeau, Carrie Griffo, Justin Harms, Emily Myers, and Gregory Badura, "Modeling geophysical properties of the Algodones Dunes from field and laboratory hyperspectral goniometer measurements using GRIT and comparison with G-LiHT imagery," Proc. SPIE 9972, Earth Observing Systems XXI, 99720K (Presented at SPIE Optical Engineering + Applications: August 30, 2016; Published: 19 September 2016); https://doi.org/10.1117/12.2238270.
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