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Article

In-Situ and Aircraft Reflectance Measurement Effectiveness for CAL/VAL Activities: A Study over Railroad Valley

1
European Commission, Joint Research Centre (JRC), via E. Fermi 2749, I-21027 Ispra (VA), Italy
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Hellenic Centre for Marine Research (HCMR), Institute of Oceanography, Former USAF Base Gournes, 71500 Hersonissos, Crete, Greece
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Mullard Space Science Laboratory, UCL, Holmbury Hill Rd, Dorking RH5 6NP, UK
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NASA, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
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Universities Space Research Association, Columbia, MD 21046, USA
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National Physical Laboratory, Earth Observation, Climate and Optical Group, Hampton Rd. Teddington, Middlesex TW11 0LW, UK
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(20), 3366; https://doi.org/10.3390/rs12203366
Received: 11 August 2020 / Revised: 2 October 2020 / Accepted: 7 October 2020 / Published: 15 October 2020
This paper aims to assess the relationship between the surface reflectance derived from ground based and aircraft measurements. The parameters of the Rahman–Pinty–Verstraete (RPV) and Ross Thick-LiSparse (RTLS) kernel based bi-directional reflectance distribution functions (BRDF), have been derived using actual measurements of the hemispherical-directional reflectance factor (HDRF), collected during different campaigns over the Railroad Valley Playa. The effect of the atmosphere, including that of the diffuse radiation on bi-directional reflectance factor (BRF) parameter retrievals, assessed using 6S model simulations, was negligible for the low turbidity conditions of the site under investigation (τ5500.05). It was also shown that the effects of the diffuse radiation on RPV spectral parameters retrieval is linear for the isotropic parameter ρ0 and the scattering parameter Θ, and can be described with a second order polynomial for the k-Minnaert parameter. In order to overcome the lack of temporal collocations between aircraft and in-situ measurements, Monte Carlo 3-D radiative transfer simulations mimicking in-situ and remote sensing techniques were performed on a synthetic parametric meshed scene defined by merging Landsat and Multianglhe Imaging Spectroradiometer (MISR) remote sensing reflectance data. We simulated directional reflectance measurements made at different heights for PARABOLA and CAR, and analyzed them according to practices adopted for real measurements, consisting of the inversion of BRF functions and the calculation of the bi-hemispherical reflectance (BHR). The difference of retrievals against the known benchmarks of kernel parameters and BHR is presented. We associated an uncertainty of up to 2% with the retrieval of area averaged BHR, independently of flight altitudes and the BRF model used for the inversion. As expected, the local nature of PARABOLA data is revealed by the difference of the anisotropic kernel parameters with the corresponding parameters retrieved from aircraft loops. The uncertainty of the resultant BHR fell within ±3%. View Full-Text
Keywords: albedo; BRDF; validation; in-situ measurement; 3-D RTM albedo; BRDF; validation; in-situ measurement; 3-D RTM
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MDPI and ACS Style

Lanconelli, C.; Banks, A.C.; Muller, J.-P.; Bruegge, C.; Cappucci, F.; Gatebe, C.; Kharbouche, S.; Morgan, O.; Mota, B.; Gobron, N. In-Situ and Aircraft Reflectance Measurement Effectiveness for CAL/VAL Activities: A Study over Railroad Valley. Remote Sens. 2020, 12, 3366. https://doi.org/10.3390/rs12203366

AMA Style

Lanconelli C, Banks AC, Muller J-P, Bruegge C, Cappucci F, Gatebe C, Kharbouche S, Morgan O, Mota B, Gobron N. In-Situ and Aircraft Reflectance Measurement Effectiveness for CAL/VAL Activities: A Study over Railroad Valley. Remote Sensing. 2020; 12(20):3366. https://doi.org/10.3390/rs12203366

Chicago/Turabian Style

Lanconelli, Christian, Andrew C. Banks, Jan-Peter Muller, Carol Bruegge, Fabrizio Cappucci, Charles Gatebe, Said Kharbouche, Olivier Morgan, Bernardo Mota, and Nadine Gobron. 2020. "In-Situ and Aircraft Reflectance Measurement Effectiveness for CAL/VAL Activities: A Study over Railroad Valley" Remote Sensing 12, no. 20: 3366. https://doi.org/10.3390/rs12203366

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