The reflectance-based vicarious calibration approach uses measurements at well-understood test sites to provide top-of-atmosphere reference reflectance values suitable for inter-calibration approaches and does not require coincident views. The challenge is that results from such data may suffer from high variability from day to day. Data from high-quality sensors, such as the imaging spectrometers on the International Space Station (ISS) platform, provide an opportunity to use improved fine spectral information about the test sites with various sun/sensor geometries and site surface and atmospheric conditions to improve the test sites’ characterization. The results here are based on data from the DLR Earth Sensing Imaging Spectrometer (DESIS) instrument installed on the ISS since 2018 combined with output from the Radiometric Calibration Network (RadCalNet) site at Railroad Valley Playa (RRV) to decouple the effects of sun/sensor geometry from the RadCalNet predictions. The approach here uses the precessing orbit of the ISS to allow similar sensor view zenith angles at varying sun angles over short periods that limit the impact of any sensor changes and highlight the bi-directional effects of the surface reflectance and atmospheric conditions. DESIS data collected at (i) similar solar angles but varying view angles, (ii) similar sensor angles and varying solar angles, and (iii) similar scatter angles are compared. The DESIS results indicate that the top-of-atmosphere reflectance spectra for RRV at similar solar zenith angles but with varying sensor viewing angles provide more consistent data than those with varying solar zenith but with similar sensor viewing angles. In addition, comparisons of reflectance spectra of the site performed in terms of the sensor view scatter angle show good agreement, indicating that a directional reflectance correction would be straightforward and could offer a significant improvement in the use of RadCalNet data. The work shows that observations from imaging spectroscopy data from DESIS, and eventually Earth Surface Mineral Dust Source Investigation (EMIT), Surface Biology and Geology (SBG), and the climate-quality sensor CLARREO Pathfinder (CPF), provide the opportunity for the development of a model-based, SI-traceable prediction of at-sensor radiance over the RRV site that would serve as the basis for similar site characterizations with error budgets valid for arbitrary view and illumination angles.
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