Publication Abstracts

Thompson et al. 2020

Thompson, D.R., A. Braverman, P. Brodrick, A. Candela, N. Carmon, R.N. Clark, D. Connelly, R.O. Green, R.F. Kokaly, L. Li, N. Mahowald, R.L. Miller, G.S. Okin, T.H. Painter, G.A. Swayze, M. Turmon, J. Susilouto, and D.S. Wettergreen, 2020: Quantifying uncertainty for remote spectroscopy of surface composition. Remote Sens. Environ., 247, 111898, doi:10.1016/j.rse.2020.111898.

Remote surface measurements by imaging spectrometers play an important role in planetary and Earth science. To make these measurements, investigators calibrate instrument data to absolute units, invert physical models to estimate atmospheric effects, and then determine surface properties from the spectral reflectance. This study quantifies the uncertainty in this process. Global missions demand predictive uncertainty models that can estimate future errors for varied environments and observing conditions. Here we validate uncertainty predictions with remote surface composition retrievals and in situ measurements in a field analogue of Earth and planetary exploration. We consider rover transects at Cuprite, Nevada, and remote observations by NASA's Next- Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). We show that accounting for input uncertainties can benefit mineral detection methods such as constrained spectrum fitting. This suggests that operational uncertainty estimates could improve future NASA missions like the Earth Mineral dust source InvesTigation (EMIT) and the Lunar Trailblazer mission, as well as NASA's Decadal Surface Biology and Geology (SBG) Investigation.

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BibTeX Citation

  author={Thompson, D. R. and Braverman, A. and Brodrick, P. and Candela, A. and Carmon, N. and Clark, R. N. and Connelly, D. and Green, R. O. and Kokaly, R. F. and Li, L. and Mahowald, N. and Miller, R. L. and Okin, G. S. and Painter, T. H. and Swayze, G. A. and Turmon, M. and Susilouto, J. and Wettergreen, D. S.},
  title={Quantifying uncertainty for remote spectroscopy of surface composition},
  journal={Remote Sens. Environ.},

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RIS Citation

ID  - th03200x
AU  - Thompson, D. R.
AU  - Braverman, A.
AU  - Brodrick, P.
AU  - Candela, A.
AU  - Carmon, N.
AU  - Clark, R. N.
AU  - Connelly, D.
AU  - Green, R. O.
AU  - Kokaly, R. F.
AU  - Li, L.
AU  - Mahowald, N.
AU  - Miller, R. L.
AU  - Okin, G. S.
AU  - Painter, T. H.
AU  - Swayze, G. A.
AU  - Turmon, M.
AU  - Susilouto, J.
AU  - Wettergreen, D. S.
PY  - 2020
TI  - Quantifying uncertainty for remote spectroscopy of surface composition
JA  - Remote Sens. Environ.
VL  - 247
SP  - 111898
DO  - 10.1016/j.rse.2020.111898
ER  -

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