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Spectral and Radiometric Calibration of the Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG)

by Chapman, John W. , Bue, Brian D. , Green, Robert O. , Thompson, David R. , Eastwood, Michael L. , Helmlinger, Mark C. , Olson-Duvall, Winston , Geier, Sven , Lundeen, Sarah R.

in Accuracy / AVIRIS / bad pixel correction / Calibration / destripe / Earth science / Fields (mathematics) / image analysis / Infrared analysis / Infrared imaging / Infrared spectrometers / Laboratories / Markov chains / Mathematical models / Noise / Parameter estimation / probabilistic models / radiometry / Remote sensing / Sensors / spectrometers / spectroscopy / Statistical methods / uncertainty

2019

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Spectral and Radiometric Calibration of the Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG)

by Chapman, John W. , Bue, Brian D. , Green, Robert O. , Thompson, David R. , Eastwood, Michael L. , Helmlinger, Mark C. , Olson-Duvall, Winston , Geier, Sven , Lundeen, Sarah R.

2019

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Spectral and Radiometric Calibration of the Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG)

by Chapman, John W. , Bue, Brian D. , Green, Robert O. , Thompson, David R. , Eastwood, Michael L. , Helmlinger, Mark C. , Olson-Duvall, Winston , Geier, Sven , Lundeen, Sarah R.

2019

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Journal Article

Spectral and Radiometric Calibration of the Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG)

Chapman, John W.,

Bue, Brian D.,

Green, Robert O.,

Thompson, David R.,

Eastwood, Michael L.,

Helmlinger, Mark C.,

Olson-Duvall, Winston,

Geier, Sven,

Lundeen, Sarah R.

2019

Overview

We describe advanced spectral and radiometric calibration techniques developed for NASA’s Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). By employing both statistically rigorous analysis and utilizing in situ data to inform calibration procedures and parameter estimation, we can dramatically reduce undesirable artifacts and minimize uncertainties of calibration parameters notoriously difficult to characterize in the laboratory. We describe a novel approach for destriping imaging spectrometer data through minimizing a Markov Random Field model. We then detail statistical methodology for bad pixel correction of the instrument, followed by the laboratory and field protocols involved in the corrections and evaluate their effectiveness on historical data. Finally, we review the geometric processing procedure used in production of the radiometrically calibrated image data.

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Publisher

MDPI AG

Subject

Accuracy

/ AVIRIS

/ bad pixel correction

/ Calibration

/ destripe

/ Earth science

/ Fields (mathematics)