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Next-generation orbital imaging spectrometers will generate unprecedented data volumes, demanding new methods to optimize storage and communication resources. Here, we demonstrate that onboard analysis can excise cloud-contaminated scenes, reducing data volumes while preserving science return. We calculate optimal cloud-screening parameters in advance, exploiting stable radiometric calibration and foreknowledge of illumination and viewing geometry. Channel thresholds expressed in raw instrument values can be then uploaded to the sensor where they execute in real time at gigabit-per-second (Gb/s) data rates. We present a decision theoretic method for setting these instrument parameters and characterize performance using a continuous three-year image archive from the “classic” Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-C). We then simulate the system onboard the International Space Station, where it provides factor-of-two improvements in data volume with negligible false positives. Finally, we describe a real-time demonstration onboard the AVIRIS Next Generation (AVIRIS-NG) flight platform during a recent science campaign. In this blind test, cloud screening is performed without error while keeping pace with instrument data rates. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]