MONTE-CARLO BASED DETERMINATION OF MEASUREMENT UNCERTAINTY FOR IMAGING SPECTROMETERS

To enable traceability of imaging spectrometer data, the associated measurement uncertainties have to be provided reliably. Here, a new tool for a Monte-Carlo-type measurement uncertainty propagation for the uncertainties that originate from the spectrometer itself is described. For this, an instrument model of the imaging spectrometer ROSIS is used. Combined uncertainties are then derived for radiometrically and spectrally calibrated data using a synthetic at-sensor radiance spectrum as input. By coupling this new software tool with an inverse modeling program, the measurement uncertainties are propagated for an exemplary water data product.