Measuring the error between actual and estimated atmospherics and the effect on estimating reflectance profiles

Accurate target detection and classification of hyperspectral imagery require that the measurement by the imager matches as closely as possible the known “true” target as collected under controlled conditions. Therefore, the effect of the radiation source and the atmosphere must be factored out of the result before detection is attempted. Our objective is to investigate the relationship between uncertainty in the estimation of target spectra and uncertainty in the estimation of atmospherics. We apply a range of atmospheric profiles to a MODTRAN-based prediction of the radiative transfer effect. These profiles are taken from known distribution percentiles as obtained from historic meteorological measurements at the chosen site. We calculate the change in radiative transfer effects as measured by the Euclidean distance, given the range of atmospheric conditions in the historic profile, and show that changes in the atmospheric assumptions change the total transmission, spectral radiance, and estimated reflectance.