Development of a line-by-line-based atmosphere removal algorithm for airborne and spaceborne imaging spectrometers

In recent years, spectral imaging data have been acquired with a number of airborne imaging spectrometers. Similar data will soon be collected with the NASA HyperSpectral Imager (HSI) instrument from the Lewis spacecraft. The majority of users of imaging spectrometer data are interested in studying surface properties. The atmospheric absorption and scattering effects must be removed from imaging spectrometer data, so that surface reflectance spectra can be derived. Previously, we developed and updated an operational atmosphere removal algorithm (ATREM), which used the Malkmus narrow band model for modeling atmospheric gaseous transmittances. The narrow band model does a reasonably good job in modeling spectra at a resolution of 10 nm or coarser. Imaging spectrometers with spectral resolutions finer than 10 nm are now available. The narrow band model is not quite suitable for modeling data collected with these spectrometers. In this paper, we describe the development of a line-by-line-based algorithm for removing atmospheric effects from imaging spectrometer data. We also discuss issues related to sampling and spectral resolution.