Atmospheric parameterization for model-based thermal infrared atmospheric correction of spectral imagery

Model-based atmospheric correction of multi-spectral and hyperspectral imagery (MSI/HSI) typically involves searching through a look-up table (LUT) of potential atmospheric representations for a best fit, based on some fit criterion. These representations are generated using a radiation transport model such as MODTRAN. The parameter space covered by the LUT is defined to cover the likely atmospheric conditions encountered by the sensor that affect observed radiance over the spectral region covered by the sensor. For instance, aerosols play an important role in the visible through SWIR (450-2500 nm) but a minor role in the thermal IR, where water column content and atmospheric temperature are critical. We investigate the sampling and representation of the atmospheric parameter space in the thermal IR as it effects retrieval of the atmosphere. Using the SMACC convex projection technique we evaluate selection of significant basis members from a broadly-based LUT. We apply SMACC selected endmembers to solve for an arbitrary atmosphere.