Radiative transfer code based estimation of atmospheric parameters for inversion of imaging spectrometer measured radiance to apparent surface reflectance

Surface reflectance is required to quantitatively investigate molecular absorption and particle scattering properties of materials on the Earth's surface. Atmospheric aerosol optical depth, surface pressure and water vapor are required to constrain a radiative transfer code for the inversion of measured spectral radiance to apparent surface reflectance. A suite of algorithms using nonlinear least squares fitting techniques are described that directly estimate these atmospheric parameters from spectral radiance measured by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The derived atmospheric parameters are used to constrain a radiative transfer code for the inversion of the imaging spectrometer radiance to apparent reflectance. The derived apparent reflectance is validated with respect to in situ measurement on the same target.