Gu, DG, Gillespie, AR, Kahle, AB, Palluconi, FD (2000). Autonomous atmospheric compensation (AAC) of high resolution hyperspectral thermal infrared remote-sensing imagery. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 38(6), 2557-2570.
Atmospheric emission and absorption significantly modify the thermal infrared (TIR) radiation spectra from Earth's land surface. A new algorithm, autonomous atmospheric compensation (AAC), was developed to estimate and compensate for the atmospheric effects, The algorithm estimates from hyperspectral TIR measurements two atmospheric index parameters, the transmittance ratio, and the path radiance difference between strong and weak absorption channels near the 11.73 mum water band. These two parameters depend on the atmospheric water and temperature distribution profiles, and thus, from them, the complete atmospheric transmittance and path radiance spectra can be predicted. The AAC algorithm is self-contained and needs no supplementary data. Its accuracy depends largely on instrument characteristics, particularly spectral and spatial resolution. Atmospheric conditions, especially humidity and temperature, and other meteorological parameters, also have some secondary impacts. The AAC algorithm was successfully applied to a hyperspectral TIR data set, and the results suggest its accuracy is comparable to that based on the in situ radiosonde measurements.