Autonomous atmospheric compensation (AAC) of high resolution hyperspectralthermal infrared remote-sensing imagery

Atmospheric emission and absorption significantly modify the thermal infrar ed (TIR) radiation spectra from Earth's land surface. A new algorithm, auto nomous atmospheric compensation (AAC), was developed to estimate and compen sate for the atmospheric effects, The algorithm estimates from hyperspectra l TIR measurements two atmospheric index parameters, the transmittance rati o, and the path radiance difference between strong and weak absorption chan nels near the 11.73 mum water band. These two parameters depend on the atmo spheric water and temperature distribution profiles, and thus, from them, t he complete atmospheric transmittance and path radiance spectra can be pred icted. The AAC algorithm is self-contained and needs no supplementary data. Its accuracy depends largely on instrument characteristics, particularly s pectral and spatial resolution. Atmospheric conditions, especially humidity and temperature, and other meteorological parameters, also have some secon dary impacts. The AAC algorithm was successfully applied to a hyperspectral TIR data set, and the results suggest its accuracy is comparable to that b ased on the in situ radiosonde measurements.