Evaluation of Different Atmospheric Correction Algorithms for Eo-1 Hyperion Imagery

Hyperspectral remote sensing is a powerful tool in discriminating lithological units and in preparation of mineral maps. Hyperion is a space borne sensor of Hyperspectral imagery having 220 channels within the 400 nm to 2500 nm wavelength range. Although the technical specifications of the sensor are quite high, in the operational stage there exist many nuisances like atmosphere. The presence of atmosphere with aerosols and gases alters the reflected signal from the surface resulting in a decrease in the quality of the Hyperion image. In order to obtain accurate and reliable results, atmospheric correction must be carried out for Hyperion data. There are many atmospheric correction algorithms based on MODTRAN or LOWTRAN in literature and/or in commercial use. In this study, the Atmospheric CORrection Now (ACORN), the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), and ATmospheric CORrection (ATCOR 2-3) atmospheric correction algorithms were tested for atmospheric correction of Hyperion data. Test site is located on Central Anatolia having sparse vegetation cover. Both the obtained resultant images and the whole spectral signatures from the field samples were compared with cross correlations of whole spectra and specific wavelengths in spectral domain. Despite the compromises in different wavelength regions ACORN is found to be a slightly better corrector algorithm for natural earth materials through lithological and mineralogical mapping needs.