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The important step is correction of the effect of atmospheric on hyper-spectral imagery of the VIS "visible", short wave & NIR "near-infrared" spectral range. In general, the cause for limiting the use of hyperspectral images is the atmospheric effects, so, atmospheric correction is necessary for any accurate processing. In this work, two atmospheric correction techniques have been applied on Hyperspectral image. From the raw original image and also from the FLAASH and QUAC atmospheric corrected images the spectra of vegetation, water and soil were extracted. The acquisition data for study contained Hyperion bands for year "2015" images over each of the following regions: first region is the sedimentary plain in the central region of Republic of Iraq and the second region is a mountainous area of the northern regions of the Republic of Iraq. The survey will focus mainly on the precision of the atmospheric compensation algorithms by comparing the corrected bands location in the reflectance measurement of different surface types collected for each region. The results of two algorithms in the mountainous area that have terrain are best than the sedimentary plain area.

The atmospheric correction of satellite images is an important first step for different remote sensing applications such as estimation of vegetation indices. In atmospheric corrections, most uncertainties arise from temporal and spatial variations in aerosol types and quantities. Thus, considered validation estimate Aerosol is an essential step in the validation atmospheric correction algorithms. In the current study, two models of atmospheric correction algorithms ATCOR (ATCOR 3 and ATCOR 2) were applied to remove atmospheric effects of test sites in Middle part of Iraq. Statistical results of ATCOR 2 was shown to be successful in the urban parts to remove effective type of aerosol which could be chosen to process satellite images in areas under investigation.