Assessment of Atmospheric Correction Methods for Hyperspectral Remote Sensing Imagery Using Geospatial Techniques

Abstract

Atmospheric correction is a main problem in visible or near-infrared remote sensing images since the existence of the atmosphere continuously influences the radiation from the ground to the sensor. Hence, atmospheric correction is necessary. Remotely sensed imagery has noise affected by atmospheric particles that can unclear the image and make quantitative analysis unreliable. The aim of this research is to evaluate atmospheric correction methods for remotely sensed imagery using ENVI software to get accurate results. In this research, three methods of atmospheric correction have been selected depend on the essential parameters whether from the image or field for hyperspectral imagery by using ENVI software. These methods include: IAR Reflectance, Flat field correction, and Empirical Line Correction. The results showed the corrected images from three methods give better interpretation of Z-profile than original image which helps to determine the absorption feature and increase the possibility to get a good result after processing. IAR Reflectance method gives easier spectral curve to be interpreted when comparison between radiance spectrum and reflectance spectra than other correction methods.