The use of selected pseudo-invariant targets for the application of atmospheric correction in multi-temporal studies using satellite remotely sensed imagery

Abstract

Because atmospheric effects can have a significant impact on the data obtained from multi-spectral satellite remote sensing, it is frequently necessary to make corrections before any other image processing can be started. This paper describes a robust and relatively simple atmospheric correction method that uses pseudo-invariant targets (PITs) in conjunction with the empirical line method. The method is based on the selection of a number of suitable generic PITs, on the basis that they are large, distinctive in shape, and occur in many geographical areas. Whereas the multi-temporal normalization method corrects all images to a selected reference image, in this method images are simultaneously corrected using targets with a range of estimated surface reflectance values. The paper describes some applications of the method for a range of environmental studies involving water quality and air pollution monitoring, and mapping land-cover changes.