Evaluation of atmospheric correction to airborne hyperspectral data relying on radiative transfer concepts

Physically based atmospheric correction is one of the most important but also perilous radiometric corrections in remote-sensing imagery. The main objective of this work was to evaluate the efficiency of atmospheric correction algorithms, based not only on quantification of the changes induced but also on a step-by-step interpretation of the results, in association with the radiative transfer (RT) processes that occur in the atmosphere and on Earth. A four-level atmospheric correction scheme was applied to airborne hyperspectral visible/near-infrared (VNIR) imagery and the performance was evaluated. Each atmospheric correction level was more numerous than the previous following adjunctive assessment of the following parameters: (1) atmospheric influence, (2) the adjacency effect, (3) cast shadows, and (4) effects induced by the Earth’s surface reflectance anisotropy. Performance assessment showed that, even though a more complex atmospheric correction scheme resembles in greater detail the conditions under which the image acquisition was carried out, it is more sensitive to restrictions that arise from either the sensor’s characteristics or the algorithms and data used. Moreover, it was shown that evaluating atmospheric correction results using criteria based on RT concepts can considerably assist in the evaluation process.