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This paper describes a simple, iterative atmospheric correction procedure based on the MODTRAN®5 radiative transfer code. Such a procedure receives in input a spectrally resolved at-sensor radiance image, evaluates the different contributions to received radiation, and corrects the effect of adjacency from surrounding pixels permitting the retrieval of ground reflectance spectrum for each pixel of the image. The procedure output is a spectral ground reflectance image obtained without the need of any user-provided a priori hypothesis. The novelty of the proposed method relies on its iterative approach for evaluating the contribution of surrounding pixels: a first run of the atmospheric correction procedure is performed by assuming that the spectral reflectance of the surrounding pixels is equal to that of the pixel under investigation. Such information is used in the subsequent iteration steps to estimate the spectral radiance of the surrounding pixels, in order to make a more accurate evaluation of the reflectance image. The results are here presented and discussed for two different cases: synthetic images produced with the hyperspectral simulation tool PRIMUS and real images acquired by CHRIS–PROBA sensor. The retrieved reflectance error drops after a few iterations, providing a quantitative estimate for the number of iterations needed. Relative error after the procedure converges is in the order of few percent, and the causes of remaining uncertainty in retrieved spectra are discussed.

A Fast Iterative Procedure for Adjacency Effects Correction on Remote Sensed Data