Abstract

In satellite-based and airborne imagery, the observed radiances reflected by a certain pixel at the surface are additionally influenced by reflections from the neighboring surface pixels and multiple scatterings due to atmospheric components (mainly cloud and aerosol particles) into the observational solid angle of the imaging camera. This phenomenon is commonly referred to as the atmospheric adjacency effect. This three-dimensional (3D) radiative transfer effect is caused by spatial inhomogeneities of the surface reflectivity and the atmospheric properties. Based on the recently published 3D radiative transfer code LEIPSIC (Light Estimator Including Polarization, Surface Inhomogeneities, and Clouds), a new atmospheric correction (AC) algorithm is proposed to consider for the atmospheric adjacency effect when estimating the surface reflectivity from satellite or airborne imagery. The effectiveness of the new AC algorithm is quantified and compared to the results based on the independent pixel approximation (IPA) radiative transfer approach. It is shown that the image blurring caused by the atmospheric adjacency effect and the error of reflectivity retrievals are reduced by 80% using the new AC algorithm. Furthermore, the simulations demonstrate that the vertical profile of the atmospheric properties is crucial in determining the quality of the AC.

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