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Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters
Author(s): De Keukelaere, Liesbeth
Sterckx, Sindy
Adriaensen, Stefan
Knaeps, Els
Reusen, Ils
Giardino, Claudia
Bresciani, Mariano
Hunter, Peter
Neil, Claire
Van der Zande, Dimitry
Vaiciute, Diana
Keywords: Icor
atmospheric correction
adjacency effects
Landsat-8 OLI
Sentinel-2 MSI
Issue Date: 31-Dec-2018
Citation: De Keukelaere L, Sterckx S, Adriaensen S, Knaeps E, Reusen I, Giardino C, Bresciani M, Hunter P, Neil C, Van der Zande D & Vaiciute D (2018) Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters, European Journal of Remote Sensing, 51 (1), pp. 525-542.
Abstract: Image correction for atmospheric effects (iCOR) is an atmospheric correction tool that can process satellite data collected over coastal, inland or transitional waters and land. The tool is adaptable with minimal effort to hyper- or multi-spectral radiometric sensors. By using a single atmospheric correction implementation for land and water, discontinuities in reflectance within one scene are reduced. iCOR derives aerosol optical thickness from the image and allows for adjacency correction, which is SIMilarity Environmental Correction (SIMEC) over water. This paper illustrates the performance of iCOR for Landsat-8 OLI and Sentinel-2 MSI data acquired over water. An intercomparison of water leaving reflectance between iCOR and Aerosol Robotic Network – Ocean Color provided a quantitative assessment of performance and produced coefficient of determination (R2) higher than 0.88 in all wavebands except the 865 nm band. For inland waters, the SIMEC adjacency correction improved results in the red-edge and near-infrared region in relation to optical in situ measurements collected during field campaigns.
DOI Link: 10.1080/22797254.2018.1457937
Rights: © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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