Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters
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 c...
Published in: | European Journal of Remote Sensing |
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Language: | English |
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Online Access: | https://vb.ku.lt/KU:ELABAPDB29085394&prefLang=en_US |
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ftklaipedauniv:oai:elaba:29085394 2023-05-15T13:06:06+02:00 Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters 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 application/pdf https://vb.ku.lt/KU:ELABAPDB29085394&prefLang=en_US eng eng info:eu-repo/semantics/altIdentifier/doi/10.1080/22797254.2018.1457937 https://vb.ku.lt/object/elaba:29085394/29085394.pdf https://vb.ku.lt/KU:ELABAPDB29085394&prefLang=en_US info:eu-repo/semantics/openAccess European journal of remote sensing, Firenze : Associazione Italiana di Telerilevamento, 2018, vol. 51, no. 1, p. 525-542 eISSN 2279-7254 Icor atmospheric correction adjacency effects SIMEC Landsat-8 OLI Sentinel-2 MSI info:eu-repo/semantics/article 2018 ftklaipedauniv https://doi.org/10.1080/22797254.2018.1457937 2021-12-16T00:09:32Z 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 rededge and near-infrared region in relation to optical in situ measurements collected during field campaigns. Article in Journal/Newspaper Aerosol Robotic Network KU VL (Klaipėdos universitetas Virtual Library) European Journal of Remote Sensing 51 1 525 542 |
institution |
Open Polar |
collection |
KU VL (Klaipėdos universitetas Virtual Library) |
op_collection_id |
ftklaipedauniv |
language |
English |
topic |
Icor atmospheric correction adjacency effects SIMEC Landsat-8 OLI Sentinel-2 MSI |
spellingShingle |
Icor atmospheric correction adjacency effects SIMEC Landsat-8 OLI Sentinel-2 MSI 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. Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters |
topic_facet |
Icor atmospheric correction adjacency effects SIMEC Landsat-8 OLI Sentinel-2 MSI |
description |
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 rededge and near-infrared region in relation to optical in situ measurements collected during field campaigns. |
format |
Article in Journal/Newspaper |
author |
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. |
author_facet |
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. |
author_sort |
De Keukelaere, L. |
title |
Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters |
title_short |
Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters |
title_full |
Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters |
title_fullStr |
Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters |
title_full_unstemmed |
Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters |
title_sort |
atmospheric correction of landsat-8/oli and sentinel-2/msi data using icor algorithm: validation for coastal and inland waters |
publishDate |
2018 |
url |
https://vb.ku.lt/KU:ELABAPDB29085394&prefLang=en_US |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
European journal of remote sensing, Firenze : Associazione Italiana di Telerilevamento, 2018, vol. 51, no. 1, p. 525-542 eISSN 2279-7254 |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1080/22797254.2018.1457937 https://vb.ku.lt/object/elaba:29085394/29085394.pdf https://vb.ku.lt/KU:ELABAPDB29085394&prefLang=en_US |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1080/22797254.2018.1457937 |
container_title |
European Journal of Remote Sensing |
container_volume |
51 |
container_issue |
1 |
container_start_page |
525 |
op_container_end_page |
542 |
_version_ |
1766403380347928576 |