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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ftdoajarticles:oai:doaj.org/article:f616edbf7e074da292daa28c50b3bb5b 2023-05-15T13:06:11+02:00 Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters L. De Keukelaere S. Sterckx S. Adriaensen E. Knaeps I. Reusen C. Giardino M. Bresciani P. Hunter C. Neil D. Van der Zande D. Vaiciute 2018-01-01T00:00:00Z https://doi.org/10.1080/22797254.2018.1457937 https://doaj.org/article/f616edbf7e074da292daa28c50b3bb5b EN eng Taylor & Francis Group http://dx.doi.org/10.1080/22797254.2018.1457937 https://doaj.org/toc/2279-7254 2279-7254 doi:10.1080/22797254.2018.1457937 https://doaj.org/article/f616edbf7e074da292daa28c50b3bb5b European Journal of Remote Sensing, Vol 51, Iss 1, Pp 525-542 (2018) Icor atmospheric correction adjacency effects SIMEC Landsat-8 OLI Sentinel-2 MSI Oceanography GC1-1581 Geology QE1-996.5 article 2018 ftdoajarticles https://doi.org/10.1080/22797254.2018.1457937 2022-12-30T22:15:54Z 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. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles European Journal of Remote Sensing 51 1 525 542 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Icor atmospheric correction adjacency effects SIMEC Landsat-8 OLI Sentinel-2 MSI Oceanography GC1-1581 Geology QE1-996.5 |
spellingShingle |
Icor atmospheric correction adjacency effects SIMEC Landsat-8 OLI Sentinel-2 MSI Oceanography GC1-1581 Geology QE1-996.5 L. De Keukelaere S. Sterckx S. Adriaensen E. Knaeps I. Reusen C. Giardino M. Bresciani P. Hunter C. Neil D. Van der Zande D. Vaiciute 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 Oceanography GC1-1581 Geology QE1-996.5 |
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 red-edge and near-infrared region in relation to optical in situ measurements collected during field campaigns. |
format |
Article in Journal/Newspaper |
author |
L. De Keukelaere S. Sterckx S. Adriaensen E. Knaeps I. Reusen C. Giardino M. Bresciani P. Hunter C. Neil D. Van der Zande D. Vaiciute |
author_facet |
L. De Keukelaere S. Sterckx S. Adriaensen E. Knaeps I. Reusen C. Giardino M. Bresciani P. Hunter C. Neil D. Van der Zande D. Vaiciute |
author_sort |
L. De Keukelaere |
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 |
publisher |
Taylor & Francis Group |
publishDate |
2018 |
url |
https://doi.org/10.1080/22797254.2018.1457937 https://doaj.org/article/f616edbf7e074da292daa28c50b3bb5b |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
European Journal of Remote Sensing, Vol 51, Iss 1, Pp 525-542 (2018) |
op_relation |
http://dx.doi.org/10.1080/22797254.2018.1457937 https://doaj.org/toc/2279-7254 2279-7254 doi:10.1080/22797254.2018.1457937 https://doaj.org/article/f616edbf7e074da292daa28c50b3bb5b |
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_ |
1765995442593595392 |