A New Method for Retrieving Remote Sensing Reflectance from First-Level OLCI Satellite Data
The paper proposes an alternative method of atmospheric correction using the OLCI satellite data for the Black Sea as an example. Currently, for remote sensing problems, the standard Gordon and Wang atmospheric correction algorithm is used in most cases (GW94). Unfortunately, its operation is often...
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Russian Academy of Sciences, The Geophysical Center
2025-05-01
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| Series: | Russian Journal of Earth Sciences |
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| Online Access: | http://doi.org/10.2205/2025ES001014 |
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| author | Shybanov Evgeny Papkova Anna Stanislavovna |
| author_facet | Shybanov Evgeny Papkova Anna Stanislavovna |
| author_sort | Shybanov Evgeny |
| collection | DOAJ |
| description | The paper proposes an alternative method of atmospheric correction using the OLCI satellite data for the Black Sea as an example. Currently, for remote sensing problems, the standard Gordon and Wang atmospheric correction algorithm is used in most cases (GW94). Unfortunately, its operation is often accompanied by the appearance of negative values of the spectral radiance coefficient of the sea (remote sensing reflectance) 𝑅rs(𝜆) in the shortwave region, which means a sufficient number of physically incorrect values and subsequent incorrect calculation of the concentration of chlorophyll-a and yellow matter. In this paper, a simple algorithm is proposed, built exclusively on analytical formulas, where two procedures of interpolation and extrapolation are conceptually implemented simultaneously, extrapolation - via two channels, interpolation based on the constancy of the color index ratio (CI = 𝑅rs(412)/𝑅rs(443) = 0.8). Using individual examples of OLCI scanner data, the performance GW94 of the new algorithm was tested for different states of the atmosphere and sea surface by comparing the results with in-kind measurements of the AERONET-OC platforms, with Level-2 data and with the operation of the regional method of additional correction. The new algorithm was tested under the following conditions: clear atmosphere (presence of background aerosol), presence of dust aerosol, cloud boundaries, presence of sun glare, coccolithophore bloom. When analyzing a number of Sentinel 3A/3B satellite images, it was found that the new simple algorithm was, on average, better than the standard one, which means that there is a prospect for its improvement. The advantage of this approach is its universality and the possibility of its implementation for other water areas, if there are patterns in the variability of the "blue" color index. |
| format | Article |
| id | doaj-art-e049124a925e4486a3dbabb018752acf |
| institution | DOAJ |
| issn | 1681-1208 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Russian Academy of Sciences, The Geophysical Center |
| record_format | Article |
| series | Russian Journal of Earth Sciences |
| spelling | doaj-art-e049124a925e4486a3dbabb018752acf2025-08-20T03:09:25ZengRussian Academy of Sciences, The Geophysical CenterRussian Journal of Earth Sciences1681-12082025-05-0125311910.2205/2025ES001014A New Method for Retrieving Remote Sensing Reflectance from First-Level OLCI Satellite DataShybanov Evgeny0https://orcid.org/0000-0001-7943-305XPapkova Anna Stanislavovna1https://orcid.org/0000-0002-4304-4877Russian Academy of Sciences Sea Hydrophysical InstituteRussian Academy of Sciences Sea Hydrophysical InstituteThe paper proposes an alternative method of atmospheric correction using the OLCI satellite data for the Black Sea as an example. Currently, for remote sensing problems, the standard Gordon and Wang atmospheric correction algorithm is used in most cases (GW94). Unfortunately, its operation is often accompanied by the appearance of negative values of the spectral radiance coefficient of the sea (remote sensing reflectance) 𝑅rs(𝜆) in the shortwave region, which means a sufficient number of physically incorrect values and subsequent incorrect calculation of the concentration of chlorophyll-a and yellow matter. In this paper, a simple algorithm is proposed, built exclusively on analytical formulas, where two procedures of interpolation and extrapolation are conceptually implemented simultaneously, extrapolation - via two channels, interpolation based on the constancy of the color index ratio (CI = 𝑅rs(412)/𝑅rs(443) = 0.8). Using individual examples of OLCI scanner data, the performance GW94 of the new algorithm was tested for different states of the atmosphere and sea surface by comparing the results with in-kind measurements of the AERONET-OC platforms, with Level-2 data and with the operation of the regional method of additional correction. The new algorithm was tested under the following conditions: clear atmosphere (presence of background aerosol), presence of dust aerosol, cloud boundaries, presence of sun glare, coccolithophore bloom. When analyzing a number of Sentinel 3A/3B satellite images, it was found that the new simple algorithm was, on average, better than the standard one, which means that there is a prospect for its improvement. The advantage of this approach is its universality and the possibility of its implementation for other water areas, if there are patterns in the variability of the "blue" color index.http://doi.org/10.2205/2025ES001014aerosol atmospheric correction remote sensing reflectance sea optics color index interpolation Black Sea |
| spellingShingle | Shybanov Evgeny Papkova Anna Stanislavovna A New Method for Retrieving Remote Sensing Reflectance from First-Level OLCI Satellite Data Russian Journal of Earth Sciences aerosol atmospheric correction remote sensing reflectance sea optics color index interpolation Black Sea |
| title | A New Method for Retrieving Remote Sensing Reflectance from First-Level OLCI Satellite Data |
| title_full | A New Method for Retrieving Remote Sensing Reflectance from First-Level OLCI Satellite Data |
| title_fullStr | A New Method for Retrieving Remote Sensing Reflectance from First-Level OLCI Satellite Data |
| title_full_unstemmed | A New Method for Retrieving Remote Sensing Reflectance from First-Level OLCI Satellite Data |
| title_short | A New Method for Retrieving Remote Sensing Reflectance from First-Level OLCI Satellite Data |
| title_sort | new method for retrieving remote sensing reflectance from first level olci satellite data |
| topic | aerosol atmospheric correction remote sensing reflectance sea optics color index interpolation Black Sea |
| url | http://doi.org/10.2205/2025ES001014 |
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