Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season
This study aimed to assess the applicability of global bio-optical algorithms for the estimation of chlorophyll-a (chl-a) concentration (C) and develop regional empirical bio-optical algorithms for estimating C and colored dissolved organic matter (CDOM) content (D) from ocean remote sensing reflect...
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ftmdpi:oai:mdpi.com:/2072-4292/14/22/5797/ 2023-08-20T03:59:37+02:00 Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season Pavel A. Salyuk Igor E. Stepochkin Ekaterina B. Sokolova Svetlana P. Pugach Vasiliy A. Kachur Irina I. Pipko agris 2022-11-16 application/pdf https://doi.org/10.3390/rs14225797 EN eng Multidisciplinary Digital Publishing Institute Ocean Remote Sensing https://dx.doi.org/10.3390/rs14225797 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 22; Pages: 5797 chlorophyll-a colored dissolved organic matter remote sensed reflectance spectral response function hyperspectral multispectral band ratio index Anadyr Bay Anadyr River Text 2022 ftmdpi https://doi.org/10.3390/rs14225797 2023-08-01T07:22:33Z This study aimed to assess the applicability of global bio-optical algorithms for the estimation of chlorophyll-a (chl-a) concentration (C) and develop regional empirical bio-optical algorithms for estimating C and colored dissolved organic matter (CDOM) content (D) from ocean remote sensing reflectance spectra in the western part of the Bering Sea in the late summer period. The analysis took into account possible problems with the different relative contributions of phytoplankton and CDOM to water-leaving radiance and possible errors associated with the atmosphere correction procedure for ocean color satellite data. Shipborne remote sensing measurements obtained using an above-water hyperspectral ASD HandHeld spectroradiometer, satellite measurements collected via MODIS and VIIRS radiometers, and in situ measurements of C and D in seawater were used. The simulated values of the different multispectral satellite radiometers with daily or 2-day global coverage, obtained by applying the corresponding spectral response functions to ship hyperspectral data, were also analyzed. In this paper, a list of recommended regional bio-optical algorithms is presented. Recommendations are given depending on the possible quality of atmospheric correction and the purpose of use. To obtain more precise estimations of C, OC3/OC4-like algorithms should be used. If the atmosphere correction is poor, then use OC2-like algorithms in which spectral bands in the 476–539 nm range should be used to estimate C and bands near 443 nm to estimate D; however, in the last case, this will provide only the order of magnitude. To estimate more independent fields of C and D, it is necessary to use a spectral range of 501–539 nm for chl-a and bands near 412 nm in the case of modern satellite radiometers (e.g., OLCI or SGLI), for which this band is not the first. Additionally, we showed that global bio-optical algorithms can be applied with acceptable accuracy and similar recommendations. Text Anadyr Anadyr' Bering Sea MDPI Open Access Publishing Bering Sea Anadyr ENVELOPE(177.510,177.510,64.734,64.734) Anadyr’ ENVELOPE(176.233,176.233,64.882,64.882) Anadyr River ENVELOPE(177.924,177.924,64.489,64.489) Remote Sensing 14 22 5797 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
chlorophyll-a colored dissolved organic matter remote sensed reflectance spectral response function hyperspectral multispectral band ratio index Anadyr Bay Anadyr River |
spellingShingle |
chlorophyll-a colored dissolved organic matter remote sensed reflectance spectral response function hyperspectral multispectral band ratio index Anadyr Bay Anadyr River Pavel A. Salyuk Igor E. Stepochkin Ekaterina B. Sokolova Svetlana P. Pugach Vasiliy A. Kachur Irina I. Pipko Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season |
topic_facet |
chlorophyll-a colored dissolved organic matter remote sensed reflectance spectral response function hyperspectral multispectral band ratio index Anadyr Bay Anadyr River |
description |
This study aimed to assess the applicability of global bio-optical algorithms for the estimation of chlorophyll-a (chl-a) concentration (C) and develop regional empirical bio-optical algorithms for estimating C and colored dissolved organic matter (CDOM) content (D) from ocean remote sensing reflectance spectra in the western part of the Bering Sea in the late summer period. The analysis took into account possible problems with the different relative contributions of phytoplankton and CDOM to water-leaving radiance and possible errors associated with the atmosphere correction procedure for ocean color satellite data. Shipborne remote sensing measurements obtained using an above-water hyperspectral ASD HandHeld spectroradiometer, satellite measurements collected via MODIS and VIIRS radiometers, and in situ measurements of C and D in seawater were used. The simulated values of the different multispectral satellite radiometers with daily or 2-day global coverage, obtained by applying the corresponding spectral response functions to ship hyperspectral data, were also analyzed. In this paper, a list of recommended regional bio-optical algorithms is presented. Recommendations are given depending on the possible quality of atmospheric correction and the purpose of use. To obtain more precise estimations of C, OC3/OC4-like algorithms should be used. If the atmosphere correction is poor, then use OC2-like algorithms in which spectral bands in the 476–539 nm range should be used to estimate C and bands near 443 nm to estimate D; however, in the last case, this will provide only the order of magnitude. To estimate more independent fields of C and D, it is necessary to use a spectral range of 501–539 nm for chl-a and bands near 412 nm in the case of modern satellite radiometers (e.g., OLCI or SGLI), for which this band is not the first. Additionally, we showed that global bio-optical algorithms can be applied with acceptable accuracy and similar recommendations. |
format |
Text |
author |
Pavel A. Salyuk Igor E. Stepochkin Ekaterina B. Sokolova Svetlana P. Pugach Vasiliy A. Kachur Irina I. Pipko |
author_facet |
Pavel A. Salyuk Igor E. Stepochkin Ekaterina B. Sokolova Svetlana P. Pugach Vasiliy A. Kachur Irina I. Pipko |
author_sort |
Pavel A. Salyuk |
title |
Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season |
title_short |
Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season |
title_full |
Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season |
title_fullStr |
Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season |
title_full_unstemmed |
Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season |
title_sort |
developing and using empirical bio-optical algorithms in the western part of the bering sea in the late summer season |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14225797 |
op_coverage |
agris |
long_lat |
ENVELOPE(177.510,177.510,64.734,64.734) ENVELOPE(176.233,176.233,64.882,64.882) ENVELOPE(177.924,177.924,64.489,64.489) |
geographic |
Bering Sea Anadyr Anadyr’ Anadyr River |
geographic_facet |
Bering Sea Anadyr Anadyr’ Anadyr River |
genre |
Anadyr Anadyr' Bering Sea |
genre_facet |
Anadyr Anadyr' Bering Sea |
op_source |
Remote Sensing; Volume 14; Issue 22; Pages: 5797 |
op_relation |
Ocean Remote Sensing https://dx.doi.org/10.3390/rs14225797 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs14225797 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
22 |
container_start_page |
5797 |
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1774713778227642368 |