Calculation of Hue Angle and Inherent Optical Properties of Black Sea and Sea of Azov Water Based on Satellite Color Scanners Data

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription or Fee Access

Abstract

The study calculates the hue angles of the Black Sea and Sea of Azov water based on satellite and in situ measurements of the reflectance coefficient for 20192023. The correlation coefficient for the satellite and in situ hue angles is 0.92. Division of the reflectance spectra into subgroups according to the values of the hue angle is proposed for the study area. Satellite-derived values of absorption by dissolved organic matter(including detritus absorption) and backscattering by suspended particles have been compared in three ways: by empirical formulas for the hue angle, by a semianalytical algorithm for the spectral reflectance coefficient,and by the standard satellite algorithm (GIOP model). The empirical relationship is better at retrieving the absorption by dissolved organic matter than the standard satellite or semianalytical algorithms whereas for backscattering by suspended particles all three methods show similar quality of retrieving.

Full Text

Restricted Access

About the authors

E. N. Korchemkina

Marine Hydrophysical Institute of RAS

Author for correspondence.
Email: korchemkina@mhi-ras.ru
Russian Federation, Sevastopol

E. V. Mankovskaya

Marine Hydrophysical Institute of RAS

Email: korchemkina@mhi-ras.ru
Russian Federation, Sevastopol

References

  1. Копелевич О.В., Костяной А.Г. Использование биооптических параметров океана, определяемых по спутниковым данным, в качестве основных климатических переменных // Фундаментальная и прикладная климатология. 2018. Т. 3. С. 8–29. https://doi.org/10.21513/2410-8758-2018-3-8-29. EDN: YNFLOP
  2. Корчемкина Е.Н. Влияние дополнительной коррекции на соответствие данных дистанционного измерения коэффициента яркости 2-го уровня данным in situ для вод Черного моря // Труды XII Всероссийской конференции с международным участием “Современные проблемы оптики естественных вод”. М.: Издательство “ИО РАН”, 2023. С. 124–129. https://doi.org/10.29006/ 978-5-6051054-4-2-2023
  3. Корчемкина Е.Н., Маньковская Е.В. Спектральный коэффициент яркости, цветовые характеристики и относительная прозрачность вод Черного моря весной 2019 и 2021 годов: сравнительная изменчивость и эмпирические связи // Морской гидрофизический журнал. 2024. Т. 40. № 1. С. 5–20. EDN: HMPHDG
  4. Ли М.Е., Мартынов О.В. Измеритель коэффициента яркости для подспутниковых измерений биооптических параметров вод // Экологическая безопасность прибрежных и шельфовых вод и комплексное использование ресурсов шельфа. 2000. № 1. С. 163–173. EDN: BELAJW
  5. Ли М.Е., Шибанов Е.Б., Корчемкина Е.Н., Мартынов О.В. Определение концентрации примесей в морской воде по спектру яркости восходящего излучения // Морской гидрофизический журнал. 2015. № 6. С. 17–33. EDN: VHEWVT
  6. Маньковский В.И., Соловьев М.В., Маньковская Е.В. Гидрооптические характеристики Черного моря. Справочник. Севастополь: МГИ НАН Украины. 2009. С. 40–41.
  7. Оптика океана: В 2-х т. / Отв. ред. А.С. Монин. Москва: Наука, 1983. Т. 1. Физическая оптика океана. 371 с.; Т. 2. Прикладная оптика океана. 236 с.
  8. Algorithm Descriptions. 2018. https://oceancolor.gsfc.nasa.gov/atbd (дата обращения 26.06.2024)
  9. Churilova T., Efimova T., Moiseeva N. et al. Annual variability in light absorption by particles and colored dissolved organic matter in coastal waters of Crimea (the Black Sea) // Proceedings of SPIE. Irkutsk: SPIE, 2017. V. 10466: 23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics. 104664B. https://doi.org/10.1117/12.2288339
  10. Churilova T., Suslin V., Krivenko O. et al. Light absorption by phytoplankton in the upper mixed layer of the Black Sea: Seasonality and parametrization // Frontiers in Marine Science. 2017. V. 4. 90. https://doi.org/10.3389/fmars.2017.00090
  11. Korchemkina E.N., Kalinskaya D.V. Algorithm of additional correction of Level 2 remote sensing reflectance data using modelling of the optical properties of the Black Sea waters // Remote Sensing. 2022. V. 14. № 4. https://doi.org/10.3390/rs14040831
  12. Lee M.E., Shybanov E.B., Korchemkina E.N., Martynov O.V. Retrieval of concentrations of seawater natural components from reflectance spectrum // Proceedings of SPIE 22nd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, Tomsk, Russia, 29 November 2016 (100352Y). https://doi.org/10.1117/12.2247845
  13. Morel A. Optical properties of pure water and pure sea water // Optical Aspects of Oceanography / Edited by N.G. Jerlov, E.S. Nielson. New York: Academic Press, 1974. P. 1–24.
  14. Ocean Color Web. https://oceancolor.gsfc.nasa.gov/ (дата обращения 26.06.2024)
  15. Shybanov E., Papkova A., Korchemkina E., Suslin V. Blue Color Indices as a Reference for Remote Sensing of Black Sea Water // Remote Sens. 2023. V. 15. 3658. https://doi.org/10.3390/rs15143658
  16. Smith R.C., Baker K.S. Optical properties of the clearest natural waters (200–800 nm) // Applied Optics. 1981. V. 20. Iss. 2. P. 177–184. https://doi.org/10.1364/AO.20.000177
  17. Smith T., Guild J. The C.I.E. colorimetric standards and their use // Transactions of the Optical Society. 1931. V. 33. Iss. 3. P. 73–134. https://doi.org/10.1088/1475-4878/33/3/301
  18. Van der Woerd H.J., Wernand M.R. True colour classification of natural waters with medium-spectral resolution satellites: SeaWiFS, MODIS, MERIS and OLCI // Sensors. 2015. V. 15. Iss. 10. P. 25663–25680. https://doi.org/10.3390/s151025663
  19. Werdell P.J., Franz B.A., Bailey S.W. et al. Generalized ocean color inversion model for retrieving marine inherent optical properties // Applied Optics. 2013. V. 52. Iss. 10. P. 2019–2037. https://doi.org/10.1364/AO.52.002019
  20. Werdell J., Mckinna L., Boss E. et al. An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing // Progress in Oceanography. 2018. V. 160. P. 186–212. https://doi.org/10.1016/j.pocean.2018.01.001
  21. Zhao Y., Shen Q., Wang Q. et al. Recognition of water colour anomaly by using Hue Angle and Sentinel 2 image // Remote Sensing. 2020. V. 12(4). 716. https://doi.org/10.3390/rs12040716

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. The layout of the optical stations where measurements were carried out during the flights of the NIS “Professor Vodianitsky" in 2019-2023.

Download (443KB)
Indexing metadata
3. Fig. 2. Chromaticity diagram showing the correspondence of the chromaticity angle α relative to the white (xw, yw) point of the FU (Trout-Ole) scale colors [18, p. 25667].

Download (232KB)
Indexing metadata
4. Fig. 3. Comparison of the values of the chromaticity angle calculated from the data of full–scale measurements of AE (in situ) and from satellite data of Rrs (asatellite); red dots are data from MODIS/Aqua, MODIS/Terra, blue – OLCI/Sentinel-3A, OLCI/Sentinel-3B. Ovals and Roman numerals indicate the subgroups of the QN spectra (a possible intermediate subgroup is indicated by a dashed line). Straight lines are regression lines.

Download (169KB)
Indexing metadata
5. Fig. 4. The average spectra of CR and their standard deviations (shown by shading) for the three subgroups, identified by the angle of chromaticity of the waters.

Download (249KB)
Indexing metadata
6. Fig. 5. Distribution of the values of the chromaticity angle. The sizes of the symbols correspond to the angle range from 80° to 220°, the larger size corresponds to the smaller angle. For example, some values of the chromaticity angles are indicated.

Download (179KB)
Indexing metadata
7. Fig. 6. Comparison of the backscattering indices by suspended particles calculated from field measurements of QW and from satellite Rrs data in three ways: a – according to MODIS/Aqua, MODIS/Terra; b – according to OLCI/Sentinel-3A, OLCI/Sentinel-3B.

Download (427KB)
Indexing metadata
8. Fig. 7. Comparison of absorption rates by dissolved organic matter calculated from field measurements of QW and from satellite Rrs data in three ways: a – according to MODIS/Aqua, MODIS/Terra; b – according to OLCI/Sentinel-3A, OLCI/Sentinel-3B.

Download (381KB)
Indexing metadata

Copyright (c) 2025 Russian Academy of Sciences