Passive optical sensing of river plumes from board of a vessel using gyro-stabilized complex EMMA
https://doi.org/10.7868/S2073667320020124
Abstract
The greatest variability of the ecological state of coastal waters is observed in the areas of river mouths. River plumes can differ from the surrounding sea water both in the composition of impurities and in their concentration. Moreover, the size and position of plumes are characterized by strong variability. Monitoring of such water areas requires measurements with high spatial and temporal resolution. The possibility of operative estimation of natural sea water components distribution at a river plume by the method of passive optical sensing from board a vessel was demonstrated at the Caucasian coast of the Black Sea. Portable three-channel hyperspectral complex EMMA (Ecological Monitoring of Marine Areas) installed on a gyro-stabilized platform was used for this purpose. The data of the EMMA complex were processed by a special algorithm, which allowed obtaining light absorption spectra of sea water and estimating concentrations of its natural components. The efficiency of the gyro-stabilized complex is discussed in comparison with measurements without stabilization. It has been shown that it is possible to obtain estimates of the concentration of the main natural seawater constituents with a gyro-stabilized complex EMMA under conditions of uneven illumination at low sun position, which significantly expands the time frame for measurements. The presented complex may be useful for ground truth measurements in coastal areas of the ocean or inland seas with river plumes.
Keywords
passive optical remote sensing,
sea radiance coefficient spectrum,
sea water absorption,
concentration of seawater suspended matter and coloured organic matter,
river plume
Supporting agencies: The research was carried out under the support of Russian Foundation for Basic Research (RFBR) № 18–05–80049 (data processing algorithms) as well as within the framework of the State Assignment № 0149–2019–0003 (data analysis).
About the Authors
I. V. Goncharenko
Shirshov Institute of Oceanology RAS
Russian Federation
Russian Federation
117997, Nahimovsky Prospekt, 36, Moscow
V. V. Rostovtseva
Shirshov Institute of Oceanology RAS
Russian Federation
Russian Federation
117997, Nahimovsky Prospekt, 36, Moscow
References
1. Mouw C.B., Greb S., Aurin D., DiGiacomo P.M., Lee Z-P., Twardowski M., Binding C., Hu C., Ma R., Moore T., Moses W., Craig S. E. Aquatic color radiometry remote sensing of coastal and inland waters: Challenges and recommendations for future satellite missions. Remote Sens. Environ. 2015, 160, 15–30.
2. Schaeffer B.A., Schaeffer K.G., Keith D., Lunetta R.S., Conmy R., Gould R.W. Barriers to adopting satellite remote sensing for water quality management. Int. J. Remote Sens. 2013, 34, 7534–7544.
3. Tyler A.N., Hunter P.D., Spyrakos E., Groom S., Constantinescu A.M., Kitchen J. Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters. Sci. Total Environ. 2016, 572, 1307–1321.
4. Hestir E.L., Brando V.E., Bresciani M., Giardino C., Matta E., Villa P., Dekker A.G. Measuring freshwater aquatic ecosystems: The need for a hyperspectral global mapping satellite mission. Remote Sens. Environ. 2015, 167, 181–195.
5. Palmer S.C.J., Kutser T., Hunter P.D. Remote sensing of inland waters: Challenges, progress and future directions. Remote Sens. Environ. 2015, 157, 1–8.
6. Spyrakos E., O’Donnell R., Hunter P.D., Miller C., Scott M., Simis S.G.H., Neil C., Barbosa C.C.F., Binding C.E., Bradt S. et al. Optical types of inland and coastal waters. Limnol. Oceanogr. 2018, 63, 846–870.
7. Le C., Li Y., Zha Y., Sun D., Huang C., Zhang H. Remote estimation of chlorophyll a in optically complex waters based on optical classification. Remote Sens. Environ. 2011, 115, 725–737.
8. Huang C.C., Li Y.M., Yang H., Li J.S., Chen X., Sun D.Y., Le C.F., Zou J., Xu L.J. Assessment of water constituents in highly turbid productive water by optimization bio-optical retrieval model after optical classification. J. Hydrol. 2014, 519, 1572–1583.
9. Alikas K., Ansko I., Vabson V., Ansper A., Kangro K., Uudeberg K., Ligi M. Consistency of Radiometric Satellite Data over Lakes and Coastal Waters with Local Field Measurements. Remote Sens. 2020, 12, 616. doi:10.3390/rs12040616
10. Yushmanova A., Kopelevich O., Vazyulya S., Sahling I. Inter-Annual Variability of the Seawater Light Absorption in Surface Layer of the Northeastern Black Sea in Connection with Hydrometeorological Factors. J. Mar. Sci. Eng. 2019, 7, 326. doi:10.3390/jmse7090326
11. Konovalov B.V., Kravchishina M.D., Belyaev N.A., Novigatsky A.N. Determination of the concentration of mineral particles and suspended organic substance based on their spectral absorption. Oceanology. 2014, 54(5), 660–667.
12. Glukhovets D.I., Sheberstov S.V., Kopelevich O.V., Zaytseva A.F., Pogosyan S.I. Measuring the sea water absorption factor using integrating sphere. Light & Engineering. 2018, 26, 1, 120–126.
13. Dörnhöfer K., Klinger P., Heege T., Oppelt N. Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake. Sci. Total Environ. 2018, 612, 1200–1214.
14. Bresciani M., Pinardi M., Free G. et al. The Use of Multisource Optical Sensors to Study Phytoplankton Spatio-Temporal Variation in a Shallow Turbid Lake. Water. 2020, 12, 284. doi:10.3390/w12010284
15. Matyushenko V.A., Pelevin V.N., Rostovtseva V.V. Measurement of the Sea Radiance Coefficient with Three-Channel Spectrophotometer from board a Research Ship. Atmospheric and Oceanic Optics. 1996, 9, 5, 421–424.
16. Mobley C.D. Estimation of the remote sensing reflectance from above–water methods. Appl. Optics. 1999, 38, 7442–7455.
17. Hommersom A., Kratzer S., Laanen M., Ansko I., Ligi M., Bresciani M., Giardino C., Beltrán-Abaunza J.M., Moore G., Wernand M., Peters S. Intercomparison in the field between the new WISP-3 and other radiometers (TriOS Ramses, ASD FieldSpec, and TACCS). J. Appl. Rem. Sens. 2012, 6, 1, 1–21.
18. Simis S.G.H., Olsson J. Unattended processing of shipborne hyperspectral reflectance measurements. Remote Sens. Environ. 2013, 135, 202–212.
19. Peters S., Laanen M., Groetsch P., Ghezehegn S., Poser K., Hommersom A., De Reus E., Spaias L. WISPstation: A new autonomous above water radiometer system. Proc. Ocean Optics XXIV Conf., Dubrovnik, Croatia, 2018.
20. Ruddick K., De Cauwer V., Park Y., Moore G. Seaborne measurements of near infrared water-leaving reflectance: The similarity spectrum for turbid waters. Limnol. Oceanogr. 2006, 51, 1167–1179.
21. Goncharenko I.V., Rostovtseva V.V., Konovalov B.V. Using of new shipborne complex for passive optical remote sensing for obtaining distribution of natural admixtures in coastal waters. Fundamentalnaya i Prikladnaya Gidrofizika. 2018, 11, 3, 97–101 (in Russian).
22. Rostovtseva V.V. Method for sea water absorption spectra estimation on the basis of shipboard passive remote sensing data and pure sea water properties. Atmospheric and Oceanic Optics. 2016, 29, 2, 162–170.
23. Rostovtseva V.V., Konovalov B.V., Goncharenko I.V., Khlebnikov D.V. Method for estimating admixture content in seawater using operative spectrophotometry. Oceanology. 2017, 57, 4, 505–519.
24. Wozniak B., Dera J. Light Absorption in Sea Water. New York, Springer Science+Business Media, LLC. 2007.
Review
For citations:
Goncharenko I.V., Rostovtseva V.V. Passive optical sensing of river plumes from board of a vessel using gyro-stabilized complex EMMA. Fundamental and Applied Hydrophysics. 2020;13(2):96-102. https://doi.org/10.7868/S2073667320020124
Views:
98
Email this article 