Skip to main content

Satellite Instrumentation and Technique for Monitoring of Seawater Quality

  • Chapter
  • First Online:
Instrumentation and Measurement Technologies for Water Cycle Management

Part of the book series: Springer Water ((SPWA))

Abstract

The chapter provides a brief overview of satellite instrumentation, techniques and methods for monitoring of seawater quality (oil pollution, suspended matter, and algae bloom). Monitoring of oil pollution from space is usually carried out using the Synthetic Aperture Radar remote sensing systems, but under certain conditions, for example, in the zone of the sunglint, optical imagery is also very effective. Ocean color scanners are unique instrumentation for detection and monitoring of suspended matter (turbid waters) and chlorophyll-a (algae bloom) concentrations in the surface layer of the ocean. As any remote, in-situ or laboratory method, the ocean color scanners have a set of advantages (multispectral approach, high spectral resolution, high spatial resolution, etc.) as well as disadvantages which include dependence on the sunlight (there are no optical imagery during the night and Polar night) and clouds, dependence of the swath and repetition period on the spatial resolution of the sensor, etc. Application of the optical satellite remote sensing systems is illustrated by several examples of oil spill detection, turbid waters, and algal bloom in different seas of the World Ocean, and inland seas. Natural processes like wind-wave mixing in the coastal zone, river runoff, runoff from shallow lagoons, and algae bloom, as well as anthropogenic impact related to offshore and coastal mining, construction of ports and fairways, laying of underwater pipelines and cables, significantly impact seawater quality in the coastal zone of the World Ocean, and inland seas.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Algorithm Descriptions (2021). https://oceancolor.gsfc.nasa.gov/atbd/. Accessed on 09.03.2021.

  2. Berdeal I, Hickey B, Kawase M (2002) Influence of wind stress and ambient flow on high discharge river plume. J Geophys Res 107(C9):3130. https://doi.org/10.1029/2001JC000932

    Article  Google Scholar 

  3. Brockmann C, Doerffer R, Peters M, Kerstin S, Embacher S, Ruescas A (2016) Evolution of the C2RCC neural network for sentinel 2 and 3 for the retrieval of ocean colour products in normal and extreme optically complex waters. In: Living planet symposium, proceedings of the esa living planet symposium. 740. ISBN 978-92-9221-305-3

    Google Scholar 

  4. Bukanova T, Kopelevich O, Vazyulya S, Bubnova E, Sahling I (2018) Suspended matter distribution in the south-eastern Baltic Sea from satellite and in situ data. Int J Remote Sensing. https://doi.org/10.1080/01431161.2018.1519290

    Article  Google Scholar 

  5. CEOS (2021) The CEOS database: mission, instruments and measurements. http://database.eohandbook.com. Accessed on 09.03.2021

  6. Carpenter A (ed) (2016) Oil pollution in the North Sea. Springer International Publishing AG, Cham, Switzerland, 312 p. https://doi.org/10.1007/978-3-319-23901-9

  7. Carpenter A, Kostianoy AG (eds) (2018a) Oil pollution in the Mediterranean Sea: Part I—the international context. Springer International Publishing AG, Cham, Switzerland, 350 pp. https://doi.org/10.1007/978-3-030-12236-2

  8. Carpenter A, Kostianoy AG (eds) (2018b) Oil pollution in the Mediterranean Sea: Part II—national case studies. Springer International Publishing AG, Cham, Switzerland, 291p. https://doi.org/10.1007/978-3-030-11138-0

  9. Carpenter A, Kostianoy AG (2018c) Conclusions for Part I: the international context. In: Carpenter A, Kostianoy AG (eds) Oil pollution in the Mediterranean Sea: Part I—the international context. Springer International Publishing AG, Cham, Switzerland, pp 325–344

    Google Scholar 

  10. Chen J, D’Sa E, Cui T, Zhang X (2013) A semi-analytical total suspended sediment retrieval model in turbid coastal waters: a case study in Changjiang river estuary. Opt Express 21:13018–13031. https://doi.org/10.1364/oe.21.013018

    Article  ADS  PubMed  Google Scholar 

  11. Coble PG (2007) Marine optical biogeochemistry: the chemistry of ocean color. Chem Rev 107:402–418. https://doi.org/10.1021/cr050350

  12. Doerffer R, Fiseher J (1994) Concentration of chlorophyll, suspended matter, and gelbstoff case II water derived from satellite coastal zone color scanner data with inverse modeling methods. J Geophys Res 99(C4):7457–7466

    Article  ADS  CAS  Google Scholar 

  13. Doerffer R, Schiller H (2007) The MERIS Case 2 water algorithm. Int J Remote Sens 28(3–4):517–535. https://doi.org/10.1080/01431160600821127

    Article  Google Scholar 

  14. Doxaran D, Froidefond JM, Castaing P (2002) A reflectance band ratio used to estimate suspended matter concentrations in sediment-dominated coastal waters. Int J Remote Sens 23:5079–5085. https://doi.org/10.1080/0143116021000009912

    Article  Google Scholar 

  15. Ermakov S, Kapustin I, Molkov A, Leshev G, Danilicheva O, Sergievskaya I (2018) Remote sensing of evolution of oil spills on the water surface. In: Proceedings of SPIE 10784, Remote sensing of the ocean, sea ice, coastal waters, and large water regions. 107840L. https://doi.org/10.1117/12.2325745

  16. Frouin RR, McPherson J, Ueyoshi K, Franz BA (2012) A time series of photosynthetically available radiation at the ocean surface from SeaWiFS and MODIS data. In: Proceedings of SPIE, vol 8525. 852519 (December 11, 2012). https://doi.org/10.1117/12.9812642012

  17. Gower J, Doerffer R, Borstad GA (1999) Interpretation of the 685 nm peak in water-leaving radiance spectra in terms of fluorescence, absorption and scattering, and its observation by MERIS. Int J Remote Sens 20(9):1771–1786. https://doi.org/10.1080/014311699212470

  18. Grishin N, Kostianoy A (2012a) Satellite monitoring of suspended matter pollution resulted from the Nord Stream gas pipeline construction in Russian waters of the Baltic Sea in 2010–2011. Int Water Technol J 2(1):80–89

    Google Scholar 

  19. Grishin NN, Kostianoy AG (2012b) On satellite monitoring of suspended matter transport during the construction of an offshore gas pipeline Nord Stream in Russian waters of the Baltic Sea in 2010. Current problems in remote sensing of the Earth from space, vol 9, no 1, pp 167–175 (in Russian)

    Google Scholar 

  20. Grishin NN, Kostianoy AG (2013) The use of satellite monitoring of suspended matter transport for the assessment of transboundary environmental impact of construction the Russian section of the offshore gas pipeline Nord Stream. Current problems in remote sensing of the Earth from space, vol 10, no 1, pp 303–319 (in Russian)

    Google Scholar 

  21. Güttler FN, Niculescu S, Gohin F (2013) Turbidity retrieval and monitoring of Danube Delta waters using multi-sensor optical remote sensing data: an integrated view from the delta plain lakes to the western–northwestern Black Sea coastal zone. Remote Sens Environ 132:86–101. https://doi.org/10.1016/j.rse.2013.01.009

  22. HELCOM (2018) State of the Baltic Sea—Second HELCOM holistic assessment 2011–2016. In: Baltic Sea Environment Proceedings 155. ISSN 0357–2994 Available at: www.helcom.fi/baltic-sea-trends/holistic-assessments/state-of-the-baltic-sea-2018/reports-and-materials/. Accessed on 28 Mar 2021

  23. Han B, Loisel H, Vantrepotte V, Mériaux X, Bryère P, Ouillon S, Dessailly D, Xing Q, Zhu J (2016) Development of a semi-analytical algorithm for the retrieval of suspended particulate matter from remote sensing over clear to very turbid waters. Remote Sens 8:211. https://doi.org/10.3390/rs8030211

  24. Hansson M, Hakansson B (2007) The Baltic algae watch system—a remote sensing application for monitoring cyanobacterial blooms in the Baltic sea. J Appl Remote Sens 1(1):011507, 10pp

    Google Scholar 

  25. Hopkins CCE. (2000) Overview of monitoring in the Baltic Sea: Report to the Global Environment Facility/Baltic Sea Regional Project. AquaMarine Advisers, 39pp

    Google Scholar 

  26. IOCCG (2021) http://ioccg.org/resources/missions-instruments/current-ocean-colour-sensors. Accessed on 7 Mar 2021

  27. Izrael YuA, Tsyban AV (2009) Anthropogenic ecology of the ocean. Nauka, Moscow 529p (in Russian)

    Google Scholar 

  28. Jackson CR, Alpers W (2010) The role of the critical angle in brightness reversals on sunglint images of the sea surface. J Geophys Res 115(9)

    Google Scholar 

  29. Kahru M, Savchuk OP, Elmgren R (2007) Satellite measurements of cyanobacterial bloom frequency in the Baltic Sea: interannual and spatial variability. Mar Ecol Prog Ser 343:15–23

    Article  ADS  Google Scholar 

  30. Kahru M, Elmgren R (2014) Multidecadal time series of satellite-detected accumulations of cyanobacteria in the Baltic Sea. Biogeosciences 11:3619–3633

    Google Scholar 

  31. Knaeps E, Ruddick KG, Doxaran D, Dogliotti AI, Nechad B, Raymaekers D, Sterckx SA (2015) SWIR based algorithm to retrieve total suspended matter in extremely turbid waters. Remote Sens Environ 168:66–79. https://doi.org/10.1016/j.rse.2015.06.022

    Article  ADS  Google Scholar 

  32. Kopelevich OV, Burenkov VI, Sheberstov SV (2006) Development and use of regional algorithms for calculating the bio-optical characteristics of the seas of Russia from the data of satellite color scanners. Curr Problems Remote Sensing Earth Space 3(2):99–105

    Google Scholar 

  33. Kopelevich OV (2012) Application of data on seawater light scattering for the study of marine particles: a selective review focusing on Russian literature. Geo-Marine Lett 32(2):183–93

    Google Scholar 

  34. Kopelevich OV, Burenkov VI, Ershova SV, Sheberstov SV, Evdoshenko MA (2004) Application of SeaWiFS data for studying variability of bio-optical characteristics in the Barents, Black and Caspian Seas. Deep Sea Res Part II: Topical Stud Oceanogr 51(10–11):1063–1091

    Google Scholar 

  35. Kopelevich OV, Burenkov VI, Sheberstov SV (2008) Case studies of optical remote sensing in the Barents Sea, Black Sea, and Caspian Sea. In: Remote sensing of the European seas. Springer, Berlin, pp 53–66. https://doi.org/10.1007/978-1-4020-6772-3_4

  36. Kopelevich OV, Kostianoy AG (2018) Use of bio-optical parameters of the ocean, derived from satellite data, as essential climate variables. Fundamental Appl Climatol 3:8–29. https://doi.org/10.21513/2410-8758-2018-3-8-29 (in Russian)

  37. Kopelevich OV, Sheberstov SV, Burenkov VI, Vazyulya SV, Likhacheva MV (2007) Assessment of underwater irradiance and absorption of solar radiation at water column from satellite data. In: Proceedings of SPIE, 6615, 661507

    Google Scholar 

  38. Kopelevich OV, Vazyulya SV, Saling IV, Sheberstov SV, Burenkov VI (2015). Electronic atlas “Bio-optical characteristics of the seas of Russia according to the data of satellite color scanners 1998–2014”. In: Current problems in remote sensing of the Earth from space, vol 12, no 6, pp 99–110

    Google Scholar 

  39. Kopelevich O, Vazyulya S, Sheberstov S, Bukanova T (2016) Suspended matter in the surface layer of the South-Eastern Baltic from satellite data. Oceanology 56(1): 46–54. https://doi.org/10.1134/S0001437016010069

  40. Kosarev AN, Kostianoy AG, Zonn IS (2009) Kara-Bogaz-Gol Bay: physical and chemical evolution. Aquatic Geochem 15(1–2): 223–236 (Special Issue: Saline Lakes and Global Change). https://doi.org/10.1007/s10498-008-9054-z

  41. Kostianoy AG, Kostianaia EA, Soloviev DM (2016) Satellite monitoring of Dzhubga-Lazarevskoye-Sochi offshore gas pipeline construction. In: Zhiltsov SS, Zonn IS, Kostianoy AG (eds) Oil and gas pipelines in the Black-Caspian Seas Region. Springer International Publishing AG, Switzerland, pp 225–260. https://doi.org/10.1007/698_2016_465

  42. Kostianoy AG, Lavrova OYu (2014a) Oil pollution in the Baltic Sea. The handbook of environmental chemistry, vol 27. Springer, Berlin, 268pp

    Google Scholar 

  43. Kostianoy AG, Lavrova OYu (2014b) Conclusions. In: Kostianoy AG, Lavrova OYu (eds) Oil pollution in the Baltic Sea, vol 27. Springer, Berlin, pp 249–264

    Google Scholar 

  44. Kostianoy AG, Lavrova OYu (2014c) Introduction. In: Kostianoy AG, Lavrova OYu (eds) Oil pollution in the Baltic Sea, vol 27. Springer, Berlin, pp 1–14

    Google Scholar 

  45. Kostianoy AG, Lavrova OYu (2022) Satellite instrumentation and technique for oil pollution monitoring of the seas. In: Di Mauro A, Scozzari A, Soldovieri F (eds) Instrumentation and measurement technologies for water cycle management, Springer Nature Switzerland AG, pp 53–77. https://doi.org/10.1007/978-3-031-08262-7_4

  46. Kostianoy AG, Lavrova OYu, Mityagina MI, Solovyov DM (2014a) Satellite monitoring of the Nord Stream gas pipeline construction in the Gulf of Finland. In: Kostianoy AG, Lavrova OYu (eds) Oil pollution in the Baltic Sea, vol 27. Springer, Berlin, pp 221–248

    Google Scholar 

  47. Kostianoy AG, Lavrova OYu, Mityagina MI, Solovyov DM, Lebedev SA (2014b) Satellite monitoring of oil pollution in the Southeastern Baltic Sea. In: Kostianoy AG, Lavrova OYu (eds) Oil pollution in the Baltic Sea, vol 27. Springer, Berlin, pp 125–154

    Google Scholar 

  48. Kostianoy AG, OYu, Lavrova, Solovyov DM (2014) Oil pollution in coastal waters of Nigeria. In: Barale V, Gade M (eds) Remote sensing of the African Seas. Springer, Berlin, pp 149–165

    Google Scholar 

  49. Kostianoy AG, Lebedev SA, Solovyov DM (2013) Satellite monitoring of the Caspian Sea, Kara-Bogaz-Gol Bay, Sarykamysh and Altyn Asyr Lakes, and Amu Darya River. In: Zonn IS, Kostianoy AG (eds) The Turkmen Lake Altyn Asyr and water resources in Turkmenistan, vol 28. Springer, Berlin, pp 197–232

    Google Scholar 

  50. Kronberg P (1988) Remote sensing of the Earth. Mir, Moscow, p 350

    Google Scholar 

  51. Lavrova OYu, Kostianoy AG, Lebedev SA, Mityagina MI, Ginzburg AI, Sheremet NA (2011) Complex satellite monitoring of the Russian seas. IKI RAN, Moscow, 470pp (in Russian)

    Google Scholar 

  52. Lavrova OYu, Mityagina MI, Kostianoy AG (2016a) Satellite methods of detection and monitoring of marine zones of ecological risks. Space Research Institute, Moscow, 336p (in Russian)

    Google Scholar 

  53. Lavrova OYu, Soloviev DM, Mityagina MI, Strochkov AYa, Bocharova TYu (2015) Revealing the influence of various factors on concentration and spatial distribution of suspended matter based on remote sensing data—remote sensing of the ocean, sea ice, coastal waters, and large water regions 2015. In: Bostater CR, Mertikas SP, Neyt X (eds) Proceedings of SPIE, vol 9638. https://doi.org/10.1117/12.2193905

  54. Lavrova OYu, Soloviev DM, Strochkov MA, Bocharova TYu, Kashnitsky AV (2016b) River plumes investigation using Sentinel-2A MSI and Landsat-8 OLI data. Remote sensing of the ocean, sea ice, coastal waters, and large water regions 2016. In: Bostater CR, Neyt X, Nichol C, Aldred O (eds) Proceedings of SPIE, vol 9999, 99990G. https://doi.org/10.1117/12.2241312

  55. Lavrova O, Krayushkin E, Golenko M, Golenko N (2016c) Effect of wind and hydrographic conditions on the transport of Vistula Lagoon waters into the Baltic Sea: Results of a combined experiment. IEEE J Selected Topics Appl Earth Observations Remote Sens 9(9):5193–5201. https://doi.org/10.1109/JSTARS.2016.2580602

  56. Lavrova OYu, Mityagina MI, Kostianoy AG, Strochkov M (2017) Satellite monitoring of the Black Sea ecological risk areas. Ecologica Montenegrina 14:1–13

    Google Scholar 

  57. Lavrova OYu, Mityagina MI (2013) Satellite monitoring of oil slicks on the Black Sea surface. Izv Atmos Ocean Phy 49(29):897–912. https://doi.org/10.1134/S0001433813090107

  58. Lavrova OYu, Kostianoy AG (2011) A catastrophic oil spill in the Gulf of Mexico in April–May 2010. In: Izvestiya, atmospheric and oceanic physics, vol 47(9). Pleiades Publishing, Ltd, pp 1114–1118

    Google Scholar 

  59. Marmorino G, Smith GB, Toporkov JV, Sletten MA, Perkovich D, Frasier SJ (2008) Evolution of ocean slicks under a rising wind. J Geophys Res-OCEANS 115:C04030

    Google Scholar 

  60. Mironenko VA, Stanichny SV (1999) Possibilities of ecological monitoring of the shelf by satellite and polygon means. Environmental control systems. Collected papers, Marine Hydrophysical Institute, 303p

    Google Scholar 

  61. Mityagina M, Lavrova O (2016) Satellite survey of inner seas: oil pollution in the Black and Caspian Seas. Remote Sens 8:875. https://doi.org/10.3390/rs8100875

  62. Mityagina MI, Lavrova OYu, Kostianoy AG (2019) Main pattern of the Caspian Sea surface oil pollution revealed by satellite data. Ecologica Montenegrina 25:91–105

    Google Scholar 

  63. Mityagina MI, Lavrova OYu (2020) Oil pollution hotspots on the Caspian Sea surface identified using satellite remote sensing. In: Proceedings of SPIE 11529, Remote sensing of the ocean, sea ice, coastal waters, and large water regions 2020, 115290L. https://doi.org/10.1117/12.2573501

  64. Mityagina M, Lavrova O (2022) Satellite survey of offshore oil seep sites in the Caspian Sea. Remote Sens 14:525. https://doi.org/10.3390/rs14030525

  65. Nazirova K, Alferyeva Y, Lavrova O, Shur Y, Soloviev D, Bocharova T, Strochkov A (2021) Comparison of in situ and remote-sensing methods to determine turbidity and concentration of suspended matter in the estuary zone of the Mzymta River, Black Sea. Remote Sens 13:143. https://doi.org/10.3390/rs13010143

    Article  ADS  Google Scholar 

  66. Nechad B, Ruddick KG, Park Y (2010) Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters. Remote Sens Environ 114:854–866. https://doi.org/10.1016/j.rse.2009.11.022

    Article  ADS  Google Scholar 

  67. Nechad B, Ruddick K, Schroeder T, Oubelkheir K, Blondeau-Patissier D, Cherukuru N, Brando V, Dekker A, Clementson L, Banks AC, Maritorena S, Werdell PJ, Sá C, Brotas V, Caballero de Frutos I, Ahn Y-H, Salama S, Tilstone G, Martinez-Vicente V, Foley D, McKibben M, Nahorniak J, Peterson T, Siliò-Calzada A, Röttgers R, Lee Z, Peters M, C (2015) CoastColour Round Robin data sets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters. Earth Syst Sci Data 7:319–348. https://doi.org/10.5194/essd-7-319-2015

  68. Novoa S, Doxaran D, Ody A, Vanhellemont Q, Lafon V, Lubac B (2017) Atmospheric corrections and multi-conditional algorithm for multi-sensor remote sensing of suspended particulate matter in low-to-high turbidity levels Coastal Waters. Remote Sens 9:61. https://doi.org/10.3390/rs9010061

  69. Patin S (1999) Environmental impact of the offshore oil and gas industry. Ecomonitor Pub 425p

    Google Scholar 

  70. Patin SA (2008) Oil spills and their impact on the marine environment and living resources. Moscow, VNIRO Publishing, 508pp (in Russian)

    Google Scholar 

  71. Petus C, Chust G, Gohin F, Doxaran D, Froidefond J-M, Sagarminaga Y (2010) Estimating turbidity and total suspended matter in the Adour River plume (South Bay of Biscay) using MODIS 250-m imagery. Shelf Res 30(5):379–339. https://doi.org/10.1016/j.csr.2009.12.007

  72. Reinart A, Kutser T (2006) Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea. Remote Sens Environ 102(1–2):74–85

    Google Scholar 

  73. Romankevich EA, Aibulatov NA (2004) Geochemical state of the seas of Russia and human health. Vestnik of the Earth Sciences Branch of RAS 1(22)

    Google Scholar 

  74. Sentinel-3 OLCI (2021) https://sentinel.esa.int/web/sentinel/user-guides/sentinel-3-olci/product-types/level-2-water. Accessed on 09.03.2021

  75. Tavora J, Boss E, Doxaran D, Hill P (2020) An algorithm to estimate suspended particulate matter concentrations and associated uncertainties from remote sensing reflectance in coastal environments. Remote Sens 12:2172. https://doi.org/10.3390/rs12132172

    Article  ADS  Google Scholar 

  76. UNCTAD (2020) United Nations conference on trade and development. Review of maritime transport 2019. United Nations, Geneva, 31 Jan 2020, 132p

    Google Scholar 

  77. Urdenko VA, Zimmerman G (eds) (1987) Remote sensing of the sea taking into account the atmosphere (1987) V.2. Part 2. Publishing house of the Institute of Space Research of the Academy of Sciences of GDR, Moscow, Berlin, Sevastopol, 197pp

    Google Scholar 

  78. Vazyulya S, Khrapko A, Kopelevich O, Burenkov V, Eremina T, Isaev A (2014) Regional algorithms for the estimation of chlorophyll and suspended matter concentration in the Gulf of Finland from MODIS-Aqua satellite data. Oceanologia 56(4):1–19. https://doi.org/10.5697/oc.56-4.737

  79. Warrick JA, DiGiacomo PM, Weisberg SB, Nezlin NP, Mengel M, Jones BH, Ohlmann JC, Washburn L, Terrill EJ, Farnsworth KL (2007) River plume patterns and dynamics within the Southern California. Bight Cont Shelf Res 27:2427–3244. https://doi.org/10.1016/j.csr.2007.06.015

    Article  ADS  Google Scholar 

  80. Werdell PJ, Franz BA, Bailey SW et al (2013) Generalized ocean color inversion model for retrieving marine inherent optical properties. Appl Opt 52:2019–2037

    Article  ADS  PubMed  Google Scholar 

  81. Werdell PJ, Lachlan IW, McKinna et al (2018) An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing. Progr Oceanogr 160:186–212

    Google Scholar 

  82. Xue K, Ma R, Shen M, Li Y, Duan H, Cao Z, Wang D, Xiong J (2020) Variations of suspended particulate concentration and composition in Chinese lakes observed from Sentinel-3A OLCI images. Sci Total Environ 721:137774. https://doi.org/10.1016/j.scitotenv.2020.137774

Download references

Acknowledgements

The authors are thankful to D.M. Soloviev (Marine Hydrophysical Institute of RAS) for preparation of a set of satellite imagery. The research was partially funded in the framework of the Russian Science Foundation no. 19-77-20060 Project «Assessing ecological variability of the Caspian Sea in the current century using satellite remote sensing data» (2019–2022). This publication was prepared in the framework of the scientific activities related to “The Caspian Sea Digital Twin” Programme performed in the framework of the UN Decade on Ocean Science for Sustainable Development (2021–2030).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrey G. Kostianoy .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Kostianoy, A.G., Lavrova, O.Y., Strochkov, A.Y. (2022). Satellite Instrumentation and Technique for Monitoring of Seawater Quality. In: Di Mauro, A., Scozzari, A., Soldovieri, F. (eds) Instrumentation and Measurement Technologies for Water Cycle Management . Springer Water. Springer, Cham. https://doi.org/10.1007/978-3-031-08262-7_5

Download citation

Publish with us

Policies and ethics