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Satellite Remote Sensing for Ocean Biology: An Indian Perspective

Proceedings of the National Academy of Sciences, India Section A: Physical Sciences volume 87, pages 629–640 (2017)Cite this article

Abstract

Oceans play an important role in maintaining the Earth’s climate and provide vital natural resources. Ocean biota, in particular phytoplankton plays a fundamental role in regulating the Earth’s energy balance. Atmospheric carbon is fixed by these organisms and further phytoplankton acts as primary producers in oceanic food webs. Space based observations using ocean colour sensors have provided unique information about the global distribution and temporal variability of oceanic phytoplankton. India has made significant progress in developing ocean colour science and have launched two ocean colour sensors namely OCM-1 and OCM-2. The data provided by these remote sensing instruments, on phytoplankton distribution around Arabian Sea and Bay of Bengal has been extensively used to understand marine ecosystem, as well as for identifying productive regions for potential fishing zones. This paper provides a review of work done in India during the last three decades in the broad field of space based marine biology.

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References

  1. Keeling R, Peng T (1995) Transport of heat, O2, and CO2, by the Atlantic’s thermohaline circulation. Philos Trans R Soc Lond B 348:133–142

    ADS  Article  Google Scholar 

  2. Sathyendranath S, Gouveia AD, Shetye SR, Ravindran P, Platt T (1991) Biological control of surface temperature in the Arabian Sea. Nature 349:54–56

    ADS  Article  Google Scholar 

  3. Falkowski PG, Kim Y, Kolber Z, Wilson C, Wirick C, Cess R (1992) Natural versus anthropogenic factors affecting low level cloud albedo over the North Atlantic. Science 256:1311–1313

    ADS  Article  Google Scholar 

  4. Morel A (1980) In-water and remote measurements of ocean colour. Bound Layer Meteorol 18:177–181

    ADS  Article  Google Scholar 

  5. Gordon HR, Clark DK (1981) Clear water radiances for atmospheric correction of coastal zone color scanner imagery. Appl Opt 19:4174–4180

    Google Scholar 

  6. Chauhan P, Nagur CRC, Mohan M, Nayak SR, Navangund RR (2001) Surface chlorophyll-a distribution in Arabian Sea and Bay of Bengal using IRS-P4 ocean colour monitor satellite data. Curr Sci 80:127–129

    Google Scholar 

  7. Chauhan P, Mohan M, Sarangi RK, Kumari B, Nayak SR, Matondkar SGP (2002) Surface chlorophyll-a estimation using IRS-P4 OCM data in the Arabian Sea. Int J Remote Sens 23:1663–1676

    Article  Google Scholar 

  8. Chauhan P, Mohan M, Nayak S (2003) Comparative analysis of ocean colour measurements of IRS-P4 OCM and SeaWiFS in the Arabian Sea. IEEE Trans Geosci Remote Sens 41:922–926

    ADS  Article  Google Scholar 

  9. Gordon HR, Wang M (1994) Retrieval of water leaving radiance and aerosol optical thickness over the ocean with SeaWiFS: a preliminary algorithm. Appl Opt 33:443–452

    ADS  Article  Google Scholar 

  10. Chauhan P, Sanwlani N, Navalgund RR (2009) Aerosol optical depth variability in the northeastern Arabian Sea during winter monsoon: a study using in situ and satellite measurements. Indian J Mar Sci 38:390–396

    Google Scholar 

  11. O’Reilly JE, Maritorena S, Siegel D, O ‘Brien M, Toole D, Mitchell BG, Kahru M, Chavez F, Strutton P, Cota G, Hooker S, McClain C, Carder K, Muller-Karger F, Harding L, Magnuson A, Phinney D, Moore G, Aiken J, Arrigo K, Letelier R, Culver M (2000) Ocean color chlorophyll a algorithms for SeaWiFS, OC2, and OC4: Version 4. In: SeaWiFS post launch calibration and validation analyses, Part 3. NASA Tech Memo 2000-206892, 11, pp 9–23

  12. Nagamani PV, Chauhan P, Dwivedi RM (2007) Estimation of chlorophyll-a concentration using an artificial neural network (ANN) based algorithm with Oceansat-1 OCM data. J Indian Soc Remote Sens 35:201–207

    Article  Google Scholar 

  13. Nagamani PV, Chauhan P, Dwivedi RM (2008) Development of chlorophyll-a algorithm for ocean colour monitor OCEANSAT-2 satellite. IEEE Trans Geosci Remote Sens Lett 5:527–531

    ADS  Article  Google Scholar 

  14. Navalgund RR, Kiran Kumar AS (1999) Ocean colour monitor (OCM) IRS-P4. IOCCG website. (http://www.ioccg.org/generate/ocm/ocm.html)

  15. Nayak S, Raman M, Bahuguna A (2007) Remote sensing for marine algae. In: Tiwari A (ed) Monograph on recent advances on applied aspects of indian marine algae with reference to global scenario, 2. CSIR Press, New Delhi, pp 1–20

    Google Scholar 

  16. Nath AN, Rao MV, Rao KH, Nathaniel DE, Ramana TV, Suhasini TD, Gopal GV, Nath DJ (1992) Satellite forecasting for marine fishery resources exploitation along Indian coast. Interface 3:1–3

    Google Scholar 

  17. Solanki HU, Dwivedi RM, Raman M, Narain A (1994) Monitoring the oceanic features using NOAA AVHRR data for fisheries applications: a case Study of Saurastra coast. In: Proceeding of the 15th asian conference on remote sensing, vol. II, pp Q-5-1 to Q-7-5

  18. Kumari B, Solanki HU, Raman M, Narain A (1994) Satellite derived oceanographic features as an input for long term fisheries forecast system: a case study in the North west waters of India. In: proceeding of the 15th asian conference on remote sensing, vol II, pp G-4-1 to G-4-6

  19. Dwivedi RM, Solanki HU, Nayak SR, Gulati D, Somvanshi VS (2005) Exploration of fishery resources through integration of ocean colour data with sea surface temperature: Indian experience. Indian J Mar Sci 34:430–440

    Google Scholar 

  20. Choudhary SB, Rao KH, Rao MV (2002) Satellite remote sensing for marine resources assessment. Trop Ecol 43:187–202

    Google Scholar 

  21. Nayak SR, Solanki HU, Dwivedi RM (2003) Utilization of IRS P4 ocean colour data for potential fishing zone-a cost benefit analysis. Indian J Mar Sci 32:244–248

    Google Scholar 

  22. Kumari B, Raman M, Mali K (2009) Locating tuna forage ground through satellite remote sensing. Int J Remote Sens 30:5977–5988

    Article  Google Scholar 

  23. Kumari B, Raman M (2010) Whale shark habitat assessments in the northeastern Arabian Sea using satellite remote sensing. Int J Remote Sens 31:379–389

    Article  Google Scholar 

  24. Bhatpuria D, Solanki HU, Varghese S, Chauhan P (2015) Applications of satellite derived meso-scale features and in situ bycatch to understand sea turtle habitat along the Indian coast. Curr Sci 108:326–329

    Google Scholar 

  25. Sarangi RK, Chauhan P, Nayak SR (2001) Phytoplankton bloom monitoring in the offshore water of Northern Arabian Sea using IRS-P4 OCM Satellite data. Indian J Mar Sci 30:214–221

    Google Scholar 

  26. Shanmugam P, Suresh M, Sundrabalan B (2013) OSABT: an innovative algorithm to detect and characterize ocean surface algal blooms. IEEE J Appl Earth Obs Remote Sens 6:1879–1892

    Article  Google Scholar 

  27. Dwivedi RM, Raman M, Parab S, Matondkar SGP, Nayak SR (2006) Influence of northeasterly trade winds on intensity of winter bloom in the Northern Arabian Sea. Curr Sci 90:1397–1406

    Google Scholar 

  28. Dwivedi RM, Raman M, Babu KN, Singh SK, Vyas NK, Matondkar SGP (2008) Formation of algal bloom in the Northern Arabian Sea deep waters during January–March: a study using pooled in situ and satellite data. Int J Remote Sens 29:4537–4551

    Article  Google Scholar 

  29. Dwivedi RM, Rafeeq M, Simtha BR, Padmakumar KB, Thomas LC, Sanjeevan VN, Prakash P, Raman M (2015) Species identification of mixed algal bloom in the Northern Arabian Sea using Remote Sensing techniques. Environ Monit Assess 187:51–53

    Article  Google Scholar 

  30. Simon A, Shanmugam P (2012) An algorithm for classification of algal blooms using MODIS-Aqua data in oceanic waters around India. Adv Remote Sens 1:35–51

    Article  Google Scholar 

  31. Sarangi RK, Chauhan P, Nayak SR (2004) Detection and monitoring of Trichodesmium blooms in the coastal waters off Saurastra coast India using IRS-P4 OCM data. Curr Sci 86:1636–1641

    Google Scholar 

  32. Singh SK, Raman M, Dwivedi RM, Nayak S (2007) An approach to compute photosynthetically active radiation using IRS P4 OCM. Int J Remote Sens. https://doi.org/10.1080/01431160701264219

    Google Scholar 

  33. Tripathy M, Raman M, Dwivedi RM, Ajai (2012) Frequency of cyclonic disturbances and changing productivity patterns in the North Indian Ocean Region: a study using sea surface temperature and ocean colour data. Int J Geosci 3:490–506

    Article  Google Scholar 

  34. Raman M (2013) Estimating primary production in the Arabian Sea using satellite derived data. Ph. D dissertation thesis, Mangalore University

  35. Sarangi RK, Mishra MK, Chauhan P (2015) Remote sensing observations on impact of Phallin cyclone on phytoplankton distribution in northern Bay of Bengal. IEEE J Sel Top Appl Earth Obs Remote Sens 8:539–549

    Article  Google Scholar 

  36. Latha TP, Rao KH, Nagamani PV, Amminedu E, Choudhary SB, Dutt CBS, Dadhwal VK (2015) Impact of cyclone phailin on chlorophyll-a concentration and productivity in the Bay of Bengal. Int J Geosci 6:473–480

    Article  Google Scholar 

  37. Loliker A, Kumar T, Reddem VS, Nayak S (2014) Cyclone Phailin enhanced the productivity following its passage: evidence from satellite data. Curr Sci 106:360–361

    Google Scholar 

  38. Giri S, Das S, Chanda A, Das I, Maity S, Hazara S (2016) Increase in fish catch after the cyclone Phailin in the northeren Bay of Bengal lying adjacent to west bengal coast—a case study. Indian J Geo-Mar Sci 45:1094–1097

    Google Scholar 

  39. Tripathy M, Raman M, Chauhan P (2015) Estimation of photosynthetically available radiation (PAR) from OCEANSAT-I OCM using a simple atmospheric radiative transfer model. Adv Space Res 56:1441–1452

    ADS  Article  Google Scholar 

  40. IOCCG (2014) Phytoplankton functional types from Space. In: Sathyendranath S (ed) Reports of the international ocean-colour coordinating group. No. 15, IOCCG, Dartmouth, Canada

  41. Sahay A, Moosa A, Gupta A, Goes J (2017) Ocean colour satellite determination of phytoplankton size class in the Arabian Sea during the winter monsoon. Remote Sens Environ 198:286–296

    ADS  Article  Google Scholar 

Download references

Acknowledgements

Authors are thankful to Shri Tapan Misra, Director, Space Applications Centre, Ahmedabad for taking keen interest in ocean colour research and for encouraging to write this review paper. Authors are also thankful to previous Directors of SAC/ISRO, namely Dr R. R. Navalgund and Shri A. S. Kiran Kumar (currently Chairman, ISRO) for building the science teams of ocean colour activity at SAC/ISRO. Our deep appreciation is also due to all the members of OCM sensor development and data product generation teams.

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  1. Space Applications Centre, (ISRO), Ahmedabad, 380015, India

    Prakash Chauhan & Mini Raman

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  1. Prakash Chauhan
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Correspondence to Prakash Chauhan.

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Chauhan, P., Raman, M. Satellite Remote Sensing for Ocean Biology: An Indian Perspective. Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci. 87, 629–640 (2017). https://doi.org/10.1007/s40010-017-0439-5

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  • DOI: https://doi.org/10.1007/s40010-017-0439-5

Keywords

  • Ocean colour
  • OCEANSAT-1&2 OCM
  • Phytoplankton
  • Algal blooms
  • Potential fishing zone (PFZ)