Skip to main content

Advertisement

SpringerLink
Log in

Retrieval of Micro-Phytoplankton Density using Sentinel-3 and MODIS Satellite Sensors on the Eastern Algerian Coast

  • Published:
Thalassas: An International Journal of Marine Sciences Aims and scope Submit manuscript

Abstract

The spatiotemporal variability of the major phytoplankton groups, such as dinoflagellates and diatoms, provides crucial information about the ecosystem’s status, especially when it comes to coastal regions that are influenced by permanent anthropogenic pressure. The purpose of this study was to develop specific models for the retrieval of diatoms and dinoflagellates in Annaba Bay and El Kala’s coast (the eastern part of the Algerian coast). We established a data set that included quantified micro-phytoplankton densities from seawater samples obtained at distinct stations along the study area during different seasons and their corresponding Sentinel-3 and MODIS reflectance (Rrs) values. Several band ratios based on the blue-green and near infrared-red (NIR-red) parts of the spectrum have been tested, as well as the Generalized Linear Model (GLM) with 12 bands using the machine learning approach, in order to validate the most accurate model for quantifying micro-phytoplankton density. The results revealed the efficiency of the 6B.S3 (r = 0.90, RMSE = 3364.2 Cells l-1) based on the band ratio, which employs six bands in the blue-green and red parts of the spectrum, and the 12B.S3 (r = 0.84, RMSE = 410.49 Cells l-1) based on the machine learning approach, which employs 12 bands of the spectrum for the estimation of diatom and dinoflagellate densities, respectively. On the other hand, both groups exhibit strong correlation with the 5B.M, which involves 5 bands of MODIS Rrs (r = 0.90 and 0.76 for diatoms and dinoflagellates, respectively). Mapping phytoplankton densities revealed that Sentinel-3 data and models outperformed those of MODIS and were more suitable for monitoring diatoms and dinoflagellates along Algeria’s eastern coast.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  • Abdallah KW, Samar F, Djabourabi A, Harid R, Izeboudjen H, Bachari NEI, Houma-Bachari F (2023) A preliminary assessment of Sentinel-3 ocean and land color instrument data for the estimation of chlorophyll-a concentration using bio-optical methods in Annaba Bay and El Kala’s coast (Algerian Basin). Reg Stud Mar Sci 102882. https://doi.org/10.1016/j.rsma.2023.102882

  • Alvain S, Moulin C, Dandonneau Y, Bréon FM (2005) Remote sensing of phytoplankton groups in case 1 waters from global SeaWiFS imagery. Deep Sea Res Part I Oceanogr Res Pap 52(11):1989–2004. https://doi.org/10.1016/j.dsr.2005.06.015

    Article  Google Scholar 

  • Aminot A, Kérouel R (2004) Hydrologie des écosystèmes marins: Paramètres et analyses. Éd. Ifremer, Paris, p 336

  • Andersen P, Throndsen J (2003) Estimating cell numbers. In GM Hallegraeff, DM Anderson, AD Cembella (eds), Manual on Harmful Marine Microalgae (vol. 4). pp 99–129

  • Aounallah O (2015) Distribution and fluxes of biogeochemical variables in the Seybouse River Estuary, SW Mediterranean. p 8

  • Bachari-Houma F (2009) Modélisation et cartographie de la pollution marine et de la bathymétrie à partir de l’imagerie satellitaire [These de doctorat]: Paris Est. Accessed 23 Aug 2022. https://www.theses.fr/2009PEST0065

  • Barton AD, Finkel ZV, Ward BA, Johns DG, Follows MJ (2013) On the roles of cell size and trophic strategy in North Atlantic diatom and dinoflagellate communities. Limnol Oceanogr 58(1):254–266. https://doi.org/10.4319/lo.2013.58.1.0254

    Article  Google Scholar 

  • Benzouaï S, Louanchi F, Smara Y (2020) Phytoplankton phenology in Algerian continental shelf and slope waters using remotely sensed data. Estuar Coast Shelf Sci 247:107070. https://doi.org/10.1016/j.ecss.2020.107070

    Article  Google Scholar 

  • Blondeau-Patissier D, Gower JFR, Dekker AG, Phinn SR, Brando VE (2014) A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans. Progr Oceanogr 123:123–144. https://doi.org/10.1016/j.pocean.2013.12.008

    Article  Google Scholar 

  • Boufeniza RL, Alsahli MM, Bachari NI, Bachari FH (2020) Spatio-temporal quantification and distribution of diatoms and dinoflagellates associated with algal blooms and human activities in Algiers Bay (Algeria) using Landsat-8 satellite imagery. Reg Stud Mar Sci 36:101311. https://doi.org/10.1016/j.rsma.2020.101311

    Article  Google Scholar 

  • Bracher A, Vountas M, Dinter T, Burrows JP, Rottgers R, Peeken I (2009) Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data. p 14

  • Brewin RJW, Sathyendranath S, Hirata T, Lavender SJ, Barciela RM, Hardman-Mountford NJ (2010) A three-component model of phytoplankton size class for the Atlantic Ocean. Ecol Model 221(11):1472–1483. https://doi.org/10.1016/j.ecolmodel.2010.02.014

    Article  CAS  Google Scholar 

  • 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. 740:54

  • Butt MJ, Nazeer M (2015) Landsat ETM+ Secchi Disc Transparency (SDT) retrievals for Rawal Lake, Pakistan. Adv Space Res 56(7):1428–1440. https://doi.org/10.1016/j.asr.2015.06.041

    Article  CAS  Google Scholar 

  • Carreto J, Carignan M, Montoya N (2001) Comparative studies on mycosporine-like amino acids, paralytic shellfish toxins and pigment profiles of the toxic dinoflagellates Alexandrium tamarense, A. catenella and A. minutum. Mar Ecol Prog Ser. 223:49–60. https://doi.org/10.3354/meps223049

    Article  CAS  Google Scholar 

  • Ciotti AM, Bricaud A (2006) Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off Brazil: Algal size and CDM from SeaWiFS data. Limnol Oceanogr Methods 4(7):237–253. https://doi.org/10.4319/lom.2006.4.237

    Article  Google Scholar 

  • Di Cicco A, Sammartino M, Marullo S, Santoleri R (2017) Regional empirical algorithms for an improved identification of phytoplankton functional types and size classes in the Mediterranean sea using satellite data. Front Mar Sci 4:126. https://doi.org/10.3389/fmars.2017.00126

    Article  Google Scholar 

  • D’Ortenzio F, Prieur L (2012) The upper mixed layer. Life in the Mediterranean Sea: a Look at Habitat Changes

  • D’Ortenzio F, Ribera d’Alcalà M (2009) On the trophic regimes of the Mediterranean Sea: a satellite analysis. Biogeosciences 6(2):139–148. https://doi.org/10.5194/bg-6-139-2009

    Article  Google Scholar 

  • ESA (2012) Sentinel-3: ESA’s global land and ocean mission for GMES operational services. p 106

  • Fahrmeir L, Kneib T, Lang S, Marx B (2013) Generalized linear models. In: Regression. Berlin, Heidelberg: Springer. p 269–324. https://link.springer.com/chapter/10.1007/978-3-642-34333-9_5

  • Fowler S, Roush R, Wise J (2013) The light-dependent reactions of photosynthesis. In: Concepts of Biology

  • Frehi H, Couté A, Mascarell G, Perrette-Gallet C, Ayada M, Kara MH (2007) Dinoflagellés toxiques et/ou responsables de blooms dans la baie d’Annaba (Algérie). Comptes Rendus Biologies. 330(8):615–628. https://doi.org/10.1016/j.crvi.2007.05.002

    Article  Google Scholar 

  • Garrison DL (1984) Planktonic diatoms. Marine plankton life cycle strategies. pp 1–17

  • Gilerson AA, Gitelson AA, Zhou J, Gurlin D, Moses W, Ioannou I, Ahmed SA (2010) Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands. Opt Express 18(23):24109. https://doi.org/10.1364/OE.18.024109

    Article  CAS  Google Scholar 

  • Godhe A, Asplund ME, Härnström K, Saravanan V, Tyagi A, Karunasagar I (2008) Quantification of diatom and dinoflagellate biomasses in coastal marine seawater samples by real-time PCR. Appl Environ Microbiol 74(23):7174–7182. https://doi.org/10.1128/AEM.01298-08

    Article  CAS  Google Scholar 

  • Google Maps (2022) Algeria-google maps. https://www.google.com/maps/place/Annaba. Accessed 16 Mar 2022

  • Guelorget O, Frisoni GF, Ximenes MC, Perthuisot JP (1989) Expressions biogéologiques du confinement dans une lagune méditerranéenne: le lac Melah (Algérie)

  • Gustafson DE, Stoecker DK, Johnson MD, Van Heukelem WF, Sneider K (2000) Cryptophyte algae are robbed of their organelles by the marine ciliate Mesodinium rubrum. Nature 405(6790):1049–1052. https://doi.org/10.1038/35016570

    Article  CAS  Google Scholar 

  • Hadjadji I, Frehi H, Ayada L, Abadie E, Collos Y (2014) A comparative analysis of Alexandrium catenella/tamarense blooms in Annaba Bay (Algeria) and Thau lagoon (France); phosphorus limitation as a trigger. Comptes Rendus Biologies 337(2):117–122. https://doi.org/10.1016/j.crvi.2013.11.006

    Article  Google Scholar 

  • Hansen P (1991) Quantitative importance and trophic role of heterotrophic dinoflagellates in a coastal pelagial food web. Mar Ecol Prog Ser 73:253–261. https://doi.org/10.3354/meps073253

    Article  Google Scholar 

  • Harid R, Demarcq H, Keraghel M-A, Ait-Kaci M, Zerrouki M, Bachari N-E-I, Houma F (2022) Spatio-temporal variability of a chlorophyll-a based biomass index and influence of coastal sources of enrichment in the Algerian Basin. Cont Shelf Res 232:104629. https://doi.org/10.1016/j.csr.2021.104629

    Article  Google Scholar 

  • Hernández Fariñas T, Bacher C, Soudant D, Belin C, Barillé L (2015) Assessing phytoplankton realized niches using a French national phytoplankton monitoring network. Estuar Coast Shelf Sci 159:15–27. https://doi.org/10.1016/j.ecss.2015.03.010

    Article  Google Scholar 

  • Hirata T, Hardman-Mountford NJ, Brewin RJW, Aiken J, Barlow R, Suzuki K, Isada T, Howell E, Hashioka T, Noguchi-Aita M, Yamanaka Y (2011) Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types. Biogeosciences. 8(2):311–327. https://doi.org/10.5194/bg-8-311-2011

    Article  CAS  Google Scholar 

  • Illoul H, Masó M, Fortuño J-M, Cros L, Morales-Blake A, Séridji R (2008) Potentially harmful microalgae in coastal waters of the Algiers area (Southern Mediterranean Sea). p 18

  • Kahru M, Kudela R, Anderson C, Manzano-Sarabia M, Mitchell B (2014) Evaluation of satellite retrievals of ocean chlorophyll-a in the California current. Remote Sens 6(9):8524–8540. https://doi.org/10.3390/rs6098524

    Article  Google Scholar 

  • Kempton JW, Wolny J, Tengs T, Rizzo P, Morris R, Tunnell J, Scott P, Steidinger K, Hymel SN, Lewitus AJ (2002) Kryptoperidinium foliaceum blooms in South Carolina: a multi-analytical approach to identification. Harm Algae 1(4):383–392. https://doi.org/10.1016/S1568-9883(02)00051-3

    Article  CAS  Google Scholar 

  • Khammar H (2007) Caractères chimiques des effluents urbains introduits au littoral d’Annaba. [Magister]. Annaba, Algeria: Annaba University

  • Khélifi-Touhami M, Ounissi M, Saker I, Haridi A, Djorfi S, Abdenour C (2006) The hydrology of the Mafrag estuary (Algeria): Transport of inorganic nitrogen and phosphorus to the adjacent coast. J Food Agric Environ 4(2):340

    Google Scholar 

  • Kostadinov TS, Siegel DA, Maritorena S (2009) Retrieval of the particle size distribution from satellite ocean color observations. J Geophys Res 114(C9):C09015. https://doi.org/10.1029/2009JC005303

    Article  Google Scholar 

  • Leakey R, Archer S, Grey J (1996) Microbial dynamics in coastal waters of East Antarctica: Bacterial production and nanoflagellate bacterivory. Mar Ecol Prog Ser 142:3–17. https://doi.org/10.3354/meps142003

    Article  Google Scholar 

  • Leterme SC, Seuront L, Edwards M (2006) Differential contribution of diatoms and dinoflagellates to phytoplankton biomass in the NE Atlantic Ocean and the North Sea. Mar Ecol Prog Ser 312:57–65. https://doi.org/10.3354/meps312057

    Article  Google Scholar 

  • Lodhi MA (2002) Influence of bright bottom depth on reflectance from clear and turbid water bodies. Geocarto Int 17(3):7–16

    Article  Google Scholar 

  • Lorenzen CJ (1967) Determination of chlorophyll and pheo-pigments: Spectrophotometric equations1. Limnol Oceanogr 12(2):343–346. https://doi.org/10.4319/lo.1967.12.2.0343

    Article  CAS  Google Scholar 

  • Middelburg JJ, Soetaert K (2004) The role of sediments in shelf ecosystem dynamics. Sea 13:353–373

    Google Scholar 

  • Millot C (1999) Circulation in the Western Mediterranean Sea. J Mar Syst 20(1–4):423–442. https://doi.org/10.1016/S0924-7963(98)00078-5

    Article  Google Scholar 

  • Mischke U, Venohr M, Behrendt H (2011) Using phytoplankton to assess the trophic status of German rivers. Int Rev Hydrobiol 96(5):578–598. https://doi.org/10.1002/iroh.201111304

    Article  CAS  Google Scholar 

  • Montes-Hugo M, Doney SC, Ducklow HW, Fraser W, Martinson D, Stammerjohn SE, Schofield O (2009) Recent changes in phytoplankton communities associated with rapid regional climate change along the Western Antarctic Peninsula. Science 323(5920):1470–1473. https://doi.org/10.1126/science.1164533

    Article  CAS  Google Scholar 

  • Moses WJ, Saprygin V, Gerasyuk V, Povazhnyy V, Berdnikov S, Gitelson AA (2019) OLCI-based NIR-red models for estimating chlorophyll-a concentration in productive coastal waters—a preliminary evaluation. Environ Res Commun 1(1):011002. https://doi.org/10.1088/2515-7620/aaf53c

    Article  Google Scholar 

  • Mouw CB, Greb S, Aurin D, DiGiacomo PM, Lee Z, Twardowski M, Binding C, Hu C, Ma R, Moore T et al (2015) Aquatic color radiometry remote sensing of coastal and inland waters: Challenges and recommendations for future satellite missions. Remote Sens Environ 160:15–30. https://doi.org/10.1016/j.rse.2015.02.001

    Article  Google Scholar 

  • Mouw CB, Yoder JA (2010) Optical determination of phytoplankton size composition from global SeaWiFS imagery. J Geophys Res 115(C12):C12018. https://doi.org/10.1029/2010JC006337

    Article  Google Scholar 

  • Nakamura Y (1998) Biomass, feeding and production of Noctiluca scintillans in the Seto Inland Sea, Japan. J Plankton Res 20(11):2213–2222. https://doi.org/10.1093/plankt/20.11.2213

    Article  Google Scholar 

  • ONS (2008) Office National des Statistiques

  • O’Reilly JE, Maritorena S, Mitchell BG, Siegel DA, Carder KL, Garver SA, Kahru M, McClain C (1998) Ocean color chlorophyll algorithms for SeaWiFS. J Geophys Res 103(C11):24937–24953. https://doi.org/10.1029/98JC02160

    Article  Google Scholar 

  • O’Reilly JE, Werdell PJ (2019) Chlorophyll algorithms for ocean color sensors - OC4, OC5 & OC6. Remote Sens Environ 229:32–47. https://doi.org/10.1016/j.rse.2019.04.021

    Article  Google Scholar 

  • Ounissi M, Frehi H, Khelifi-Touhami M (1998) Composition et abondance du zooplancton en situation d’eutrophisation dans un secteur côtier du golfe d’Annaba (Algérie). Ann Inst Oceanogr (Monaco) 74(1):13–28

    Google Scholar 

  • Ounissi M, Ziouch O-R, Aounallah O (2014) Variability of the dissolved nutrient (N, P, Si) concentrations in the Bay of Annaba in relation to the inputs of the Seybouse and Mafragh estuaries. Mar Pollut Bullet 80(1–2):234–244. https://doi.org/10.1016/j.marpolbul.2013.12.030

    Article  CAS  Google Scholar 

  • Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V et al (2011) Scikit-learn: Machine Learning in Python. Machine Learn Python 6

  • Roy S, Sathyendranath S, Bouman H, Platt T (2013) The global distribution of phytoplankton size spectrum and size classes from their light-absorption spectra derived from satellite data. Remote Sens Environ 139:185–197. https://doi.org/10.1016/j.rse.2013.08.004

    Article  Google Scholar 

  • Sarthou G, Timmermans KR, Blain S, Tréguer P (2005) Growth physiology and fate of diatoms in the ocean: a review. J Sea Res 53(1–2):25–42. https://doi.org/10.1016/j.seares.2004.01.007

    Article  CAS  Google Scholar 

  • Smetacek V (1999) Diatoms and the ocean carbon cycle. Protist 150(1):25–32. https://doi.org/10.1016/S1434-4610(99)70006-4

    Article  CAS  Google Scholar 

  • Sunda W, Kieber DJ, Kiene RP, Huntsman S (2002) An antioxidant function for DMSP and DMS in marine algae. Nature 418(6895):317–320. https://doi.org/10.1038/nature00851

    Article  CAS  Google Scholar 

  • Takano Y, Hansen G, Fujita D, Horiguchi T (2008) Serial replacement of diatom endosymbionts in two freshwater dinoflagellates, peridiniopsis spp. (Peridiniales, Dinophyceae). Phycologia 47(1):41–53. https://doi.org/10.2216/07-36.1

  • Tomas CR (1997) Identifying marine phytoplankton. [place unknown]: Elsevier

  • Uitz J, Stramski D, Gentili B, D’Ortenzio F, Claustre H (2012) Estimates of phytoplankton class-specific and total primary production in the Mediterranean Sea from satellite ocean color observations: primary production in the Mediterranean. Global Biogeochem Cycles 26(2). https://doi.org/10.1029/2011GB004055

  • Utermöhl H (1958) Zur Vervollkommnung der quantitativen Phytoplankton-Methodik: Mit 1 Tabelle und 15 abbildungen im Text und auf 1 Tafel. SIL Commun 1953–1996 9(1):1–38. https://doi.org/10.1080/05384680.1958.11904091

Download references

Acknowledgement

The authors would like to thank Copernicus for providing the satellite data used in this research. We also acknowledge the entire ECOSYSMarL laboratory team, especially Belloulou for their assistance in acquiring the measured data. We thank the anonymous reviewers for their helpful recommendations that greatly improved this manuscript.

Funding

This research did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors. We have no conflicts of interest associated with this publication that could have influenced its outcome.

Author information

Authors and Affiliations

  1. Laboratoire de recherche sur la biodiversité et la pollution des écosystèmes, Département des Sciences de la Mer, Université de Chadli Bendjedid BP 73, 36000, El Tarf, Algeria

    Khadidja Wissal Abdallah, Faouzi Samar & Aicha Djabourabi

  2. Ecole Nationale Supérieure des Sciences de la Mer et de l’Aménagement du Littoral, Campus Universitaire de Dely Ibrahim Bois des Cars, B.P. 19, 16320, Alger, Algeria

    Romaissa Harid, Hichem Izeboudjen & Fouzia Houma-Bachari

  3. MARBEC, IRD, Ifremer, CNRS, Univ Montpellier, Sète, Avenue Jean Monnet, CS 30171, 34203, Sète cedex, France

    Hervé Demarcq

  4. Département Ecologie et Environnement, Université des Sciences et Technologie Houari Boumedien, BP 32 Bab Ezzouar, 16111, Alger, Algeria

    Nour El Islam Bachari

Authors
  1. Khadidja Wissal Abdallah
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Romaissa Harid
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hervé Demarcq
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Faouzi Samar
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Aicha Djabourabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hichem Izeboudjen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nour El Islam Bachari
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Fouzia Houma-Bachari
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

K.W. Abdallah: Conceptualization; Investigation; Methodology; Software; Formal Analysis; Laboratory Analysis; Writing – original draft; Writing - review & editing; R. Harid: Methodology; Formal Analysis; Laboratory Analysis; Software; Writing - review & editing; H. Demarcq: Methodology; Formal Analysis; Writing - review & editing; F. Samar: Laboratory Analysis; Formal Analysis; Writing - review & editing; A. Djabourabi: Investigation; Formal Analysis; Writing - review & editing; H. Izeboudjen : Software; Formal Analysis; Writing - review & editing; N.E. Bachari: Investigation; Methodology; Formal Analysis F. Houma-Bachari: Supervision; Investigation; Formal Analysis.

Corresponding author

Correspondence to Khadidja Wissal Abdallah.

Ethics declarations

Ethical Approval

Not applicable.

Competing Interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abdallah, K.W., Harid, R., Demarcq, H. et al. Retrieval of Micro-Phytoplankton Density using Sentinel-3 and MODIS Satellite Sensors on the Eastern Algerian Coast. Thalassas 40, 285–297 (2024). https://doi.org/10.1007/s41208-023-00624-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41208-023-00624-8

Keywords

Search

Navigation