Estuaries and Coasts

, Volume 33, Issue 2, pp 428–439 | Cite as

Diagnostic Properties of Phytoplankton Time Series from Remote Sensing

  • Trevor Platt
  • Shubha Sathyendranath
  • George N. WhiteIII
  • César Fuentes-Yaco
  • Li Zhai
  • Emmanuel Devred
  • Charles Tang


Remote sensing provides our only window into the phytoplankton community on synoptic scales, permitting the construction of spatially distributed time series of biomass indexed as chlorophyll concentration. Data from the SeaWiFS mission have accumulated to the point where they meet the criterion of a 10-year series. The seasonal phytoplankton cycle is the dominant mode of temporal variability. The time series can be used to construct a variety of ecological indicators of the pelagic system useful in ecosystem-based management. These are reviewed and examples of their implementation are presented. Phenology of phytoplankton blooms is given particular attention. Interannual variation in some of the indicators is strong, presumably a response to variation in large-scale forcing. Examination of the results in the context of a simple phytoplankton-nutrient model enhances the interpretation. Remote sensing imagery also lends itself to the retrieval of information on community structure, in addition to biomass. More information will be recovered from satellite imagery if the remote-sensing program is coupled closely to a ship program on which appropriate bio-optical observations are made. The data series can be distilled to yield concise descriptions of the unfolding of ecosystem characteristics through time.


Ecological indicators Phytoplankton Ocean colour Remote sensing Phenology 


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Copyright information

© Coastal and Estuarine Research Federation 2009

Authors and Affiliations

  • Trevor Platt
    • 1
    • 2
  • Shubha Sathyendranath
    • 1
  • George N. WhiteIII
    • 2
  • César Fuentes-Yaco
    • 3
  • Li Zhai
    • 3
  • Emmanuel Devred
    • 3
  • Charles Tang
    • 2
  1. 1.Plymouth Marine LaboratoryPlymouthUK
  2. 2.Coastal Ocean ScienceBedford Institute of OceanographyDartmouthCanada
  3. 3.Oceanography DepartmentDalhousie UniversityHalifaxCanada

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