Ocean surface partitioning strategies using ocean colour remote Sensing: A review

•Partitioning ocean surface into functional units supports research and management.•Inclusion of ocean colour remote sensing into partitioning expands its benefits.•Abiotic and/or biotic variables are used in (un)supervised classification methods.•Static and dynamic approaches are applied in mesosca...

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Published in:Progress in oceanography Vol. 155; pp. 41 - 53
Main Authors: Krug, Lilian Anne, Platt, Trevor, Sathyendranath, Shubha, Barbosa, Ana B.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.06.2017
Subjects:
artificial intelligence
case studies
chlorophyll
color
ecosystems
Iberian Peninsula
oceanography
optical properties
phytoplankton
remote sensing
Iberian Peninsula
ISSN:0079-6611, 1873-4472
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Abstract •Partitioning ocean surface into functional units supports research and management.•Inclusion of ocean colour remote sensing into partitioning expands its benefits.•Abiotic and/or biotic variables are used in (un)supervised classification methods.•Static and dynamic approaches are applied in mesoscale to global ocean partitions. The ocean surface is organized into regions with distinct properties reflecting the complexity of interactions between environmental forcing and biological responses. The delineation of these functional units, each with unique, homogeneous properties and underlying ecosystem structure and dynamics, can be defined as ocean surface partitioning. The main purposes and applications of ocean partitioning include the evaluation of particular marine environments; generation of more accurate satellite ocean colour products; assimilation of data into biogeochemical and climate models; and establishment of ecosystem-based management practices. This paper reviews the diverse approaches implemented for ocean surface partition into functional units, using ocean colour remote sensing (OCRS) data, including their purposes, criteria, methods and scales. OCRS offers a synoptic, high spatial-temporal resolution, multi-decadal coverage of bio-optical properties, relevant to the applications and value of ocean surface partitioning. In combination with other biotic and/or abiotic data, OCRS-derived data (e.g., chlorophyll-a, optical properties) provide a broad and varied source of information that can be analysed using different delineation methods derived from subjective, expert-based to unsupervised learning approaches (e.g., cluster, fuzzy and empirical orthogonal function analyses). Partition schemes are applied at global to mesoscale spatial coverage, with static (time-invariant) or dynamic (time-varying) representations. A case study, the highly heterogeneous area off SW Iberian Peninsula (NE Atlantic), illustrates how the selection of spatial coverage and temporal representation affects the discrimination of distinct environmental drivers of phytoplankton variability. Advances in operational oceanography and in the subject area of satellite ocean colour, including development of new sensors, algorithms and products, are among the potential benefits from extended use, scope and applications of ocean surface partitioning using OCRS.
AbstractList •Partitioning ocean surface into functional units supports research and management.•Inclusion of ocean colour remote sensing into partitioning expands its benefits.•Abiotic and/or biotic variables are used in (un)supervised classification methods.•Static and dynamic approaches are applied in mesoscale to global ocean partitions. The ocean surface is organized into regions with distinct properties reflecting the complexity of interactions between environmental forcing and biological responses. The delineation of these functional units, each with unique, homogeneous properties and underlying ecosystem structure and dynamics, can be defined as ocean surface partitioning. The main purposes and applications of ocean partitioning include the evaluation of particular marine environments; generation of more accurate satellite ocean colour products; assimilation of data into biogeochemical and climate models; and establishment of ecosystem-based management practices. This paper reviews the diverse approaches implemented for ocean surface partition into functional units, using ocean colour remote sensing (OCRS) data, including their purposes, criteria, methods and scales. OCRS offers a synoptic, high spatial-temporal resolution, multi-decadal coverage of bio-optical properties, relevant to the applications and value of ocean surface partitioning. In combination with other biotic and/or abiotic data, OCRS-derived data (e.g., chlorophyll-a, optical properties) provide a broad and varied source of information that can be analysed using different delineation methods derived from subjective, expert-based to unsupervised learning approaches (e.g., cluster, fuzzy and empirical orthogonal function analyses). Partition schemes are applied at global to mesoscale spatial coverage, with static (time-invariant) or dynamic (time-varying) representations. A case study, the highly heterogeneous area off SW Iberian Peninsula (NE Atlantic), illustrates how the selection of spatial coverage and temporal representation affects the discrimination of distinct environmental drivers of phytoplankton variability. Advances in operational oceanography and in the subject area of satellite ocean colour, including development of new sensors, algorithms and products, are among the potential benefits from extended use, scope and applications of ocean surface partitioning using OCRS.
The ocean surface is organized into regions with distinct properties reflecting the complexity of interactions between environmental forcing and biological responses. The delineation of these functional units, each with unique, homogeneous properties and underlying ecosystem structure and dynamics, can be defined as ocean surface partitioning. The main purposes and applications of ocean partitioning include the evaluation of particular marine environments; generation of more accurate satellite ocean colour products; assimilation of data into biogeochemical and climate models; and establishment of ecosystem-based management practices. This paper reviews the diverse approaches implemented for ocean surface partition into functional units, using ocean colour remote sensing (OCRS) data, including their purposes, criteria, methods and scales. OCRS offers a synoptic, high spatial-temporal resolution, multi-decadal coverage of bio-optical properties, relevant to the applications and value of ocean surface partitioning. In combination with other biotic and/or abiotic data, OCRS-derived data (e.g., chlorophyll-a, optical properties) provide a broad and varied source of information that can be analysed using different delineation methods derived from subjective, expert-based to unsupervised learning approaches (e.g., cluster, fuzzy and empirical orthogonal function analyses). Partition schemes are applied at global to mesoscale spatial coverage, with static (time-invariant) or dynamic (time-varying) representations. A case study, the highly heterogeneous area off SW Iberian Peninsula (NE Atlantic), illustrates how the selection of spatial coverage and temporal representation affects the discrimination of distinct environmental drivers of phytoplankton variability. Advances in operational oceanography and in the subject area of satellite ocean colour, including development of new sensors, algorithms and products, are among the potential benefits from extended use, scope and applications of ocean surface partitioning using OCRS.
Author Krug, Lilian Anne
Barbosa, Ana B.
Sathyendranath, Shubha
Platt, Trevor
Author_xml – sequence: 1
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  givenname: Shubha
  surname: Sathyendranath
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  givenname: Ana B.
  surname: Barbosa
  fullname: Barbosa, Ana B.
  email: abarbosa@ualg.pt
  organization: University of the Algarve/Centre for Marine and Environmental Research (CIMA), Campus de Gambelas, 8005-139 Faro, Portugal
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Snippet •Partitioning ocean surface into functional units supports research and management.•Inclusion of ocean colour remote sensing into partitioning expands its...
The ocean surface is organized into regions with distinct properties reflecting the complexity of interactions between environmental forcing and biological...
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SubjectTerms artificial intelligence
case studies
chlorophyll
color
ecosystems
Iberian Peninsula
oceanography
optical properties
phytoplankton
remote sensing
Title Ocean surface partitioning strategies using ocean colour remote Sensing: A review
URI https://dx.doi.org/10.1016/j.pocean.2017.05.013
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