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Retrieving Marine Inherent Optical Properties and Biogeochemistry from Hyperspectral Measurements

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 6614

Special Issue Editors


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Guest Editor
NASA Goddard Space Flight Center, Mail Code: 616.2, Greenbelt, MD 20771, USA
Interests: satellite ocean color; bio-optics; remote sensing; phytoplankton

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Guest Editor
University of New Hampshire, 8 College Road, OPAL/Morse Hall, Durham, NH 03824, USA
Interests: bio-optical algorithms; aquatic remote sensing for oceans and lakes; phytoplankton dynamics; ecological trends

Special Issue Information

Dear Colleagues,

Ocean color satellite instruments provide daily observations of the upwelling spectral light field from which estimates of marine inherent optical properties (IOPs) are generated. The spectral absorption and backscattering coefficients of the surface water column are the two prime IOPs that describe the contents of the upper ocean, information critical to furthering scientific understanding of biogeochemical processes such as carbon exchanges, phytoplankton biodiversity shifts, and aquatic biogeochemistry responses to climatic disturbances. As such, the international community has invested significant effort into ensuring and improving the quality of determining IOPs from in situ measurements, bio-optical models, and ultimately, from ocean color satellite radiometry.

Upcoming satellite missions, such as the NASA Plankton, Aerosols, Clouds, ocean Ecosystem (PACE) mission, will provide far more spectral information than their predecessors. The planned PACE instrument payload will provide continuous spectra at ~5-nm resolution across the light spectrum from the ultraviolet through the near-infrared, a substantial increase over heritage satellite radiometers that provided only several wavebands in this domain. Instrument and algorithm advances are needed to support and take advantage of the new information available from the expected near hyperspectral signal from PACE. It follows that the time is right to pursue novel methods for deriving marine IOPs and aquatic biogeochemical parameters from hyperspectral measurements of ocean color. This Special Issue will highlight how space-borne spectroscopy can improve the quality of remotely-sensed bio-optical and biogeochemical data products. We are inviting submissions including, but not limited to, the derivation of the following from hyperspectral ocean color:

  • Absorption by phytoplankton, non-algal particles, and CDOM
  • Backscattering by phytoplankton and non-algal particles
  • Phytoplankton community composition, including harmful algal blooms
  • Phytoplankton physiological parameters
  • Carbon stocks and processes
  • Indices of water quality for watershed management (e.g., light penetration and turbidity)
  • Atmospheric (correction) parameters that improve estimates of remote-sensing reflectance

Dr. Jeremy Werdell
Dr. Timothy Moore
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ocean color
  • satellite remote sensing
  • radiative transfer theory
  • bio-optics
  • aquatic biogeochemistry
  • phytoplankton community composition
  • inherent optical properties
  • spectroscopy
  • semi-analytical algorithms
  • derivative analyses
  • PACE

Published Papers (1 paper)

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Research

32 pages, 22809 KiB  
Article
Retrieval of Phytoplankton Pigments from Underway Spectrophotometry in the Fram Strait
by Yangyang Liu, Emmanuel Boss, Alison Chase, Hongyan Xi, Xiaodong Zhang, Rüdiger Röttgers, Yanqun Pan and Astrid Bracher
Remote Sens. 2019, 11(3), 318; https://doi.org/10.3390/rs11030318 - 6 Feb 2019
Cited by 17 | Viewed by 6200
Abstract
Phytoplankton in the ocean are extremely diverse. The abundance of various intracellular pigments are often used to study phytoplankton physiology and ecology, and identify and quantify different phytoplankton groups. In this study, phytoplankton absorption spectra ( a p h ( λ ) ) [...] Read more.
Phytoplankton in the ocean are extremely diverse. The abundance of various intracellular pigments are often used to study phytoplankton physiology and ecology, and identify and quantify different phytoplankton groups. In this study, phytoplankton absorption spectra ( a p h ( λ ) ) derived from underway flow-through AC-S measurements in the Fram Strait are combined with phytoplankton pigment measurements analyzed by high-performance liquid chromatography (HPLC) to evaluate the retrieval of various pigment concentrations at high spatial resolution. The performances of two approaches, Gaussian decomposition and the matrix inversion technique are investigated and compared. Our study is the first to apply the matrix inversion technique to underway spectrophotometry data. We find that Gaussian decomposition provides good estimates (median absolute percentage error, MPE 21–34%) of total chlorophyll-a (TChl-a), total chlorophyll-b (TChl-b), the combination of chlorophyll-c1 and -c2 (Chl-c1/2), photoprotective (PPC) and photosynthetic carotenoids (PSC). This method outperformed one of the matrix inversion algorithms, i.e., singular value decomposition combined with non-negative least squares (SVD-NNLS), in retrieving TChl-b, Chl-c1/2, PSC, and PPC. However, SVD-NNLS enables robust retrievals of specific carotenoids (MPE 37–65%), i.e., fucoxanthin, diadinoxanthin and 19 -hexanoyloxyfucoxanthin, which is currently not accomplished by Gaussian decomposition. More robust predictions are obtained using the Gaussian decomposition method when the observed a p h ( λ ) is normalized by the package effect index at 675 nm. The latter is determined as a function of “packaged” a p h ( 675 ) and TChl-a concentration, which shows potential for improving pigment retrieval accuracy by the combined use of a p h ( λ ) and TChl-a concentration data. To generate robust estimation statistics for the matrix inversion technique, we combine leave-one-out cross-validation with data perturbations. We find that both approaches provide useful information on pigment distributions, and hence, phytoplankton community composition indicators, at a spatial resolution much finer than that can be achieved with discrete samples. Full article
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