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Special Issue "Remote Sensing of Ocean Colour: Theory and Applications"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: 31 July 2019

Special Issue Editors

Guest Editor
Prof. Trevor Platt

Plymouth Marine Laboratory, Plymouth PL1 3DH, United Kingdom
Website | E-Mail
Interests: the physiological ecology of marine phytoplankton; structure and function of the marine ecosystem; submarine optics; remote sensing of ocean colour; the ocean carbon cycle and climate change, and the ecological approach to fisheries management
Guest Editor
Dr. Shubha Sathyendranath

Plymouth Marine Laboratory, Plymouth PL1 3DH, United Kingdom
Website | E-Mail
Interests: ocean colour modelling; spectral characteristics of light penetration underwater; bio-optical properties of phytoplankton; modelling primary production; bio-geochemical cycles in the sea; climate change; biological–physical interactions in the marine system; ecological provinces in the sea; ecological indicators and phytoplankton functional types
Guest Editor
Dr. Heather Bouman

Department of Earth Sciences, University of Oxford
E-Mail
Interests: polar ecosystems; community structure of phytoplankton; meta-analysis of phytoplankton data; bio-optical properties of phytoplankton; and primary production
Guest Editor
Dr. David McKee

Department of Physics, University of Strathclyde
E-Mail
Interests: optical sensors; remote sensing of ocean colour; radiative transfer in the ocean; propagation of measurement uncertainties; and optically complex waters
Guest Editor
Dr. Carsten Brockmann

Brockmann Consult GmbH
E-Mail
Interests: optical remote sensing; radiative transfer; remote sensing of water quality; remote sensing and climate change; calibration and validation of remotely-sensed signals; software design for earth observation (EO) data processing and image analysis; and analysis ready data

Special Issue Information

The Special Issue will deal with the theory and applications of ocean-colour remote sensing. The scope will include, but not be restricted to the following:

  • Optical theory for ocean colour
  • Atmospheric correction
  • Calibration and validation of ocean-colour signals
  • The underwater light field
  • Ocean colour in optically-complex waters
  • Ocean colour in lakes
  • Sensors, instruments, and micro-satellite missions for ocean colour
  • Ocean colour and ocean biogeochemistry
  • Ocean colour and ecological indicators; ocean colour for reporting to legislation
  • Ocean colour and the spatial structure of the global marine ecosystem
  • Analysis of time series of ocean-colour products
  • Estimation of primary production from ocean colour

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 papers will be 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. Sensors is an international peer-reviewed open access monthly 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 1800 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

  • Earth observation
  • Remote sensing
  • Ocean colour
  • Phytoplankton
  • Marine optics

Published Papers (1 paper)

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Research

Open AccessArticle Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching
Sensors 2018, 18(11), 3599; https://doi.org/10.3390/s18113599
Received: 4 September 2018 / Revised: 11 October 2018 / Accepted: 22 October 2018 / Published: 23 October 2018
PDF Full-text (13923 KB) | HTML Full-text | XML Full-text
Abstract
Geometric correction is fundamental in producing high quality satellite data products. However, the geometric correction for ocean color sensors, e.g., Geostationary Ocean Color Imager (GOCI), is challenging because the traditional method based on ground control points (GCPs) cannot be applied when the shoreline
[...] Read more.
Geometric correction is fundamental in producing high quality satellite data products. However, the geometric correction for ocean color sensors, e.g., Geostationary Ocean Color Imager (GOCI), is challenging because the traditional method based on ground control points (GCPs) cannot be applied when the shoreline is absent. In this study, we develop a hybrid geometric correction method, which applies shoreline matching and frequency matching on slots with shorelines and without shorelines, respectively. Frequency matching has been proposed to estimate the relative orientation between GOCI slots without a shoreline. In this paper, we extend our earlier research for absolute orientation and geometric correction by combining frequency matching results with shoreline matching ones. The proposed method consists of four parts: Initial sensor modeling of slots without shorelines, precise sensor modeling through shoreline matching, relative orientation modeling by frequency matching, and generation of geometric correction results using a combination of the two matching procedures. Initial sensor modeling uses the sensor model equation for GOCI and metadata in order to remove geometric distortion due to the Earth’s rotation and curvature in the slots without shorelines. Precise sensor modeling is performed with shoreline matching and random sample consensus (RANSAC) in the slots with shorelines. Frequency matching computes position shifts for slots without shorelines with respect to the precisely corrected slots with shorelines. GOCI Level 1B scenes are generated by combining the results from shoreline matching and frequency matching. We analyzed the accuracy of shoreline matching alone against that of the combination of shoreline matching and frequency matching. Both methods yielded a similar accuracy of 1.2 km, which supports the idea that frequency matching can replace traditional shoreline matching for slots without visible shorelines. Full article
(This article belongs to the Special Issue Remote Sensing of Ocean Colour: Theory and Applications)
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