Special Issue "Sentinel-3 Satellites: A Three-sensor Mission to Observe the Physical, Bio-optical and Biogeochemical Properties of Marine/Water Bodies"

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

Deadline for manuscript submissions: closed (31 July 2020).

Special Issue Editors

Dr. Stefano Vignudelli
Website SciProfiles
Guest Editor
Consiglio Nazionale delle Ricerche (CNR), Area della Ricerca CNR S. Cataldo, Via Moruzzi 1, 56100 Pisa, Italy
Interests: ocean and land remote sensing; satellite radar altimetry; water level; coastal zone; inland waters
Special Issues and Collections in MDPI journals
Dr. Jorge Vazquez
Website
Guest Editor
Jet Propulsion Laboratory/California Institute of Technology, Pasadena, CA 91109, USA
Interests: validation of remote sensing data; application of remote sensing to coastal regions; development of new remote sensing for high resolution; Validation of remote sensing data sets in challenging areas, including the Arctic and coastal regions
Special Issues and Collections in MDPI journals
Dr. Emmanuel Devred

Guest Editor
Ocean and Ecosystem Sciences Division, Bedford Institute of Oceanography, Fisheries and Oceans, Canada
Interests: Phytoplankton ecology, bio-optics; satellite ocean colour; climate change; coastal oceanography; ecosystem dynamics
Special Issues and Collections in MDPI journals
Assoc. Prof. Cédric Jamet
Website
Guest Editor
Univ. Littoral Cote d’Opale, Univ. Lille, CNRS, UMR 8187, LOG, Laboratoire d’Océanologie et de Géosciences, 62930 Wimereux, France
Interests: remote sensing of ocean color, atmospheric correction, inversion techniques for the estimation of biogeochemical parameters
Dr. Oleg Kopelevich
Website
Guest Editor
Russian Acad Sci, PP Shirshov Inst Oceanol, Moscow 117997, Russia
Interests: seawater optical properties; optical methods; satellite ocean color; field studies; regional algorithms; climatic factors
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The Sentinel-3 satellite, as part of the European Copernicus program, is primarily an ocean mission. The Sentinel-3A satellite was launched in February 2016 and has been in routine phase since October 2017. The twin Sentinel-3B satellite was launched in April 2018. During the commissioning phase, the two satellites have been positioned in tandem configuration, separated by 30 seconds. Once Sentinel-3B is operational, it will fly in the same orbit of Sentinel-3A, but 140° ahead. Each satellite carries three main sensors, specifically an SAR radar altimeter, SST radiometer and ocean colour imager, revisiting the same place every 2 days with the two satellites. In this Special Issue we invite contributions highlighting how Sentinel-3 data are improved (technologies, algorithms, etc.) and used (also in combination/synergy with in situ and other satellite missions and/or modelling tools) to contribute to the study/research/monitoring (also operationally) of the ocean from the global to the coastal scale. Of particular interest are also studies addressing synergies between the three Sentinel-3 sensors. Comparative studies made possible by the Sentinel-3A/B tandem phase are also encouraged. Work that seeks to build on the previous records of SST, Ocean Color, and altimetry are also encouraged (especially with ENVISAT). This includes improvements in quality and consistency with applications to interannual and climate scale variability.

Examples include:

  1. Development of the OLCI regional algorithms for retrieval of the bio-optical parameters in Case 2 waters and their validation using in situ data.
  2. Joining the satellite data products from OLCI, MODIS and MERIS sensors to build long-term series of bio-optical data and sea surface temperature data. For SST built on the results of the SST special collection, see https://www.mdpi.com/journal/remotesensing/special_issues/SST_RS
  3. Using OLCI and SLSTR data to estimate the changes in the amount of solar radiation entering the waters of the Arctic sea and analyze the causes and consequences. Use of these products for the validation of SST and Ocean Colour in the Arctic is encouraged.
  4. Use of the parameters derived from OLCI and SLSTR data as essential climate variables.
  5. Sentinel-3 radar altimetry for studies on ocean circulation variability, sea level changes, extreme events (storm surges and hurricanes), ocean wave field, assimilation of data in models, etc.
  6. Sentinel-3 radar altimetry in the coastal zone: progress on waveform modelling and retracking, improvements in corrections (SSB, wet troposphere, tides, etc.); assessment of coastal altimetry; calibration and validation of coastal altimetry data; intercalibration against various missions; applications of coastal altimetry data, including the usage of data from the various providers (e.g., SARvatore, SAR Versatile Altimetric Toolkit for Ocean Research and Exploitation for Sentinel-3).
  7. Synergy between S3A and S3B for following high-spatial and frequency events over coastal waters and inland seas.

Dr. Stefano Vignudelli
Dr. Jorge Vazquez
Dr. Emmanuel Devred
Dr. Cédric Jamet
Dr. Oleg Kopelevich
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 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. 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 2200 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
  • inland and coastal waters
  • synergy
  • radar altimetry
  • sea level
  • wave
  • currents
  • SST
  • regional algorithms
  • long-term series
  • solar radiation
  • essential climate variables

Published Papers (3 papers)

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Research

Open AccessArticle
Sentinel-3A SRAL Global Statistical Assessment and Cross-Calibration with Jason-3
Remote Sens. 2019, 11(13), 1573; https://doi.org/10.3390/rs11131573 - 03 Jul 2019
Cited by 1
Abstract
The Sentinel-3A satellite, equipped with Synthetic Aperture Radar (SAR) Altimeter (SRAL) instrument to derive sea surface height, significant wave height and surface wind speed over the global ocean, was launched on 16 February 2016. The assessment of data quality and the system performance [...] Read more.
The Sentinel-3A satellite, equipped with Synthetic Aperture Radar (SAR) Altimeter (SRAL) instrument to derive sea surface height, significant wave height and surface wind speed over the global ocean, was launched on 16 February 2016. The assessment of data quality and the system performance of the altimeter are very important to data application. In this article, Sentinel-3A SRAL data quality is assessed and altimetry system performance is estimated by verifying data availability and monitoring the parameters of altimeter and radiometer through the global statistical analyses of Sentinel-3A Non-Time-Critical (NTC) Marine Level 2 products during the period from 13 March 2016 to 25 February 2019, in comparison with self-crossovers and cross-calibration with the Jason-3 mission. The global statistical analyses and the comparisons at self-crossovers show that Sentinel-3A SRAL data and performance are stable and have no trend over time, and the total cycle average root mean square errors (RMSEs) of sea surface height (SSH) differences at self-crossovers is about 5.4 cm. The comparisons at the dual-crossovers show the consistency of the observation between Sentinel-3A SRAL and Jason-3, and indicate that the systemic bias of SSH is about 2.96 cm. In general, it can be concluded that Sentinel-3A SRAL has good and stable data quality and system performance for operational ocean forecasting and scientific research. Full article
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Open AccessFeature PaperArticle
Evaluation of Five Atmospheric Correction Algorithms over French Optically-Complex Waters for the Sentinel-3A OLCI Ocean Color Sensor
Remote Sens. 2019, 11(6), 668; https://doi.org/10.3390/rs11060668 - 19 Mar 2019
Cited by 10
Abstract
The Sentinel-3A satellite was launched on 16 February 2016 with the Ocean and Land Colour Instrument (OLCI-A) on-board for the study of ocean color. The accuracy of ocean color parameters depends on the atmospheric correction algorithm (AC). This processing consists of removing the [...] Read more.
The Sentinel-3A satellite was launched on 16 February 2016 with the Ocean and Land Colour Instrument (OLCI-A) on-board for the study of ocean color. The accuracy of ocean color parameters depends on the atmospheric correction algorithm (AC). This processing consists of removing the contribution of the atmosphere from the total measured signal by the remote sensor at the top of the atmosphere. Five ACs: the baseline AC, the Case 2 regional coast color neural network AC, its alternative version, the Polymer AC, and the standard NASA AC, are inter-compared over two bio-optical contrasted French coastal waters. The retrieved water-leaving reflectances are compared with in situ ocean color radiometric measurements collected using an ASD FielSpec4 spectrometer. Statistical and spectral analysis were performed to assess the best-performing AC through individual (relative error (RE) at 412 nm ranging between 23.43 and 57.31%; root mean squared error (RMSE) at 412 nm ranging between 0.0077 and 0.0188) and common (RE(412 nm) = 24.15–50.07%; RMSE(412 nm) = 0.0081–0.0132) match-ups. The results suggest that the most efficient schemes are the alternative version of the Case 2 regional coast color neural network AC with RE(412 nm) = 33.52% and RMSE(412 nm) = 0.0101 for the individual and Polymer with RE(412 nm) = 24.15% and RMSE(412 nm) = 0.0081 for the common ACs match-ups. Sensitivity studies were performed to assess the limitations of the AC, and the errors of retrievals showed no trends when compared to the turbidity and CDOM. Full article
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Open AccessArticle
Unsupervised Sub-Pixel Water Body Mapping with Sentinel-3 OLCI Image
Remote Sens. 2019, 11(3), 327; https://doi.org/10.3390/rs11030327 - 07 Feb 2019
Cited by 6
Abstract
Mapping land surface water bodies from satellite images is superior to conventional in situ measurements. With the mission of long-term and high-frequency water quality monitoring, the launch of the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A and Sentinel-3B provides the best possible [...] Read more.
Mapping land surface water bodies from satellite images is superior to conventional in situ measurements. With the mission of long-term and high-frequency water quality monitoring, the launch of the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A and Sentinel-3B provides the best possible approach for near real-time land surface water body mapping. Sentinel-3 OLCI contains 21 bands ranging from visible to near-infrared, but the spatial resolution is limited to 300 m, which may include lots of mixed pixels around the boundaries. Sub-pixel mapping (SPM) provides a good solution for the mixed pixel problem in water body mapping. In this paper, an unsupervised sub-pixel water body mapping (USWBM) method was proposed particularly for the Sentinel-3 OLCI image, and it aims to produce a finer spatial resolution (e.g., 30 m) water body map from the multispectral image. Instead of using the fraction maps of water/non-water or multispectral images combined with endmembers of water/non-water classes as input, USWBM directly uses the spectral water index images of the Normalized Difference Water Index (NDWI) extracted from the Sentinel-3 OLCI image as input and produces a water body map at the target finer spatial resolution. Without the collection of endmembers, USWBM accomplished the unsupervised process by developing a multi-scale spatial dependence based on an unsupervised sub-pixel Fuzzy C-means (FCM) clustering algorithm. In both validations in the Tibet Plate lake and Poyang lake, USWBM produced more accurate water body maps than the other pixel and sub-pixel based water body mapping methods. The proposed USWBM, therefore, has great potential to support near real-time sub-pixel water body mapping with the Sentinel-3 OLCI image. Full article
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