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Advances in Remote Sensing of Phytoplankton Optical Properties and for Studies in Marine Biology

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

Deadline for manuscript submissions: 28 February 2025 | Viewed by 6801

Special Issue Editors

Dr. Monika Soja-Wozniak

E-Mail Website
Guest Editor
Freshwater and Marine Ecosystems, Faculty of Science, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
Interests: optical properties; phytoplankton; reflectance; marine optics; ocean colour; radiative transfer
Dr. Krista Alikas

E-Mail Website
Guest Editor
Faculty of Science and Technology, Tartu Observatory, University of Tartu, 61602 Tõravere, Estonia
Interests: lakes; satellite data; water quality; water quality monitoring; limnology; remote sensing; dissolved organic matter; optics; environment
Special Issues, Collections and Topics in MDPI journals
Dr. Susanne Kratzer

E-Mail Website
Guest Editor
Department of Ecology, Environment and Plant Sciences, Stockholm University, 10961 Stockholm, Sweden
Interests: marine ecology; bio-optical oceanography; marine remote sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Ana B. Ruescas

E-Mail Website
Guest Editor
University of Valencia, Brockamnn Consult GmbH, Valencia, Spain
Interests: ocean colour; machine learning; SNAP
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Optical properties of oceanic waters are mainly influenced by phytoplankton, whilst coastal and inland waters are also optically influenced by suspended particulate matter (SPM) and colored dissolved organic matter (CDOM).

Phytoplankton are microscopic, single-cell, free-floating plants or cyanobacteria that can absorb light with their pigments. Together with available nutrients, the underwater light field determines phytoplankton biomass, and ultimately the productivity of water mass. Phytoplankton absorption varies due to pigment composition and concentration, while the size and shape of phytoplankton cells change phytoplankton scattering properties. The concentration of phytoplankton pigment is commonly used as a proxy for its abundance. Most of the previous studies have been focused on chlorophyll a, the main light-absorbing pigment; however, recent studies show the importance of phytoplankton accessory pigments. Several accessory pigments are specific for certain phytoplankton groups. Remote sensing allows us to estimate not only the concentration of phytoplankton pigments but also phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). Ocean color remote sensing is an important source of data for understanding ocean phytoplankton dynamics.

This Special Issue aims for studies on the optical properties of phytoplankton by means of remote sensing methods. Topics may cover anything from the influence of phytoplankton communities on the water—leaving reflectance through phytoplankton pigment concentration—to the bio-optical properties of phytoplankton communities and optical properties of coastal as well as inland waters.

Articles may address, but are not limited to, the following topics:

  • Bio-optical properties of phytoplankton communities.
  • Phytoplankton absorption and/or scattering properties.
  • Estimation of phytoplankton biomass.
  • Phytoplankton pigment concentration.
  • Estimation of phytoplankton size classes from ocean color remote sensing.
  • Influence of phytoplankton communities on spectral remote sensing reflectance.
  • Influence of CDOM and SPM on spectral remote sensing reflectance.
  • Influence of land use and land cover on optical properties of coastal as well as inland waters.
  • Using hyperspectral measurements for phytoplankton studies.
  • Using modeling as an additional data source for remote sensing in phytoplankton studies.

Dr. Monika Soja-Wozniak
Dr. Krista Alikas
Dr. Susanne Kratzer
Dr. Ana B. Ruescas
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

  • marine optics
  • marine biology
  • phytoplankton communities
  • phytoplankton biomass
  • phytoplankton pigments

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Published Papers (3 papers)

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Research

23 pages, 4910 KiB  
Article
A Validation of OLCI Sentinel-3 Water Products in the Baltic Sea and an Evaluation of the Effect of System Vicarious Calibration (SVC) on the Level-2 Water Products
by Sean O’Kane, Tim McCarthy, Rowan Fealy and Susanne Kratzer
Remote Sens. 2024, 16(21), 3932; https://doi.org/10.3390/rs16213932 - 22 Oct 2024
Viewed by 539
Abstract
The monitoring of coastal waters using satellite data, from sensors such as Sentinel-3 OLCI, has become a vital tool in the management of these water environments, especially when it comes to improving our understanding of the effects of climate change on these regions. [...] Read more.
The monitoring of coastal waters using satellite data, from sensors such as Sentinel-3 OLCI, has become a vital tool in the management of these water environments, especially when it comes to improving our understanding of the effects of climate change on these regions. In this study, the latest Level-2 water products derived from different OLCI Sentinel-3 processors were validated against a comprehensive in situ dataset from the NW Baltic Sea proper region through a matchup analysis. The products validated were those of the regionally adapted Case-2 Regional Coast Colour (C2RCC) OLCI processor (v1.0 and v2.1), as well as the latest standard Level-2 OLCI Case-2 (neural network) products from Sentinel-3’s processing baseline, listed as follows: Baseline Collection 003 (BC003), including “CHL_NN”, “TSM_NN”, and “ADG443_NN”. These products have not yet been validated to such an extent in the region. Furthermore, the effect of the current EUMETSAT system vicarious calibration (SVC) on the Level-2 water products was also validated. The results showed that the system vicarious calibration (SVC) reduces the reliability of the Level-2 OLCI products. For example, the application of these SVC gains to the OLCI data for the regionally adapted v2.1 C2RCC products resulted in RMSD increases of 36% for “conc_tsm”; 118% for “conc_chl”; 33% for “iop_agelb”; 50% for “iop_adg”; and 10% for “kd_z90max” using a ±3 h validation window. This is the first time the effects of these SVC gains on the Level-2 OLCI water products has been isolated and quantified in the study region. The findings indicate that the current EUMETSAT SVC gains should be applied and interpreted with caution in the region of study at present. A key outcome of the paper recommends the development of a regionally specific SVC against AERONET-OC data in order to improve the Level-2 water product retrieval in the region. The results of this study are important for end users and the water authorities making use of the satellite water products in the Baltic Sea region. Full article
(This article belongs to the Special Issue Advances in Remote Sensing of Phytoplankton Optical Properties and for Studies in Marine Biology)
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19 pages, 3831 KiB  
Article
Chlorophyll-Specific Absorption Coefficient of Phytoplankton in World Oceans: Seasonal and Regional Variability
by Jianwei Wei, Menghua Wang, Karlis Mikelsons and Lide Jiang
Remote Sens. 2023, 15(9), 2423; https://doi.org/10.3390/rs15092423 - 5 May 2023
Cited by 1 | Viewed by 2339
Abstract
This study investigates the seasonal and regional variability in the chlorophyll-specific absorption coefficient of phytoplankton at 443 nm (aph*(443); unit: m2 mg−1) in surface oceans. It is focused on the time series data [...] Read more.
This study investigates the seasonal and regional variability in the chlorophyll-specific absorption coefficient of phytoplankton at 443 nm (aph*(443); unit: m2 mg−1) in surface oceans. It is focused on the time series data derived from the satellite products of chlorophyll-a (Chl-a) concentration and the phytoplankton absorption coefficient. Global estimates of aph*(443) reveal a decreasing gradient from the open ocean toward the coastal environment, with considerable spatial variance. Seasonal variations are prominent over most oceans, resulting in substantial deviations from the climatological means. A sinusoidal model was fitted to the monthly time series data to characterize the annual and semiannual features. The amplitudes and the phases of the monthly data were latitudinally dependent. The occurrence times of the maximum aph*(443) values were six months out of phase between the northern and southern hemispheres. Satellite observations present a global mean relationship between aph*(443) and Chl-a comparable with those obtained via in situ measurements. However, the seasonal/regional aph*(443) and Chl-a relationships can significantly depart from the global mean relationship. We propose a hypothesis that aph*(443) can be predicted as a function of geolocation and time. Preliminary validations with in situ matchup data confirm that the proposed model is a promising alternative to the traditional approaches requiring Chl-a as the input. The present exploration helps understand the phytoplankton biogeography and facilitates future efforts to improve bio-optical modeling, including estimating the primary production. Full article
(This article belongs to the Special Issue Advances in Remote Sensing of Phytoplankton Optical Properties and for Studies in Marine Biology)
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19 pages, 6280 KiB  
Article
Cyanobacteria Index as a Tool for the Satellite Detection of Cyanobacteria Blooms in the Baltic Sea
by Marta Konik, Katarzyna Bradtke, Joanna Stoń-Egiert, Monika Soja-Woźniak, Sylwia Śliwińska-Wilczewska and Mirosław Darecki
Remote Sens. 2023, 15(6), 1601; https://doi.org/10.3390/rs15061601 - 15 Mar 2023
Cited by 5 | Viewed by 3216
Abstract
Cyanobacteria blooms in the Baltic Sea have been studied for years due to their toxicity, which negatively affects all biota, along with the influence of these floating colonies on surface fluxes. However, mapping these blooms is still a challenge since their high dynamics, [...] Read more.
Cyanobacteria blooms in the Baltic Sea have been studied for years due to their toxicity, which negatively affects all biota, along with the influence of these floating colonies on surface fluxes. However, mapping these blooms is still a challenge since their high dynamics, wide coverage, and specific radiometric footprint hinder atmospheric correction and negatively affect the quality of satellite images. In this study, we assessed the use of an alternative approach called the cyanobacteria index (CI), which is based on the reflectance spectral shape and which does not require comprehensive atmospheric correction. We demonstrated a close relationship between the positive CI values, indicating the presence of blooms, and the concentration of phycocyanin, the marker pigment of filamentous cyanobacteria in the Baltic Sea. We proved that the CI index could efficiently identify cyanobacteria-dominated blooms where colonies floated near the surface. Therefore, this index represents a valuable complement to the previous monitoring methods, suitable for extreme bloom events. The analysis of a time series of satellite images obtained between 2002 and 2018 using the CI index revealed the elongation of the bloom season, which may have been a consequence of the water temperature remaining within the cyanobacteria’s tolerance range for a longer time. Full article
(This article belongs to the Special Issue Advances in Remote Sensing of Phytoplankton Optical Properties and for Studies in Marine Biology)
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