Submit to Remote Sensing Review for Remote Sensing Propose a Special Issue

Journal Browser

► Journal Browser

Remote Sensing Monitoring of Ocean and Coastal Biogeochemistry

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

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

Deadline for manuscript submissions: closed (30 October 2022) | Viewed by 14229

Share This Special Issue

Special Issue Editors

Dr. Hae-Cheol Kim

E-Mail Website
Guest Editor

University Corporation for Atmospheric Research at NOAA/GFDL, Princeton University Forrestal Campus, 201 Forrestal Road, Princeton, NJ 08540, USA
Interests: ocean color; primary productivity of benthic, coastal and oceanic waters; biogeochemically-physically coupled modelling; bio-optics; ecological modeling and forecasting; data assimilation
Special Issues, Collections and Topics in MDPI journals

Dr. SeungHyun Son

E-Mail Website
Guest Editor

Cooperative Institute for Research in the Atmosphere at NOAA/NESDIS/STAR, Colorado State University, NCWCP Building, 5830 University Research Court, College Park, MD 20740, USA
Interests: remote sensing; ocean color; bio-optical algorithms; water quality; phytoplankton productivity; human-/climate-induced changes in marine ecosystems
Special Issues, Collections and Topics in MDPI journals

Dr. Veronica P. Lance

E-Mail Website
Guest Editor

NOAA Coast Watch/Ocean Watch/Polar Watch, NCWCP building, 5830 University Research Court, College Park, MD 20740, USA
Interests: primary productivity; ocean biogeochemistry; ocean satellite remote sensing; ocean color remote sensing; applications for remote sensing data; user training

Dr. Paul M. DiGiacomo

E-Mail Website
Guest Editor

NOAA/NESDIS Center for Satellite Applications and Research (STAR), Chief, Satellite Oceanography and Climatology Division (SOCD), Co-Chair, GEO Blue Planet Initiative, NCWCP Building, 5830 University Research Court, College Park, MD 20740, USA
Interests: marine ecosystem dynamics and biogeochemical cycles; multisensor remote sensing of inland, coastal, and oceanic waters; development and implementation of global and coastal ocean observing networks; linking coastal/ocean data providers and users for research, applications, and management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Accurate predictions of physical/biogeochemical states of marine environments will allow for a wide variety of applications in various time scales, from subseasonal to decadal. Some examples can include real-time monitoring of environmental stressors, seasonal migration of fish stock, larval transport, long-term ecological regime-shift of marine resources, and climate-driven and/or anthropogenic air–sea carbon dioxide dynamics. Such predictions will facilitate the coastal environment management, fishing industry, and fisheries management in establishing more realistic policies and better decision-making. However, due to the spatiotemporal limitations in observations, understanding regional and global marine environmental states has been a challenging task.

Ocean satellite instruments provide timely observations of important marine environmental properties, such as sea surface temperature, sea surface salinity, sea surface height, sea surface winds, sea ice coverage, as well as ocean color. While ocean satellite observations are limited to 2-dimensional surface fields with limited temporal resolutions, they are complementary to those observations from other measurement platforms (e.g., ships, buoys, floats, gliders, drones) given their broader spatial coverage (regional to global), frequent repeats (minutes to days), and time-series looks ranging from synoptic to long-term (multiple satellite mission time scales from years to decades). Remotely-sensed ocean color (e.g., chlorophyll-a concentration and the diffuse attenuation coefficients at 490 nm (K_d(490)) and for photosynthetically available radiation (K_dPAR)) is frequently used for deriving up-to-date, biogeochemically-relevant information such as phytoplankton biomass and estimates of primary productivity which are, in turn, important in understanding marine food webs, nutrient and carbon cycling, ecological conditions, etc. Much effort has been made to advance sensing technologies and data processing in marine ecology and biogeochemistry, and their applications are expanding to more diverse properties, other than chlorophyll. Thus, remote sensing has been playing a pivotal role in interdisciplinary oceanographic progress, and it is also through these satellite products from multiple platforms equipped with various ocean-observing sensors that we can provide a foundational path for emerging technologies, such as artificial intelligence with big data and data assimilative physical/biogeochemical modeling in support of the end-users’ strategic objectives.

In this Special Issue, we are seeking contributions concerning, but not limited to, applications of remote-sensing data/techniques combined with other approaches to better monitor and/or understand coastal and oceanic marine biogeochemical processes. Especially manuscripts using novel statistical techniques or deterministic approaches with satellite products to derive or map secondary biogeochemical properties of interests are welcome.

Dr. Hae-Cheol Kim
Dr. Seunghyun Son
Dr. Veronica P. Lance
Dr. Paul M. DiGiacomo
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 and coastal and oceanic biogeochemistry
Ocean color and coastal and oceanic primary productivity
Ocean color and regional biogeochemical processes
Ocean color and climate processes
Ocean color and data assimilation
Ocean color and coastal water quality management
Ocean color and marine living resources
Ocean color and decision supporting tools

Published Papers (5 papers)

Download All Papers

Research

Jump to: Other

18 pages, 13080 KiB

Open AccessArticle

Variability of Marine Particle Size Distributions and the Correlations with Inherent Optical Properties in the Coastal Waters of the Northern South China Sea

by Zuomin Wang, Shuibo Hu, Qingquan Li, Huizeng Liu and Guofeng Wu

Remote Sens. 2022, 14(12), 2881; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14122881 - 16 Jun 2022

Cited by 2 | Viewed by 1626

Abstract

Particle size distribution (PSD), which is an important characteristic of marine suspended particles, plays a role in how light transfers in the ocean and impacts the ocean’s inherent optical properties (IOPs). However, PSD properties and the correlations with IOPs are rarely reported in coastal waters with complex optical properties. This study investigated the PSD variabilities both for the surface water and the water in vertical planes, and the correlations between PSD and the backscattering coefficient (b_bp), scattering coefficient (b_p), and attenuation coefficient (c_p), based on in situ PSD observations (within a size range of 2.05–297 μm) and IOPs in the coastal northern South China Sea. The results show a large variety of PSDs, with a range of 41.06–263.02 μm for the median particle diameter (D_v⁵⁰) and a range of 2.61–3.74 for the PSD slope. In addition, the predominance of small particles is most likely to appear in the nearshore shallow water and estuaries with a large amount of sediment discharge, and vice versa. For the variabilities of IOPs, the particle concentration in a cross-sectional area (AC) is the first driving factor of the variations of b_bp, b_p, and c_p, and the product of the mean particle diameter (D_A) and the apparent density (ρ_a) can explain most variations of the mass-specific b_bp (b_bp/SPM), b_p (b_p/SPM), and c_p (c_p/SPM). In this study, we found that particle size is strongly correlated with volume-specific b_bp (b_bp/VC), b_p (b_p/VC), and c_p (c_p/VC), and the 10th percentile diameter of the accumulated volume concentration (D_v¹⁰) can better explain the variations of b_bp/VC. These findings suggest a potential PSD retrieval method utilizing the b_bp or b_p, which may be determined by remote sensing observations. Full article

(This article belongs to the Special Issue Remote Sensing Monitoring of Ocean and Coastal Biogeochemistry)

► Show Figures

Graphical abstract

16 pages, 3704 KiB

Open AccessArticle

A Four-Step Method for Estimating Suspended Particle Size Based on In Situ Comprehensive Observations in the Pearl River Estuary in China

by Zuomin Wang, Shuibo Hu, Qingquan Li, Huizeng Liu, Xiaomei Liao and Guofeng Wu

Remote Sens. 2021, 13(24), 5172; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13245172 - 20 Dec 2021

Cited by 6 | Viewed by 2611

Abstract

The suspended particle size has great impacts on marine biology environments and biogeochemical processes, such as the settling rates of particles and sunlight transmission in marine water. However, the spatial–temporal variations in particle sizes in coastal waters are rarely reported due to the paucity of appropriate observations and the limitations of particle size retrieval methods, especially in areas with complex optical properties. This study proposed a remote sensing-based method for estimating the median particle size D_v⁵⁰ (calculated with a size range of 2.05–297 μm) that correlates D_v⁵⁰ with the inherent optical properties (IOPs) retrieved from in situ remote sensing reflectance above the water’s surface (R_rs(λ)) in the Pearl River estuary (PRE) in China. R_rs(λ) was resampled to simulate the Multispectral Instrument (MSI) onboard Sentinel-2A/B, and the wavebands in 490, 560, and 705 nm were utilized for the retrieval of the IOPs. The results of this method had a statistical performance of 0.86, 18.52, 21.28%, and −1.85 for the R², RMSE, MAPE, and bias values, respectively, in validation, which indicated that D_v⁵⁰ could be estimated by R_rs(λ) with the proposed four-step method. Then, the proposed method was applied to Sentinel-2 MSI imagery, and a clear difference in D_v⁵⁰ distribution which was retrieved from a different time could be seen. The proposed method holds great potential for monitoring the suspended particle size of coastal waters. Full article

(This article belongs to the Special Issue Remote Sensing Monitoring of Ocean and Coastal Biogeochemistry)

► Show Figures

Figure 1

15 pages, 32247 KiB

Open AccessArticle

Assessing the Skills of a Seasonal Forecast of Chlorophyll in the Global Pelagic Oceans

by Cecile S. Rousseaux, Watson W. Gregg and Lesley Ott

Remote Sens. 2021, 13(6), 1051; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13061051 - 10 Mar 2021

Cited by 6 | Viewed by 2507

Abstract

While forecasts of atmospheric variables, and to a lesser degree ocean circulation, are relatively common, the forecast of biogeochemical conditions is still in its infancy. Using a dynamical ocean biogeochemical forecast forced by seasonal forecasts of atmospheric and physical ocean variables, we produce seasonal predictions of chlorophyll concentration at the global scale. Results show significant Anomaly Correlation Coefficients (ACCs) for the majority of regions (11 out of the 12 regions for the 1-month lead forecast). Root mean square errors are smaller (<0.05 µg chlorophyll (chl) L⁻¹) in the Equatorial regions compared to the higher latitudes (range from 0.05 up to 0.13 µg chl L⁻¹). The forecast for all regions except three (North Atlantic, South Pacific and North Indian) are within the Semi-Interquartile Range of the satellite chlorophyll concentration (Suomi-National Polar-orbiting Partnership (NPP), 27.9%). This suggests the potential for skillful global biogeochemical forecasts on seasonal timescales of chlorophyll, primary production and harmful algal blooms that could support fisheries management and other applications. Full article

(This article belongs to the Special Issue Remote Sensing Monitoring of Ocean and Coastal Biogeochemistry)

► Show Figures

Graphical abstract

27 pages, 4141 KiB

Open AccessArticle

Assessing Phytoplankton Bloom Phenology in Upwelling-Influenced Regions Using Ocean Color Remote Sensing

by Afonso Ferreira, Vanda Brotas, Carla Palma, Carlos Borges and Ana C. Brito

Remote Sens. 2021, 13(4), 675; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13040675 - 13 Feb 2021

Cited by 15 | Viewed by 4620

Abstract

Phytoplankton bloom phenology studies are fundamental for the understanding of marine ecosystems. Mismatches between fish spawning and plankton peak biomass will become more frequent with climate change, highlighting the need for thorough phenology studies in coastal areas. This study was the first to assess phytoplankton bloom phenology in the Western Iberian Coast (WIC), a complex coastal region in SW Europe, using a multisensor long-term ocean color remote sensing dataset with daily resolution. Using surface chlorophyll a (chl-a) and biogeophysical datasets, five phenoregions (i.e., areas with coherent phenology patterns) were defined. Oceanic phytoplankton communities were seen to form long, low-biomass spring blooms, mainly influenced by atmospheric phenomena and water column conditions. Blooms in northern waters are more akin to the classical spring bloom, while blooms in southern waters typically initiate in late autumn and terminate in late spring. Coastal phytoplankton are characterized by short, high-biomass, highly heterogeneous blooms, as nutrients, sea surface height, and horizontal water transport are essential in shaping phenology. Wind-driven upwelling and riverine input were major factors influencing bloom phenology in the coastal areas. This work is expected to contribute to the management of the WIC and other upwelling systems, particularly under the threat of climate change. Full article

(This article belongs to the Special Issue Remote Sensing Monitoring of Ocean and Coastal Biogeochemistry)

► Show Figures

Graphical abstract

Other

Jump to: Research

12 pages, 4293 KiB

Open AccessTechnical Note

Winter–Spring Phytoplankton Phenology Associated with the Kuroshio Extension Instability

by Eko Siswanto, Yoshikazu Sasai, Kazuhiko Matsumoto and Makio C. Honda

Remote Sens. 2022, 14(5), 1186; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14051186 - 28 Feb 2022

Cited by 1 | Viewed by 1451

Abstract

We used ocean color data of chlorophyll-a (CHL) from the period 1998 to 2017 to investigate phytoplankton phenology during winter–spring in association with the Kuroshio Extension (KE) instability. In the areas south of the KE, CHLs tended to be higher in winter during periods of unstable KEs (compared to stable KEs) which were attributed to the increases in nutrient and light availability. Nutrients were supplied from the deep layer due to physical processes indicated by negative sea surface height anomalies (SSHAs) and shallow mixed layer depths (MLDs). The increase in light availability could be attributed to greater exposure of phytoplankton to light in the shallower MLD. The same physical processes also explained higher CHLs in spring during unstable KEs. We also found that CHLs could possibly be lower during unstable KEs in spring which might be related to warmer SSTs in winter–spring. On average, the onset of the phytoplankton spring bloom south of the KE tended to be 1–3 weeks earlier during the period of unstable KEs than during the period of stable KEs. Whether this difference of 1–3 weeks impacts high-trophic-level organisms should be investigated in future studies. Full article

(This article belongs to the Special Issue Remote Sensing Monitoring of Ocean and Coastal Biogeochemistry)

► Show Figures