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Seawater Bio-Optical Characteristics from Satellite Ocean Color Data

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

Deadline for manuscript submissions: closed (15 August 2022) | Viewed by 27276

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Special Issue Editors

Dr. Dmitry Glukhovets

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Guest Editor

Shirshov Institute of Oceanology, Russian Academy of Sciences, 117997 Moscow, Russia
Interests: ocean optics; satellite ocean color; seawater fluorescence; absorption coefficient; dissolved organic matter; chlorophyll; arctic seas; surface layer
Special Issues, Collections and Topics in MDPI journals

Dr. Oleg Kopelevich

*
E-Mail Website
Guest Editor

Shirshov Institute of Oceanology, Russian Academy of Sciences, 117997 Moscow, Russia
Interests: seawater optical properties; satellite ocean color; field studies; regional algorithms; climatic factors
* Former Guest Editor. He deceased on 28 December 2020.
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This special issue aims at presenting the results of new studies on seawater bio-optical characteristics from satellite ocean color data. And not only: we strongly encourage the submission of the multisensory concurrent data from all available sources, including other remote sensing instruments (airborne and ship-based lidars) and contact measurements. The current contact methods and tools, such as autonomous profiling biogeochemical Argo buoys and underwater gliders, allow us to study the bio-optical characteristics' spatial and temporal changes in various scales. Under conditions of often cloudiness in the Arctic seas, the combined use of continuous measurement data on the ship's flow-through system and satellite observations proved very useful.

The authors can consider various aspects of the seawater bio-optical properties: spectral, angular, and polarization characteristics, relation to the absolute content and composition of the seawater optically active components, the inverse problems, the spatial and temporal variability of the characteristics, including both the inherent and apparent ones (such as the diffuse attenuation coefficient). The modeling and measured results are welcome; the presentation of new ideas and their realization, particularly applications for the investigation and monitoring of the ocean and seas, are encouraged. The particular topics of interest include, but are not limited to:

Topics:

Application of new methods and algorithms for retrieval of the seawater bio-optical characteristics from satellite ocean color data;
Results of processing, analysis and application of the data from the multisensor data sets;
Modeling of the seawater bio-optical characteristics and their components;
Inverse problem; seawater bio-optical characteristics
Bio-optical characteristics of the arctic water;

Variability of the seawater optical characteristics depending on the hydro-physical processes;
Essential Climatic Variables.

Original papers and thematic reviews are accepted.

Dr. Dmitry Glukhovets
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 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.

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Keywords

Seawater bio-optical characteristics
Satellite ocean color data
Multi-sensor data sets
New approaches, methods and algorithms
New data on variability including polar regions
Climatic variables

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Published Papers (11 papers)

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Editorial

Jump to: Research

3 pages, 182 KiB

Open AccessEditorial

An Overview of the Special Issue on Seawater Bio-Optical Characteristics from Satellite Ocean Color Data

by Dmitry Glukhovets

Remote Sens. 2023, 15(4), 1094; https://doi.org/10.3390/rs15041094 - 17 Feb 2023

Cited by 2 | Viewed by 1035

Abstract

Satellite ocean color data provide an opportunity to effectively observe possible changes in the state of marine ecosystems [...] Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

Research

Jump to: Editorial

24 pages, 6605 KiB

Open AccessArticle

Developing and Using Empirical Bio-Optical Algorithms in the Western Part of the Bering Sea in the Late Summer Season

by Pavel A. Salyuk, Igor E. Stepochkin, Ekaterina B. Sokolova, Svetlana P. Pugach, Vasiliy A. Kachur and Irina I. Pipko

Remote Sens. 2022, 14(22), 5797; https://doi.org/10.3390/rs14225797 - 16 Nov 2022

Cited by 4 | Viewed by 1716

Abstract

This study aimed to assess the applicability of global bio-optical algorithms for the estimation of chlorophyll-a (chl-a) concentration (C) and develop regional empirical bio-optical algorithms for estimating C and colored dissolved organic matter (CDOM) content (D) from ocean remote sensing reflectance spectra in the western part of the Bering Sea in the late summer period. The analysis took into account possible problems with the different relative contributions of phytoplankton and CDOM to water-leaving radiance and possible errors associated with the atmosphere correction procedure for ocean color satellite data. Shipborne remote sensing measurements obtained using an above-water hyperspectral ASD HandHeld spectroradiometer, satellite measurements collected via MODIS and VIIRS radiometers, and in situ measurements of C and D in seawater were used. The simulated values of the different multispectral satellite radiometers with daily or 2-day global coverage, obtained by applying the corresponding spectral response functions to ship hyperspectral data, were also analyzed. In this paper, a list of recommended regional bio-optical algorithms is presented. Recommendations are given depending on the possible quality of atmospheric correction and the purpose of use. To obtain more precise estimations of C, OC3/OC4-like algorithms should be used. If the atmosphere correction is poor, then use OC2-like algorithms in which spectral bands in the 476–539 nm range should be used to estimate C and bands near 443 nm to estimate D; however, in the last case, this will provide only the order of magnitude. To estimate more independent fields of C and D, it is necessary to use a spectral range of 501–539 nm for chl-a and bands near 412 nm in the case of modern satellite radiometers (e.g., OLCI or SGLI), for which this band is not the first. Additionally, we showed that global bio-optical algorithms can be applied with acceptable accuracy and similar recommendations. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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21 pages, 7112 KiB

Open AccessArticle

Influence of the Accuracy of Chlorophyll-Retrieval Algorithms on the Estimation of Solar Radiation Absorbed in the Barents Sea

by Dmitry Glukhovets, Sergey Sheberstov, Svetlana Vazyulya, Anna Yushmanova, Pavel Salyuk, Inna Sahling and Evgeniia Aglova

Remote Sens. 2022, 14(19), 4995; https://doi.org/10.3390/rs14194995 - 7 Oct 2022

Cited by 8 | Viewed by 1732

Abstract

The aim of this work is to study the influence of errors on the accuracy of estimation of absorbed solar energy in the visible spectral range in the water column of the Barents Sea occurring due to the use of various satellite ocean color chlorophyll-retrieval algorithms. The estimates of absorbed energy are based on data obtained during field experiments conducted in various parts of the Barents Sea in June-August 2021, as well as on modeling results. A new regional algorithm for evaluation of chlorophyll concentration in the Barents Sea (B22) is presented as a data source. This algorithm provides more accurate estimates compared to the standard MODIS algorithm under conditions of coccolithophore bloom. Comparing of the results of hydro-optical modeling to the data of shipboard hydro-optical measurements made it possible to validate the obtained data and confirmed the correctness of the selected models. Furthermore, we calculate the parameters of underwater light fields and the absorbed thermal energy in the visible spectral range in the seawater column, showing that differences in the chlorophyll concentration due to the accuracy of satellite bio-optical algorithms (30–50%) have little effect on the vertical distribution of solar energy absorbed in the seawater column. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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18 pages, 7333 KiB

Open AccessArticle

Assessment of the Diffuse Attenuation Coefficient of Photosynthetically Active Radiation in a Chilean Lake

by Lien Rodríguez-López, Lisdelys González-Rodríguez, Iongel Duran-Llacer, Wirmer García, Rolando Cardenas and Roberto Urrutia

Remote Sens. 2022, 14(18), 4568; https://doi.org/10.3390/rs14184568 - 13 Sep 2022

Cited by 11 | Viewed by 2801

Abstract

The diffuse attenuation coefficient of photosynthetically active radiation is an important inherent optical property of the subaquatic light field. This parameter, as a measure of the transparency of the medium, is a good indicator of water quality. Degradation of the optical properties of water due to anthropogenic disturbances is a common phenomenon in freshwater ecosystems. In this study, we used four algorithm-based Landsat 8 OLI and Sentinel-2A/B MSI images to estimate the diffuse attenuation coefficient of photosynthetically active radiation in Lake Villarrica located in south-central Chile. The algorithms’ estimated data from the ACOLITE module were validated with in situ measurements from six sampling stations. Seasonal and intralake variations of the light attenuation coefficient were studied. The relationship between the diffuse attenuation coefficient of photosynthetically active radiation, meteorological parameters, and an optical classification was also explored. The best results were obtained with QAA v6 KdPAR Nechad (R² = 0.931, MBE = 0.023 m⁻¹, RMSE = 0.088 m⁻¹, and MAPE = 35.9%) for spring and QAA v5 Kd490 algorithms (R² = 0.919, MBE = −0.064 m⁻¹, RMSE = −0.09 m⁻¹, and MAPE = 30.3%) for summer. High KdPAR values are associated with the strong wind and precipitation events suggest they are caused by sediment resuspension. Finally, an optical classification of freshwater ecosystems was proposed for this lake. The promising results of this study suggest that the combination of in situ data and observation satellites can be useful for assessing the bio-optical state of water and water quality dynamics in Chilean aquatic systems. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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22 pages, 5491 KiB

Open AccessArticle

Lateral Border of a Small River Plume: Salinity Structure, Instabilities and Mass Transport

by Alexander Osadchiev, Alexandra Gordey, Alexandra Barymova, Roman Sedakov, Vladimir Rogozhin, Roman Zhiba and Roman Dbar

Remote Sens. 2022, 14(15), 3818; https://doi.org/10.3390/rs14153818 - 8 Aug 2022

Cited by 6 | Viewed by 1957

Abstract

The interfaces between small river plumes and ambient seawater have extremely sharp horizontal and vertical salinity gradients, often accompanied by velocity shear. It results in formation of instabilities at the lateral borders of small plumes. In this study, we use high-resolution aerial remote sensing supported by in situ measurements to study these instabilities. We describe their spatial and temporal characteristics and then reconstruct their relation to density gradient and velocity shear. We report that Rayleigh–Taylor instabilities, with spatial scales ~5–50 m, are common features of the sharp plume-sea interfaces and their sizes are proportional to the Atwood number determined by the cross-shore density gradient. Kelvin–Helmholtz instabilities have a smaller size (~3–7 m) and are formed at the plume border in case of velocity shear >20–30 cm/s. Both instabilities induce mass transport across the plume-sea interfaces, which modifies salinity structure of the plume borders and induces lateral mixing of small river plumes. In addition, aerial observations revealed wind-driven Stokes transport across the sharp plume-sea interface, which occurs in the shallow (~2–3 cm) surface layer. This process limitedly affects salinity structure and mixing at the plume border, however, it could be an important issue for the spread of river-borne floating particles in the ocean. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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20 pages, 5527 KiB

Open AccessArticle

Satellite Observation of the Long-Term Dynamics of Particulate Organic Carbon in the East China Sea Based on a Hybrid Algorithm

by Sunbin Cai, Ming Wu and Chengfeng Le

Remote Sens. 2022, 14(13), 3220; https://doi.org/10.3390/rs14133220 - 4 Jul 2022

Cited by 3 | Viewed by 2274

Abstract

The distribution pattern and flux variation of POC in the continental shelf seas are essential for understanding the carbon cycle in marginal seas. The hydrodynamic environment and complicated estuarine processes in the East China Sea result in challenging estimates and substantial spatio-temporal variability in terms of POC concentrations. A hybrid retrieval model based on the mutual combination of the color index algorithm (CI_POC) and the empirical band ratio algorithm was applied in this study to effectively and dynamically monitor the surface POC concentration in the East China Sea in a long-term series for the first time using MODIS/Aqua remote sensing satellite data from 2003 to 2020. A hybrid retrieval model based on the mutual combination of the color index algorithm (CI_POC) and the empirical band ratio algorithm was applied in this study. The MODIS/Aqua remote sensing satellite data from 2003 to 2020 were employed for the first time to dynamically monitor the surface POC concentrations in the East China Sea for a long time series. The results demonstrated that the performance (R² = 0.84, RMSE = 156.14 mg/m³, MAPE = 43.30%, bias = −64.79 mg/m³) exhibited by this hybrid retrieval algorithm confirms the usability of inversion studies of surface POC in the East China Sea. Different drivers such as river discharge, phytoplankton, wind, and the sea surface current field jointly influence the spatial and temporal distribution of POC concentrations in the East China Sea. This paper also verifies that the hybrid algorithm can be applied to retrieval tasks for POC in different seas with similar optical properties to the waters of the East China Sea. In conclusion, the long-term series East China Sea POC data record, which was established based on MODIS/Aqua, provides supplementary information for in-situ sampling, which will aid the long-term monitoring of POC fluxes in shelf seas. At the same time, it has also improved our understanding of the transport and spatio-temporal variability of POC in the East China Sea, enhancing our comprehension of the impact of POC on environmental changes and carbon cycling in marginal seas. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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18 pages, 17513 KiB

Open AccessArticle

Fluorescence Line Height Extraction Algorithm for the Geostationary Ocean Color Imager

by Min Zhao, Yan Bai, Hao Li, Xianqiang He, Fang Gong and Teng Li

Remote Sens. 2022, 14(11), 2511; https://doi.org/10.3390/rs14112511 - 24 May 2022

Cited by 6 | Viewed by 2634

Abstract

Chlorophyll fluorescence is an important indicator of the physiological state of phytoplankton in water bodies. The new generation of ocean color satellite remote sensors usually sets fluorescence bands to detect the phytoplankton fluorescence line height (FLH). Yet, the Geostationary Ocean Color Imager (GOCI) offers no FLH products so far, and the FLH results calculated using the fluorescence band (680 nm) and the two baseline bands (660 and 745 nm) have numerous negative values and are quite different from the FLH products of other satellite ocean color sensors. To address this problem, we established an FLH retrieval algorithm suitable for GOCI. We simulated the spectral datasets of different water types using the radiative transfer model HydroLight and established the band conversion relationship from 680 to 685 nm based on the simulated datasets. The remote sensing reflectance after band conversion was applied to the FLH product inversion, significantly reducing the number of negative FLH values and appreciably improving data availability for GOCI FLH products (from 14.78% to 66.73% on average). The new FLH product has a good correlation with the field-measured data (R² = 0.73), and the relative error was 6.95%. Moreover, after band conversion, the FLH products retrieved by GOCI are in good agreement with the FLH products of MODIS, and fusion products can be further produced to improve the spatiotemporal resolution of the data. In addition, the radiative transfer simulation datasets also revealed that changes in solar zenith angle have little effect on FLH inversion. The hourly GOCI-derived FLH has good spatiotemporal continuity and can clearly reflect the diurnal variation of FLH. It can provide a stable FLH algorithm for further recovery of time-series GOCI FLH products and research on diurnal changes in FLH. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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21 pages, 6117 KiB

Open AccessArticle

Why Is It Important to Consider Dust Aerosol in the Sevastopol and Black Sea Region during Remote Sensing Tasks? A Case Study

by Darya V. Kalinskaya and Anna S. Papkova

Remote Sens. 2022, 14(8), 1890; https://doi.org/10.3390/rs14081890 - 14 Apr 2022

Cited by 10 | Viewed by 1774

Abstract

Atmospheric correction of satellite optical data is based on an assessment of the optical characteristics of the atmosphere, such as the aerosol optical thickness of the atmosphere and the spectral slope, the so-called Angstrom parameter. Inaccurate determination of these parameters is one of the causes of error in the retrieval of remote-sensed reflectance spectra. In this work, a large array of field and satellite data measured in Sevastopol and the northeastern part of the Black Sea were used, including ship-based measurements of atmospheric characteristics and sea reflectance, MODIS Aqua/Terra, and VIIRS NOAA/NPP Level 2 remote-sensed reflectance and atmospheric data. In total, three episodes of Saharan dust transfer over the Black Sea region were considered, mainly in the autumn-winter period. The purpose of this study was to show the numerical differences between the atmospheric parameters measured at the surface level and by satellites, and show their relationship with the differences between in situ and satellite remote-sensed reflectance. Based on the information identified, we propose an algorithm for additional correction of satellite level 2 data that uses a two-parametric model of the Black Sea remote-sensed reflectance as a first approximation. Moreover, additional correction significantly reduces the discrepancy between in situ and retrieved remote-sensed reflectance, especially in short-wave spectral bands. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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19 pages, 6802 KiB

Open AccessArticle

A Novel Approach to Obtain Diurnal Variation of Bio-Optical Properties in Moving Water Parcel Using Integrated Drifting Buoy and GOCI Data: A Case Study in Yellow and East China Seas

by Yuying Xu, Weibing Guan, Jianyu Chen, Zhenyi Cao and Feng Qiao

Remote Sens. 2021, 13(11), 2115; https://doi.org/10.3390/rs13112115 - 28 May 2021

Cited by 3 | Viewed by 2435

Abstract

Ocean processes that can influence rapidly changing ocean color include water-mass movement and bio-optical property changes in the water parcel. Traditionally, diurnal variability of bio-optical properties relies on daily time series at fixed locations by satellite sensors or in situ observations. There is a lack of an effective way to observe diurnal variation of bio-optical properties in a moving water parcel on a large scale. In this paper, we propose a new method to acquire diurnal variation of bio-optical properties in a moving water parcel. The novel approach integrates drifting buoy data and GOCI data. The movement of surface current was tracked by a drifting buoy, and its spatiotemporally matching bio-optical properties were obtained via the GOCI data. The results in the Yellow and East China seas during the summers of 2012 and 2013 show that the variation of time series following the movement of water parcel was obviously different from that obtained at fixed locations. The hourly differences of the former are 15.7% and 16.3% smaller than those of the latter for Chl a and total suspended sediment (TSS), respectively. The value of ag₄₄₀ was more stable within the moving water parcel than in the fixed location. Our approach provides a simple and feasible way for observing diurnal variability of bio-optical properties in a moving surface water parcel. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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22 pages, 6336 KiB

Open AccessArticle

Diurnal Variation of the Diffuse Attenuation Coefficient for Downwelling Irradiance at 490 nm in Coastal East China Sea

by Yu Zhang, Zhantang Xu, Yuezhong Yang, Guifen Wang, Wen Zhou, Wenxi Cao, Yang Li, Wendi Zheng, Lin Deng, Kai Zeng and Yinxue Zhang

Remote Sens. 2021, 13(9), 1676; https://doi.org/10.3390/rs13091676 - 26 Apr 2021

Cited by 6 | Viewed by 2258

Abstract

The diurnal variation of the diffuse attenuation coefficient for downwelling irradiance at 490 nm

(K_{d} (490))

has complex characteristics in the coastal regions. However, owing to the scarcity of in situ data, our knowledge on the diurnal variation [...] Read more.

The diurnal variation of the diffuse attenuation coefficient for downwelling irradiance at 490 nm

(K_{d} (490))

has complex characteristics in the coastal regions. However, owing to the scarcity of in situ data, our knowledge on the diurnal variation is inadequate. In this study, an optical-buoy dataset was used to investigate the diurnal variation of

K_{d} (490)

in the coastal East China Sea, and to evaluate the

K_{d} (490)

L2 products of geostationary ocean color imager (GOCI), as well as the performance of six empirical algorithms for

K_{d} (490)

estimation in the Case-2 water. The results of validation show that there was high uncertainty in GOCI L2

K_{d} (490)

, with mean absolute percentage errors (MAPEs) of 69.57% and 68.86% and root mean square errors (RMSEs) of 0.70 and 0.71 m⁻¹ compared to buoy-measured

K_{d 12} (490)

and

K_{d 13} (490)

, respectively. Meanwhile, with the coefficient of determination (R²) of 0.71, as well as the lowest MAPE of 27.31% and RMSE of 0.29 m⁻¹, the new dual ratio algorithm (NDRA) performed the best in estimating

K_{d} (490)

in the target area, among the six algorithms. Further, four main types of

K_{d} (490)

diurnal variation were found from buoy data, showing different variabilities compared to the area closer to the shore. One typical diurnal variation pattern showed that

K_{d} (490)

decreased at flood tide and increased at ebb tide, which was confirmed by GOCI images through the use of NDRA. Hydrometeorological factors influencing the diurnal variations of

K_{d} (490)

were also studied. In addition to verifying the predominant impact of tide, we found that the dominant effect of tide and wind on the water column is intensifying sediment resuspension, and the change of sediment transport produced by them are secondary to it. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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19 pages, 8956 KiB

Open AccessArticle

Variations of Water Transparency and Impact Factors in the Bohai and Yellow Seas from Satellite Observations

by Yan Zhou, Dingfeng Yu, Qian Yang, Shunqi Pan, Yingying Gai, Wentao Cheng, Xiaoyan Liu and Shilin Tang

Remote Sens. 2021, 13(3), 514; https://doi.org/10.3390/rs13030514 - 1 Feb 2021

Cited by 25 | Viewed by 5060

Abstract

Water transparency, measured with Secchi disk depth (SDD), is an important parameter for describing the optical properties of a water body. This study evaluates variations of SDD and related impact factors in the Bohai and Yellow Seas (BYS). Based on a new mechanistic model proposed by Lee et al. (2015) applied to MODIS remote sensing reflectance data, climatological SDD variation from 2003 to 2019 was estimated. The annual mean images showed an increasing trend from the coastal zone to the deep ocean. Lower values were found in the Bohai Sea (BHS), while higher values observed in the center of the southern Yellow Sea (SYS). Additionally, the entire sea has shown a decreasing temporal tend, with the variation rate lowest in the BHS at 0.003 m y⁻¹, and highest in the SYS at 0.015 m y⁻¹. However, the weak increasing trend that appeared since 2017 suggests that water quality seems to have improved. Further, it displayed seasonal patterns of low in winter and spring and high in summer and autumn. The empirical orthogonal function (EOF) analysis of SDD variations over the BYS, shows that the first SDD EOF mode is the highest, strongly correlated with total suspended matter. With the high correlation coefficients of chromophoric dissolved organic matter, it illustrates that the SDD variation is mainly dominated by the optical components in the seawater, although correlation with chlorophyll-a is the weakest. The second and third EOF modes show that photosynthetically available radiation, sea surface temperature, sea surface salinity, and wind speed are the main covariates that cause SDD changes. Water transparency evaluation on a long-term scale is essential for water quality monitoring and marine ecosystem protection. Full article

(This article belongs to the Special Issue Seawater Bio-Optical Characteristics from Satellite Ocean Color Data)

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