Challenges and New Advances in Ocean Color Remote Sensing of Coastal Waters

Loisel, Hubert; Vantrepotte, Vincent; Jamet, Cédric; NgocDat, Dinh

doi:10.5772/56414

Cited by 35 publications

(31 citation statements)

References 140 publications

(178 reference statements)

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“…For example, turbid marginal seas contain more inorganic mineral particulates than offshore oceanic waters, and these highly refractive particulates have a substantial influence on the optical properties of turbid marginal seas (Shen et al, ). Therefore, it is difficult to use one general proxy for satellite ocean color to estimate POC in optically complex waters (Le et al, ; Loisel et al, ). One possible approach to cope with this challenge is to classify water into different types based on optical properties (Feng et al, ; Huang et al, ; Le et al, ; Lubac & Loisel, ; Moore et al, ) and then develop specific optimal proxies for each water type; this approach helps to improve the performance of ocean color algorithms in estimating the POC in optically complex waters.…”

Section: Introductionmentioning

confidence: 99%

Satellite Observations of the Diurnal Dynamics of Particulate Organic Carbon in Optically Complex Coastal Oceans: The Continental Shelf Seas of China

et al. 2019

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The continental shelf seas of China (CSSC) broadly encompass the Bohai Sea, the Yellow Sea, and the East China Sea and exhibit highly variable optical properties. Accurate satellite estimates of particulate organic carbon (POC) remain challenging because optimal proxies for remotely sensed POC are largely obscure in these optically complex coastal waters. In this study, optical and biogeochemical data, including the particulate beam attenuation coefficient (cp), particulate backscattering coefficient (bbp), remote sensing reflectance (Rrs), POC, total suspended matter (TSM), and chlorophyll‐a (Chla), were collected over multiple seasons and years in the CSSC. We first classified the study area into three different water types with three different POC retrieval proxies: the TSM for high‐TSM waters, Chla for low‐TSM waters, and Rrs ratio (Rrs(490)/Rrs(555)) for moderate‐TSM waters. A composite POC algorithm using these three optimal proxies was then developed for Geostationary Ocean Color Imager (GOCI) satellite data (hereafter called the POC_CSSC algorithm). The validation results indicated that the accuracy of GOCI‐derived POC was greatly improved with a mean relative error of 32.08%. Application of the POC_CSSC algorithm to GOCI data over a tidally impacted estuary demonstrated the robustness of the algorithm and that tides play different roles in the broad CSSC. More specifically, tides have the strongest influence on nearshore estuarine waters, regulating the progression of high‐POC water masses from estuary to offshore environments, while offshore waters were the least influenced by tides with less variable, low POC concentrations.

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Section: Introductionmentioning

confidence: 99%

Satellite Observations of the Diurnal Dynamics of Particulate Organic Carbon in Optically Complex Coastal Oceans: The Continental Shelf Seas of China

et al. 2019

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“…High‐resolution (meter to hundred meters scale) ocean color remote sensing allows visualization of small‐scale features in estuaries and provides an excellent opportunity to quantify spatial and temporal variability of estuarine sediment dynamics over large scales (Jay et al, ). Remote sensing of ocean color has been used for coastal studies worldwide (Hu et al, ; Loisel et al, ; Vanhellemont & Ruddick, , ). In recent years, high spatial resolution satellite imagery (e.g., Landsat‐8 and Sentinel‐2) with high signal‐to‐noise ratio is available globally and free of charge.…”

Section: Introductionmentioning

confidence: 99%

Correlation of Remotely Sensed Surface Reflectance With Forcing Variables in Six Different Estuaries

Tao

Hill

2019

JGR Oceans

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This study examines the links between estuarine dynamics and longitudinal distributions of remotely sensed reflectance in estuaries. Reflectance at 655 nm from Landsat-8 correlates with in situ measurements of surface turbidity. Images collected from 2013 to 2018 are used to investigate the spatial and temporal characteristics of reflectance distribution in six selected estuaries with different dynamics. The results show that the maximum magnitude (C max ) and location (X max ) of the reflectance are functions of two major forcing variables, the freshwater discharge and tidal stage. Salt wedge estuaries (i.e., the Fraser River, Connecticut River, and Columbia River estuary) are affected strongly by river discharge and are relatively less affected by tidal forcing. In salt wedge estuaries, the C max values along the river channel are correlated with river discharge, while the X max values generally are not. In partially mixed to strain-induced periodic stratification (SIPS) estuaries (i.e., Delaware River) and SIPS-to-well-mixed estuaries (i.e., Gironde estuary), the X max values are correlated with river discharge, but the C max values are not. SIPS-to-well-mixed estuaries (i.e., Gironde estuary) and highly time-dependent salt wedge to well-mixed estuaries (i.e., Merrimack River estuary) are affected by tidal forcing. In these estuaries, the C max values are correlated with tidal stage. The C max values tend to be lower around high tide than low tide. Overall, the results demonstrate that remote sensing observations of ocean color can be utilized to infer subsurface estuarine processes. Satellite ocean color is a potential tool to monitor river discharge and to classify estuaries. Plain Language SummaryEstuaries are dynamic environments where river freshwater mixes with seawater. The relative strength of river flow relative to flow caused by ocean tides determines how and where freshwater and seawater mix in estuaries, which in turn affects various processes important to humans, like biological productivity and diversity, harbor siltation, and transport of pollutants. It is a challenge to classify estuaries on a global scale due to limited in situ observations. However, satellite remote sensing observations are able to provide repeated, snapshot views of surface water color over large spatial scale. In this study, we examine the links between estuarine dynamics and remote sensing observations in six different estuaries using satellite imagery. The observations demonstrate that satellite-derived maximum magnitude and position in surface reflectance, which is related to particle concentration, are correlated with river flow and tidal forcing, which can be used to infer different types of estuaries. Remotely sensed observations can also be useful for inferring the subsurface water mixing and sediment resuspension in estuaries. In addition, the responses of maximum in surface particle concentration and its location to river discharge can be used for satellite-based estimation of river discharge.

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“…Validation of ocean color products (i.e., biogeochemical parameters, inherent optical properties (IOPs) and water-leaving radiance), theoretically, should be performed from ground truth measurements acquired simultaneously to the satellite overpass over the same location (the so-called matchup points) [60]. In this study, the following criteria were used to find matchup points between satellite observations and ground truth measurements: (1) all available MERIS images over the Dutch part of Wadden Sea between 2002 and 2012 were checked to select the cloud-free images; (2) a narrow time window of ±1 h was used; (3) five-by-five pixel kernels centered on the ground truth measurement coordinates were then extracted from the MERIS images using BEAM software (version 5.0) (no aggregation method was used to avoid possible spectral contamination); (4) In addition, specific inherent optical properties (SIOPs) of water constituents in the Wadden Sea were obtained from Hommersom et al [11], who documented SIOP measurements in 2007 at 37 stations in this area.…”

Section: Ground Truth and Satellite Observation Data Matchupsmentioning

confidence: 99%

MOD2SEA: A Coupled Atmosphere-Hydro-Optical Model for the Retrieval of Chlorophyll-a from Remote Sensing Observations in Complex Turbid Waters

et al. 2016

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An accurate estimation of the chlorophyll-a (Chla) concentration is crucial for water quality monitoring and is highly desired by various government agencies and environmental groups. However, using satellite observations for Chla estimation remains problematic over coastal waters due to their optical complexity and the critical atmospheric correction. In this study, we coupled an atmospheric and a water optical model for the simultaneous atmospheric correction and retrieval of Chla in the complex waters of the Wadden Sea. This coupled model called MOD2SEA combines simulations from the MODerate resolution atmospheric TRANsmission model (MODTRAN) and the two-stream radiative transfer hydro-optical model 2SeaColor. The accuracy of the coupled MOD2SEA model was validated using a matchup data set of MERIS (MEdium Resolution Imaging SpectRometer) observations and four years of concurrent ground truth measurements (2007)(2008)(2009)(2010) at the NIOZ jetty location in the Dutch part of the Wadden Sea. The results showed that MERIS-derived Chla from MOD2SEA explained the variations of measured Chla with a determination coefficient of R 2 = 0.88 and a RMSE of 3.32 mg·m −3 , which means a significant improvement in comparison with the standard MERIS Case 2 regional (C2R) processor. The proposed coupled model might be used to generate a time series of reliable Chla maps, which is of profound importance for the assessment of causes and consequences of long-term phenological changes of Chla in the turbid Wadden Sea area.

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Challenges and New Advances in Ocean Color Remote Sensing of Coastal Waters

Cited by 35 publications

References 140 publications

Satellite Observations of the Diurnal Dynamics of Particulate Organic Carbon in Optically Complex Coastal Oceans: The Continental Shelf Seas of China

Satellite Observations of the Diurnal Dynamics of Particulate Organic Carbon in Optically Complex Coastal Oceans: The Continental Shelf Seas of China

Correlation of Remotely Sensed Surface Reflectance With Forcing Variables in Six Different Estuaries

MOD2SEA: A Coupled Atmosphere-Hydro-Optical Model for the Retrieval of Chlorophyll-a from Remote Sensing Observations in Complex Turbid Waters

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