David Doxaran

Role of measurement uncertainties in observed variability in the spectral backscattering ratio: a case study in mineral-rich coastal waters

The particulate backscattering ratio (b(bp)/b(p)) is a useful indicator of the angular scattering characteristics of natural waters. Recent studies have shown evidence both for and against significant spectral variability in b(bp)/b(p) in the visible domain, but most show significant variability in its magnitude. We present results from a case study in which both backscattering and scattering coefficients were measured at nine wavelengths in a region of UK coastal waters where optical scattering is strongly influenced by inorganic particles and where a wide range of turbidities is found in a small geographic area. Using a new approach based on regression analysis of in situ signals, it is shown that, for this study site, most of the apparent variability in the magnitude of the backscattering ratio can be attributed to measurement uncertainties. Regression analysis suggests that b(bp)/b(p) is wavelength dependent for these mineral-rich waters. This conclusion can only be avoided by positing the existence of undocumented, systematic, wavelength-dependent errors in backscattering measurements made by two independently calibrated sensors. These results are important for radiative transfer simulations in mineral-dominated waters where the backscattering ratio has often been assumed to be spectrally flat. Furthermore, spectral dependence also has profound implications for our understanding of the relationship between b(bp)/b(p) and particle size distributions in coastal waters since the commonly assumed power-law distribution is associated with a spectrally flat particulate backscattering ratio for nonabsorbing particles.

Uncertainties associated to measurements of inherent optical properties in natural waters

Monte Carlo simulations are used to explain and quantify the errors in inherent optical properties (IOPs) (absorption and attenuation coefficients) measured using the WET Labs AC-9 submarine spectrophotometer, and to assess correction algorithms. Simulated samples with a wide range of IOPs encountered in natural waters are examined. The relative errors on the measured absorption coefficient are in general lower than 25%, but reach up to 100% in highly scattering waters. Relative errors on attenuation and scattering coefficients are more stable, with an underestimation mainly driven by the volume scattering function. The errors in attenuation and scattering spectral shapes are small.

Near-infrared light scattering by particles in coastal waters

We report the first measurements of the scattering coefficient of natural marine particles, which extend over the near-infrared spectral region to up to 870 nm. The measurements were conducted in three different European estuaries (Gironde, Tamar and Elbe) using an in situ absorption and attenuation-meter. The observed particulate scattering coefficients varied from 1 to nearly 100 m(-1). The spectral shape in the near-infrared very closely matched a lambda(-gamma) spectral dependence, which is expected when the particle size followed a power-law distribution. The spectral slope of the scattering spectrum, gamma, spanned from 0.1 to 1.2 and showed significant regional and temporal variations. These variations were certainly related to the particle size distribution, which will have to be studied in future works. Using our near-infrared data as a reference, we assessed the use of the attenuation coefficient spectrum in the visible range to estimate the near-infrared particulate scattering slope and found values different by 10% on average.

Potential of High Spatial and Temporal Ocean Color Satellite Data to Study the Dynamics of Suspended Particles in a Micro-Tidal River Plume

Ocean color satellite sensors are powerful tools to study and monitor the dynamics of suspended particulate matter (SPM) discharged by rivers in coastal waters. In this study, we test the capabilities of Landsat-8/Operational Land Imager (OLI), AQUA&TERRA/Moderate Resolution Imaging Spectroradiometer (MODIS) and MSG-3/Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensors in terms of spectral, spatial and temporal resolutions to (i) estimate the seawater reflectance signal and then SPM concentrations and (ii) monitor the dynamics of SPM in the Rhone River plume characterized by moderately turbid surface waters in a micro-tidal sea. Consistent remote-sensing reflectance (Rrs) values are retrieved in the red spectral bands of these four satellite sensors (median relative difference less than ~16% in turbid waters). By applying a regional algorithm developed from in situ data, these Rrs are used to estimate SPM concentrations in the Rhone river plume. The spatial resolution of OLI provides a detailed mapping of the SPM concentration from the downstream part of the river itself to the plume offshore limits with well defined small-scale turbidity features. Despite the low temporal resolution of OLI, this should allow to better understand the transport of terrestrial particles from rivers to the coastal ocean. These details are partly lost using MODIS coarser resolutions data but SPM concentration estimations are consistent, with an accuracy of about 1 to 3 g·m−3 in the river mouth and plume for spatial resolutions from 250 m to 1 km. The MODIS temporal resolution (2 images per day) allows to capture the daily to monthly dynamics of the river plume. However, despite its micro-tidal environment, the Rhone River plume shows significant short-term (hourly) variations, mainly controlled by wind and regional circulation, that MODIS temporal resolution failed to capture. On the contrary, the high temporal resolution of SEVIRI makes it a powerful tool to study this hourly river plume dynamics. However, its coarse resolution prevents the monitoring of SPM concentration variations in the river mouth where SPM concentration variability can reach 20 g·m−3 inside the SEVIRI pixel. Its spatial resolution is nevertheless sufficient to reproduce the plume shape and retrieve SPM concentrations in a valid range, taking into account an underestimation of about 15%–20% based on comparisons with other sensors and in situ data. Finally, the capabilities, advantages and limits of these satellite sensors are discussed in the light of the spatial and temporal resolution improvements provided by the new and future generation of ocean color sensors onboard the Sentinel-2, Sentinel-3 and Meteosat Third Generation (MTG) satellite platforms.

Atmospheric Corrections and Multi-Conditional Algorithm for Multi-Sensor Remote Sensing of Suspended Particulate Matter in Low-to-High Turbidity Levels Coastal Waters

The accurate measurement of suspended particulate matter (SPM) concentrations in coastal waters is of crucial importance for ecosystem studies, sediment transport monitoring, and assessment of anthropogenic impacts in the coastal ocean. Ocean color remote sensing is an efficient tool to monitor SPM spatio-temporal variability in coastal waters. However, near-shore satellite images are complex to correct for atmospheric effects due to the proximity of land and to the high level of reflectance caused by high SPM concentrations in the visible and near-infrared spectral regions. The water reflectance signal (ρw) tends to saturate at short visible wavelengths when the SPM concentration increases. Using a comprehensive dataset of high-resolution satellite imagery and in situ SPM and water reflectance data, this study presents (i) an assessment of existing atmospheric correction (AC) algorithms developed for turbid coastal waters; and (ii) a switching method that automatically selects the most sensitive SPM vs. ρw relationship, to avoid saturation effects when computing the SPM concentration. The approach is applied to satellite data acquired by three medium-high spatial resolution sensors (Landsat-8/Operational Land Imager, National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite and Aqua/Moderate Resolution Imaging Spectrometer) to map the SPM concentration in some of the most turbid areas of the European coastal ocean, namely the Gironde and Loire estuaries as well as Bourgneuf Bay on the French Atlantic coast. For all three sensors, AC methods based on the use of short-wave infrared (SWIR) spectral bands were tested, and the consistency of the retrieved water reflectance was examined along transects from low- to high-turbidity waters. For OLI data, we also compared a SWIR-based AC (ACOLITE) with a method based on multi-temporal analyses of atmospheric constituents (MACCS). For the selected scenes, the ACOLITE-MACCS difference was lower than 7%. Despite some inaccuracies in ρw retrieval, we demonstrate that the SPM concentration can be reliably estimated using OLI, MODIS and VIIRS, regardless of their differences in spatial and spectral resolutions. Match-ups between the OLI-derived SPM concentration and autonomous field measurements from the Loire and Gironde estuaries’ monitoring networks provided satisfactory results. The multi-sensor approach together with the multi-conditional algorithm presented here can be applied to the latest generation of ocean color sensors (namely Sentinel2/MSI and Sentinel3/OLCI) to study SPM dynamics in the coastal ocean at higher spatial and temporal resolutions.

Remote sensing of suspended particulate matter in turbid oyster‐farming ecosystems

High resolution satellite data of the Medium Resolution Imaging Spectrometer in full resolution mode (MERIS FR, pixel size is 300 m) were used to study the impact of suspended particulate matter (SPM) on oyster-farming sites in a macrotidal bay of the French Atlantic coast where SPM concentration can exceed 100 g m−3. Because MERIS standard SPM concentration retrieval saturates at about 50 g m−3, we developed an alternative method for turbid nearshore waters. The method consists in the combination of the Semi-Analytical Atmospheric and Bio-Optical (SAABIO) atmospheric correction with a regional bio-optical algorithm based on a linear relationship between SPM concentration and the reflectance band ratio at 865 and 560 nm. MERIS FR-derived SPM concentrations were validated from 10 up to 300 g m−3, and then merged with oyster ecophysiological responses to provide a spatial picture of the impact of SPM concentration on oyster-farming sites. Our approach demonstrates the potential of high resolution satellite remote sensing for aquaculture management and shellfish-farming ecosystems studies.

Assessment of GOCI radiometric products using MERIS, MODIS and field measurements

The first Geostationary Ocean Color Imager (GOCI) launched by South Korea in June 2010 constitutes a major breakthrough in marine optics remote-sensing for its capabilities to observe the diurnal cycles of the ocean. The light signal recorded at eight wavelengths by the sensor allows, after correction for Solar illumination and atmospheric effects, the retrieval of coloured biogeochemical products such as the chlorophyll, suspended sediment and coloured dissolved organic matter concentrations every hour between 9:00 am and 4:00 pm local time around the Korean peninsula. However operational exploitation of the mission needs beforehand a sound validation of first the radiometric calibration, i.e. inspection of the top-of-atmosphere reflectance, and second atmospheric corrections for retrieval of the water-leaving reflectance at sea surface. This study constitutes a contribution to the quality assessment of the GOCI radiometric products generated by the Korea Ocean Satellite Center (KOSC) through comparison with concurrent data from the MODerate-resolution Imaging Spectroradiometer (MODIS, NASA) and MEdium Resolution Imaging Spectrometer (MERIS, ESA) sensors as well as in situ measurements. These comparisons are made with spatially and temporally collocated data. We focus on Rayleigh-corrected reflectance (ρRC) and normalized remote-sensing marine reflectance (nRrs). Although GOCI compares reasonably well with MERIS and MODIS, what demonstrates the success of Ocean Colour in geostationary orbit, we show that the current GOCI atmospheric correction systematically masks out data over very turbid waters and needs further examination and correction for future release of the GOCI products.

Improved correction methods for field measurements of particulate light backscattering in turbid waters

Monte Carlo simulations are used to compute the uncertainty associated to light backscattering measurements in turbid waters using the ECO-BB (WET Labs) and Hydroscat (HOBI Labs) scattering sensors. ECO-BB measurements provide an accurate estimate of the particulate volume scattering coefficient after correction for absorption along the short instrument pathlength. For Hydroscat measurements, because of a longer photon pathlength, both absorption and scattering effects must be corrected for. As the standard (sigma) correction potentially leads to large errors, an improved correction method is developed then validated using field inherent and apparent optical measurements carried out in turbid estuarine waters. Conclusions are also drawn to guide development of future short pathlength backscattering sensors for turbid waters.

Shellfish Aquaculture from Space: Potential of Sentinel2 to Monitor Tide-Driven Changes in Turbidity, Chlorophyll Concentration and Oyster Physiological Response at the Scale of an Oyster Farm

The algorithms of Novoa et al. (2017) and Gons et al. (2005) were recalibrated and applied to Sentinel2 data to respectively retrieve suspended particulate matter (SPM) and chlorophyll a (chl a) concentration in the environmentally and economically important intertidal zones. Sentinel2-derived chl a and SPM concentration distributions were analyzed at the scale of an oyster farm over a variety of tidal conditions. Sentinel2 imagery was then coupled with ecophysiological modeling to analyze the influence of tide-driven chl a and SPM dynamics on oyster clearance and chl consumption rates. Within the studied oyster farming site (Bourgneuf Bay along the French Atlantic coast), chl consumption rate mirrored the changes in chl a concentration during neap tides, whereas oyster clearance and chl consumption rates were both negatively impacted by high SPM concentration during spring tides.

On the Potential of Robust Satellite Techniques Approach for SPM Monitoring in Coastal Waters: Implementation and Application over the Basilicata Ionian Coastal Waters Using MODIS‐Aqua

Monitoring river plume dynamics and variations in complex coastal areas can provide useful information to prevent marine environmental damage. In this work, the Robust Satellite Techniques (RST) approach has been implemented and tested on historical series of Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data to monitor, for the first time, Suspended Particulate Matter (SPM) anomalies associated to river plumes. To this aim, MODIS-Aqua Level 1A data were processed using an atmospheric correction adequate for coastal waters, and SPM daily maps were generated applying an algorithm adapted from literature. The RST approach was then applied to these maps to assess the anomalous presence of SPM. The study area involves the Basilicata region coastal waters (Ionian Sea, South of Italy). A long-time analysis (2003–2015) conducted for the month of December allows us to find that the maximum SPM concentration value was registered in December 2013, when an extreme hydrological event occurred. A short-time analysis was then carried out applying RST to monitor the dynamics of anomalous SPM concentrations. Finally, the most exposed areas, in terms of SPM concentration, were identified. The results obtained in this work showed the RST high potential when used in combination with standard SPM daily maps to better characterize and monitor coastal waters.