The loss of satellite data over water because of sun glint contamination represents a high cost financially and scientifically. Although many glint removal algorithms have been developed, glint contamination can remain problematic, especially in turbid waters. In the present study, we propose a correction for sun glint in turbid waters in the absence of SWIR bands. This method could for example be applied to imagery from the Pléiades and Planetscope constellations. Our method has been developed and tested using (1) in situ multi-angle measurements of surface reflectance collected with a PANTHYR autonomous hyperspectral radiometer deployed near Ostend, and (2) a set of metre-scale Pléiades stereo imagery taken in the Belgian coastal zone, with one image of the stereo pair looking into the sun glint and one looking away from the sun glint. The method uses combinations of spectral bands for which a linear relationship is observed in water reflectance, and a constant band ratio for glint reflectance directly calculated from the glinted image. To be adapted to a high range of turbidity conditions, a switching approach between band combinations is used. Glint removal correction was successfully applied in association with the ACOLITE Dark Spectrum Fitting (DSF) atmospheric correction. Results show a good performance in terms of glint removal, and the average overestimation is reduced to less than 20 % in visible bands.
The new generation of spaceborne hyperspectral sensors offers the potential to provide new information on water quality, especially regarding phytoplankton groups. While phytoplankton species composition algorithms are easily demonstrated in model studies, the application of algorithms to spaceborne data may be much more challenging because of processing artefacts in the spectral vicinity of atmospheric absorption features. If not treated carefully, the unresolved spectral variability of radiance and irradiance can create spectral artefacts (“wiggles”) in water reflectance spectra with high second derivative and thus contaminates pigment detection algorithms. In this study one of the processes generating such spectral wiggles is explained for an in situ radiometer system with a wavelength offset between the radiance and irradiance measurements. The two measurements used to calculate reflectance are differently affected by narrow, unresolved atmospheric absorption bands. Removal or reduction of such wiggles could be achieved by physically-based weighting in the spectral interpolation of irradiance rather than the typical spectral averaging generally used to hide such problems when using linear interpolation. Although demonstrated here for in situ radiometry the need for careful treatment of unresolved spectral variability in spaceborne data is raised, particularly if such data is used for second derivative algorithms which are very sensitive to short wavelength scale variability.
During the past decade, the world's oceans have been systematically observed by orbiting spectroradiometers such as
MODIS and MERIS. These sensors have generated a huge amount of data with unprecedented temporal and spatial
coverage. The data is freely available, but not always accessible for marine researchers with no image processing
experience. In order to provide historical and current oceanographic parameters for the jellyfish forecasting in the
JELLYFOR project, a tool for the generalized processing and archiving of satellite data was created (GRIMAS). Using
this generalized software, the large amount of remote sensing data can be accessed, and parameters such as chlorophyll a
concentration (CHL), sea surface temperature (SST) and total suspended matter concentration (TSM) can be extracted
and gridded for any region on earth. Time-series and climatologies can be easily extracted from this data archive. The
products generated can be based on the standard products, as supplied by space agencies, or can be new or regionally
calibrated products. All available MODIS and MERIS L2 images from an eight year period (2003-2010) were processed
in order to create a gridded dataset of CHL, SST (MODIS only) and of TSM for the three JELLYFOR regions. For two
of the regions, data for an extended region was also processed. Multi-year composites (climatologies) of satellite data
and time-series can provide a wealth of information for different projects in any region. Climatologies from the two
sensors are in good agreement, while significant differences can occur on a scene per scene basis. Total suspended matter
concentrations match favourably with in situ data derived from sensors on autonomous buoys. MODIS sea surface
temperature corresponds closely to temperature continuously measured underway on research vessels.
A multi-sensor algorithm is applied to MODIS and MERIS satellite data in order to quantify
suspended particulate matter (SPM) in the Yangtze River plume (East China Sea). Several
atmospheric correction methods are tested; a simple but operational method is finally selected
as appropriate for MODIS, MERIS and GOCI satellite data. As most of the methods for
atmospheric corrections of satellite data fail over such highly turbid waters, an adaptation of
the black pixel assumption is used to correct for the aerosol contribution. The retrieved
seawater reflectance at red wavebands appears as the most sensitive to SPM concentrations
but tends to saturate at concentrations beyond 100 mg.l-1. By opposition the near-infrared
seawater reflectance does not saturate even at extremely high concentrations of 1000 mg.l-1.
Overall, the most robust relationship between the SPM concentration and seawater reflectance
is obtained considering a spectral ratio between the near-infrared (e.g., 850 nm) and visible
(e.g. 550 nm). This relationship is applied to atmospherically corrected ocean color satellite
data to retrieve SPM concentrations in the Yangtze River plume.
Results show that ocean color satellite data can be used to study the seasonal dynamics of
SPM and better understand the role played by the main physical processes involved (river
discharge, tidal cycles, wind and regional circulation).
K. Ruddick, C. Brockmann, R. Doerffer, Z. Lee, V. Brotas, N. Fomferra, S. Groom, H. Krasemann, V. Martinez-Vicente, C. Sa, R. Santer, S. Sathyendranath, K. Stelzer, S. Pinnock
The MERIS instrument delivers a unique dataset of ocean colour measurements of the coastal zone, at 300m resolution
and with a unique spectral band set. The motivation for the Coastcolour project is to fully exploit the potential of the
MERIS instrument for remote sensing of the coastal zone. The general objective of the project is to develop,
demonstrate, validate and intercompare different processing algorithms for MERIS over a global range of coastal water
types in order to identify best practices. In this paper the Coastcolour project is presented in general and the Regional
Algorithm Round Robin (RARR) exercise is described in detail. The RARR has the objective of determining the best
approach to retrieval of chlorophyll a and other marine products (e.g. Inherent Optical Properties) for each of the
Coastcolour coastal water test sites. Benchmark datasets of reflectances at MERIS bands will be distributed to algorithm
provider participants for testing of both global (Coastcolour and other) algorithms and site-specific local algorithms.
Results from all algorithms will be analysed and compared according to a uniform methodology. Participation of
algorithm providers from outside the Coastcolour consortium is encouraged.
Estimation of the underwater attenuation of light is important to ecosystem modellers, who require information on
Photosynthetically Available Radiation (PAR), and on the euphotic depth for calculation of primary production.
Characterisation of these processes can be achieved by determining the diffuse attenuation coefficient of PAR, KPAR . A
review of bio-optical models of the spectral diffuse attenuation coefficient for downwelling irradiance, Kd , is presented
and stresses the necessity for a better knowledge and parameterization of these coefficients.
In the second part of this work, radiative transfer simulations were carried out to model KdZ1% the spectral diffuse
attenuation of downwelling irradiance averaged over the euphotic depth Z1% (depth where the downwelling irradiance is
1% of its surface value). This model takes into account the effects of varying sun zenith angle and cloud cover and needs
absorption and backscattering coefficients (the inherent optical properties, IOPs) as input. It provides average and
maximum relative errors of 1% and 5% respectively, for sun zenith angles [0°-50°] and of 1.7% and 12% respectively at
higher sun zenith angles. A relationship was established between KdZ1% at a single wavelength (590nm) and KPAR at
ZPAR1% (where PAR is 1% of its value at the surface) which allows for a direct expression of KPARZPAR1% in terms of
inherent optical properties, sun angle and cloudiness. This model provides estimates of KPAR within 25% (respectively
40%) relative errors respectively with a mean relative error less than 7% (respectively 9%) for sun zenith angles ranging
from 0° to 50° (respectively higher than 50°). A similar method is applied to derive a model for the diffuse attenuation of
photosynthetically usable radiation, KPURZPUR1% , with similar performance.
Turbidity, as defined in the standard ISO7027, is a parameter that is routinely measured in many national and regional
water quality monitoring programmes. The definition of turbidity according to ISO and as related to satellite data
products is discussed. While satellite data products are beginning to become available for the closely related parameter,
Total Suspended Matter (TSM), the direct estimation of turbidity as a satellite data product has not yet been addressed.
In situ measurements of TSM and of turbidity, obtained in the Southern North Sea (SNS), show high correlation
(correlation coefficient of 98.6%). A generic multisensor algorithm for TSM as function of reflectance has been
previously developed. The methodology is extended here to the estimation of turbidity from water-leaving reflectance. A
set of 49 seaborne measurements of reflectance in the spectral range 600-850nm and turbidity in the SNS are used to
calibrate the algorithm. The algorithm is also calibrated for the specific bands of MERIS. Validation of these models is
carried out using an independent set of seaborne measurements of turbidity and reflectance and shows low relative errors
in turbidity retrieval at 681nm (less than 35%). This wavelength is recommended, provided no significant fluorescence
affects this range.
The shape of water-leaving reflectance spectra in the near infrared range 700-900nm is almost invariant for turbid waters and has been analysed and tabulated as a similarity spectrum by normalisation at 780nm. This similarity spectrum is used here for the quality control of seaborne reflectance measurements and for the improvement of sky glint correction. Estimates of the reflectance measurement error associated with imperfect sky glint correction from two different wavelength pairs are shown to be nearly identical. A demonstration of residual reflectance correction for data collected in cloudy, high wave conditions has shown that this correction removes a large source of variability associated with temporal variation of the wave field. The error estimate applied here to seaborne measurements has wide-ranging generality and is appropriate for any water-leaving reflectance spectra derived from seaborne, airborne or satellite borne sensors provided suitable near infrared bands are available.
The Southern Bight of the North Sea is characterised by a large influence of river inputs, which results in eutrophication of the area. High concentrations of plankton biomass and suspended matter have been reported for this area, in relation with blooms of different species and resuspension of bottom sediments. In spring the haptophyte Phaeocystis globosa blooms throughout the area reaching up to 30 mg Chlorophyll m-3 or more nearshore. This event is followed in June by red tides of the dinoflagellate Noctiluca scintillans. These blooms are concurrent with different species of diatoms. The strong optical signature of these blooms is clear to human observers making them potentially detectable in satellite imagery. As a first step in this direction, sampling has been carried out in the area, during Phaeocystis and Noctiluca blooms in 2003 and 2004. Phytoplankton pigments and inherent optical properties (particle, detrital and phytoplankton absorption) have been measured spectrophotometrically, and in situ using an ac-9 for total absorption and particle scattering. Field data were compared with optical properties of pure species obtained in laboratory. In parallel, water-leaving reflectance has been also measured. In this paper we characterise the optical signatures of diatoms, Phaeocystis and Noctiluca and their contribution to total absorption. The impact on water-leaving reflectance spectra is evaluated; in order to assess the conditions in which remote sensing can provide information for monitoring the timing, extent and magnitude of blooms in this coastal area.
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