Evaluation of the VIIRS ocean color monitoring performance in coastal regions

Hlaing, S.; Harmel, Tristan; Gilerson, Alexander; Foster, Robert; Weidemann, Alan; Arnone, Robert; Wang, Menghua; Ahmed, Samir

doi:10.1016/j.rse.2013.08.013

Cited by 86 publications

(29 citation statements)

References 41 publications

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“…The intra-channel values of ψ in Figs. 4 and 5 indicate that VIIRS systematically underestimates L WN with respect to MODIS-A, as already reported in Hlaing et al (2013) for a different reprocessing. However, the RMSD values are comparable or even slightly smaller for VIIRS (which, assuming identical absolute uncertainties, is in agreement with smaller mean spectral values of L WN ).…”

Section: Results From L Wn Match-upssupporting

confidence: 79%

In situ autonomous optical radiometry measurements for satellite ocean color validation in the Western Black Sea

et al. 2015

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Abstract. The accuracy of primary satellite ocean color data products from the Moderate Resolution Imaging Spectroradiometer on-board Aqua (MODIS-A) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) is investigated in the Western Black Sea using in situ measurements from the Gloria site included in the ocean color component of the Aerosol Robotic Network (AERONET-OC). The analysis is also extended to an additional well-established AERONET-OC site in the northern Adriatic Sea characterized by optically complex coastal waters exhibiting similarities to those observed at the Gloria site. Results from the comparison of normalized water-leaving radiance L WN indicate biases of a few percent between satellite-derived and in situ data at the center wavelengths relevant for the determination of chlorophyll a concentrations (443-547 nm, or equivalent). Remarkable is the consistency between the annual cycle determined with time series of satellite-derived and in situ L WN ratios at these center wavelengths. Contrarily, the differences between in situ and satellite-derived L WN are pronounced at the blue (i.e., 412 nm) and red (i.e., 667 nm, or equivalent) center wavelengths, confirming difficulties in confidently applying satellite-derived radiometric data from these spectral regions for quantitative analysis in optically complex waters.

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Section: Results From L Wn Match-upssupporting

confidence: 79%

In situ autonomous optical radiometry measurements for satellite ocean color validation in the Western Black Sea

et al. 2015

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“…The performances of the GRS method applied to Sentinel-2 data are similar to those obtained for the main ocean color satellite missions (MERIS, MODIS, SeaWiFS, VIIRS); which have been assessed using the same reference data provided by the AERONET-OC network (e.g., Mélin et al, 2007;Goyens et al, 2013;Hlaing et al, 2013). Therefore, the GRS method could be considered as a robust one from the point of view of the validation step.…”

Section: Quantitative Validationmentioning

confidence: 52%

Sunglint correction of the Multi-Spectral Instrument (MSI)-SENTINEL-2 imagery over inland and sea waters from SWIR bands

Harmel

Chami

Tormos

et al. 2018

Remote Sensing of Environment

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correction of the Multi-Spectral Instrument (MSI)-SENTINEL-2 imagery over inland and sea waters from SWIR bands. Remote Sensing of Environment, Elsevier, 2018, 204, pp.308-321 A B S T R A C TRemote sensing of inland and sea waters depends on the quality of the retrieval of the water-leaving radiance from the top-of-atmosphere measurements. The water-leaving radiance can be difficult to observe due to the reflection of direct sunlight on the air-water interface (sunglint) in the direction of the satellite field of view. The viewing geometry of Sentinel-2 satellite (European Space Agency) makes it vulnerable to sunglint contamination. In this paper, an original method is proposed to correct Sentinel-2-like imagery for sunglint contamination. The sunglint contribution is first estimated from the shortwave-infrared (SWIR) part of the spectrum and then extrapolated toward the near-infrared and visible bands. The spectral variation of the sunglint signal is thus revisited for a wide spectral range (from 350 to 2500 nm). The bidirectional reflectance distribution function related to the sunglint is shown to vary by > 28% from the SWIR to the blue bands of Sentinel-2. The application of the proposed algorithm on actual Sentinel-2 data demonstrates that sunglint patterns are satisfactorily removed over the entire images whatever the altitude of the observed target. Comparison with in situ data of water-leaving radiances (AERONET-OC) showed that our proposed algorithm significantly improves the correlation between satellite and in situ data by 55% (i.e., from R 2 = 0.56 to R 2 = 0.87). In addition, the discrepancies between satellite and in situ measurements are reduced by 60%. It is also shown that the aerosol data provided by the Copernicus Atmosphere Monitoring Service (CAMS) can be safely used within the proposed algorithm to correct the Sentinel-2-like satellite data for both sunglint and atmospheric radiances. Improvements of the proposed method potentially rely on simultaneous retrievals of the aerosol optical properties. The proposed method is applicable to any satellite sensor which is able to measure in SWIR spectral bands over aquatic environments.

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“…The calibration and validation of products from ocean color sensors, especially in dynamic coastal areas, do not usually account for the diurnal changes in ocean color and assume a relatively temporally stable daily product (AE2 h) for calibration procedures. 16 Previous studies using geostationary satellite measurements have found that large changes in bio-optical parameters, such as water-leaving radiance, 17 light attenuation, 18,19 suspended particulate matter, and turbidity, 13,20,21 can occur on diel timescales and can be very significant; therefore, significant biases may be introduced as a result of having only one sample per day. 22 Although the temporal coverage of current geostationary orbiting missions, such as the geostationary ocean color imager (GOCI) vastly improves the sampling frequency of these parameters, the limit of geographic coverage constrains the extent of monitoring diurnal processes on global scales.…”

Section: Introductionmentioning

confidence: 99%

Diurnal changes in ocean color sensed in satellite imagery

Arnone

Vandermeulen

Soto

et al. 2017

J. Appl. Remote Sens

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Abstract. Measurements of diurnal changes in ocean color in turbid coastal regions in the Gulf of Mexico were characterized using above water spectral radiometry from a National Aeronautics and Space Administration (aerosol robotic network-WaveCIS CSI-06) site that can provide 8 to 10 observations per day. Satellite capability to detect diurnal changes in ocean color was characterized using hourly overlapping afternoon orbits of the visual infrared imaging radiometer suite (VIIRS) Suomi National Polar-orbiting Partnership ocean color sensor and validated with in situ observations. The monthly cycle of diurnal changes was investigated for different water masses using VIIRS overlaps. Results showed the capability of satellite observations to monitor hourly color changes in coastal regions that can be impacted by vertical movement of optical layers, in response to tides, resuspension, and river plume dispersion. The spatial variability of VIIRS diurnal changes showed the occurrence and displacement of phytoplankton blooming and decaying processes. The diurnal change in ocean color was above 20%, which represents a 30% change in chlorophyll-a. Seasonal changes in diurnal ocean color for different water masses suggest differences in summer and winter responses to surface processes. The diurnal changes observed using satellite ocean color can be used to define the following: surface processes associated with biological activity, vertical changes in optical depth, and advection of water masses. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Evaluation of the VIIRS ocean color monitoring performance in coastal regions

Cited by 86 publications

References 41 publications

In situ autonomous optical radiometry measurements for satellite ocean color validation in the Western Black Sea

In situ autonomous optical radiometry measurements for satellite ocean color validation in the Western Black Sea

Sunglint correction of the Multi-Spectral Instrument (MSI)-SENTINEL-2 imagery over inland and sea waters from SWIR bands

Diurnal changes in ocean color sensed in satellite imagery

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