Remote sensing of turbid coastal and estuarine waters with VIIRS I (375 m) and M (750 m) bands
Creators: name: Vanhellemont, Quinten
name: Dogliotti, Ana
name: Doxaran, David
name: Goyens, Clémence
name: Ruddick, Kevin
name: Vansteenwegen, Dieter
Publisher: name: Taylor & Francis
Year: 2024
Subjects: Space Science
Medicine
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified

description: The Visible Infrared Imaging Radiometer Suite (VIIRS) is a visible, near and shortwave, to thermal infrared multispectral scanning instrument operational on three polar orbiting satellites, Suomi-NPP, JPSS-1, and JPSS-2. In the present paper, the processing of VIIRS using ACOLITE is introduced, using the Dark Spectrum Fitting (DSF) algorithm for processing of the visible to shortwave infrared bands. ACOLITE now includes support for processing both the imaging (I) and moderate (M) resolution bands at 375 m and 750 m spatial resolution, respectively. In most conditions encountered in the present study, the SWIR bands (either I or M) are automatically selected by the DSF for performing the aerosol correction. The processing is evaluated for turbid water remote sensing via autonomous hyperspectral radiometry from four sites across coastal and estuarine waters: two sites in Belgium and one each in France and Argentina. Through analysis of hundreds of matchups between the satellite and in situ measurements, a generally good performance is found for both I and M bands, especially for bands with the largest water signal, i.e. bands between 490 and 670 nm, where on average relative differences of 10–15% were found. Reflectance biases are generally less than 0.01, with a negative sign in the green and red bands and a positive sign in the blue and NIR bands. Similar matchup results are found for the I and M red and NIR bands, with a slightly higher scatter for the NIR bands. An additional comparison with OCSSW/l2gen processing of the M band data is performed for various configurations. Overall, DSF performance is better in the visible bands, whereas l2gen outputs are more closely aligned with the in situ measurements in the NIR. On average, negative biases are found for all l2gen configurations, up to −0.02 in the blue bands. Using either the SWIR1 + 2 or SWIR1 + 3 bands for the aerosol correction gives the best performance for l2gen processing. For the three VIIRS instruments separately, the average spectral differences with in situ measurements are comparable, with the most important deviation occurring at the Suomi-NPP shortest blue bands, where DSF processing gives a larger positive bias, up to nearly 0.02. For these bands, results from l2gen correspond more closely across the three instruments – although with significant negative biases for all three sensors up to −0.02 – presumably due to the use of system vicarious calibration gains in that processor. An operational network of autonomous hyperspectral instruments provides validation data for any overpassing optical imaging satellite in its commissioning or operational phase and eliminates the need for spectral interpolation or band shifting. In the case of VIIRS specifically, the hyperspectral instruments provide adequate data for the validation of the 20, 40 and 80 nm wide bands. With three operational wide-swath instruments, which provide largely interoperable data, a high frequency of observations is available, especially for study areas at higher latitudes. The novel exploitation of the I bands is now possible, thanks to the free and open source availability of ACOLITE. The advantage of the higher resolution I band data, combined with multiple VIIRS overpasses per day, is demonstrated for mapping turbidity in nearshore regions with high spatial variabilty and for detecting under-resolved floating algae. The open-source ACOLITE processor was adapted for VIIRS I (375 m) and M (750 m) dataThree operational VIIRS (Suomi-NPP, JPSS-1 and JPSS-2) were processed and validatedIn situ autonomous hyperspectral radiometry was used for   performance evaluationACOLITE I and M band outputs compared well across hundreds of turbid water matchupsTurbidity and FAI product resolution were improved with ACOLITE I bandprocessing The open-source ACOLITE processor was adapted for VIIRS I (375 m) and M (750 m) data Three operational VIIRS (Suomi-NPP, JPSS-1 and JPSS-2) were processed and validated In situ autonomous hyperspectral radiometry was used for   performance evaluation ACOLITE I and M band outputs compared well across hundreds of turbid water matchups Turbidity and FAI product resolution were improved with ACOLITE I bandprocessing