4.7 Article

Global satellite water classification data products over oceanic, coastal, and inland waters

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 282, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2022.113233

Keywords

Water class; Optical water type; Remote sensing reflectance; Spectral similarity; VIIRS; Hyperspectral

Funding

  1. Joint Polar Satellite System (JPSS)
  2. NASA Carbon Monitoring System (CMS) project [80NSSC20K0014]
  3. Swedish National Space Agency Grant [2021-00050]
  4. Formas [2021-00050] Funding Source: Formas

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This study reports a new water class product for global waters from VIIRS, which divides the ocean, coastal, and inland waters into 23 water classes using a hyperspectral scheme. The results show that these water classes are distinguishable by their distinct bio-optical and biogeochemical properties, and the accuracy of the water class products is validated globally.
Satellites have generated extensive data of remote sensing reflectance spectra (Rrs(lambda)) covering diverse water classes or types across global waters. Spectral classification of satellite Rrs(lambda) data allows for the distinguishing and grouping of waters with characteristic bio-optical/biogeochemical features that may influence the produc-tivity of a given water body. This study reports new satellite water class products (Level-2 and Level-3) from the Visible Infrared Imaging Radiometer Suite (VIIRS). We developed and implemented a hyperspectral scheme that accounts for the Rrs(lambda) spectral shapes and globally resolves oceanic, coastal, and inland waters into 23 water classes. We characterized the light absorption and scattering coefficients, chlorophyll-a concentration, diffuse attenuation coefficient, and suspended particulate matter for individual water classes. It is shown that the water classes are separable by their distinct bio-optical and biogeochemical properties. Furthermore, validation result suggests that the VIIRS water class products are accurate globally. Finally, we examined the spatial and temporal variability of the water classes in case studies for a demonstration of applications. The water class data in open oceans reveal that the subtropical ocean gyres have experienced dramatic expansion over the last decade. In addition, the water class data appear to be a valuable (and qualitative) indicator for water quality in coastal and inland waters with compelling evidence. We stress that this new satellite product is an excellent addition to the aquatic science database, despite the need for continuous improvement toward perfection.

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