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- Title
Global Estimation of Suspended Particulate Matter From Satellite Ocean Color Imagery.
- Authors
Jianwei Wei; Menghua Wang; Lide Jiang; Xiaolong Yu; Mikelsons, Karlis; Fang Shen
- Abstract
The suspended particulate matter (SPM) concentration (unit: mg l-1) in surface waters is an essential measure of water quality and clarity. Satellite remote sensing provides a powerful tool to derive the SPM with synoptic and repeat coverage. In this study, we developed a new global SPM algorithm utilizing the remote sensing reflectance (Rrs(λ)) at near-infrared (NIR), red, green, and blue bands (NIR-RGB) as input. The evaluations showed that the NIR-RGB algorithm could predict SPM with the median absolute percentage difference of ~35%-39% over a wide range from ~0.01 to >2,000 mg l-1. The uncertainty is smaller (29%-37%) for turbid waters where Rrs(671) ≥ 0.0012 sr-1 and slightly higher (41%-44%) for clear waters where Rrs(671) < 0.0012 mg l-1. The algorithm was implemented with the global Rrs(λ) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. We provided a brief characterization of the spatial distribution and temporal trends of the SPM products in global waters based on the monthly SPM composites. Case studies of the SPM time series in coastal and inland waters suggest that the satellite SPM estimations registered spatial and seasonal variation and episodic events in regional scales as well. The VIIRS-generated global SPM maps provide a valuable addition to the existing ocean color products for environmental and climate applications.
- Subjects
PARTICULATE matter; ARTIFICIAL satellites in oceanography; OCEANOGRAPHY; OCEAN color; OCEAN optics
- Publication
Journal of Geophysical Research. Oceans, 2021, Vol 126, Issue 8, p1
- ISSN
2169-9275
- Publication type
Article
- DOI
10.1029/2021JC017303