Marine Science Faculty Publications

On the Interplay Between Ocean Color Data Quality and Data Quantity: Impacts of Quality Control Flags

Document Type

Article

Publication Date

5-2020

Keywords

Oceans, Image color analysis, Data integrity, Quality control, Sun, Sea measurements, NASA

Digital Object Identifier (DOI)

https://doi.org/10.1109/LGRS.2019.2936220

Abstract

Nearly all calibration/validation activities for the satellite ocean color missions have focused on data quality to produce data products of the highest quality (i.e., science quality) for climate-related research. Little attention, however, has been paid to data quantity, particularly on how data quality control during data processing impacts downstream data quality and data quantity. In this letter, we attempt to fill this knowledge gap using measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). For this sensor, the same level-1B data are processed independently using different quality control methods by NASA and NOAA, respectively, allowing for an in-depth evaluation of the interplay between data quantity and quality. The results indicate that the methods to identify stray light and sun glint are the two primary quality control procedures affecting data quantity, where the criteria for flagging pixels “contaminated” by stray light and sun glint may be relaxed in the NASA ocean color data processing to increase data quantity without compromising data quality.

Was this content written or created while at USF?

Yes

Citation / Publisher Attribution

IEEE Geoscience and Remote Sensing Letters, v. 17, issue 5, p. 745-749

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