A system to measure the data quality of spectral remote-sensing reflectance of aquatic environments

Spectral remote-sensing reflectance (R-rs, sr(-1)) is the key for ocean color retrieval of water bio-optical properties. Since R-rs from in situ and satellite systems are subject to errors or artifacts, assessment of the quality of R-rs data is critical. From a large collection of high quality in situ hyperspectral R-rs data sets, we developed a novel quality assurance (QA) system that can be used to objectively evaluate the quality of an individual R-rs spectrum. This QA scheme consists of a unique R-rs spectral reference and a score metric. The reference system includes R-rs spectra of 23 optical water types ranging from purple blue to yellow waters, with an upper and a lower bound defined for each water type. The scoring system is to compare any target R-rs spectrum with the reference and a score between 0 and 1 will be assigned to the target spectrum, with 1 for perfect R-rs spectrum and 0 for unusable R-rs spectrum. The effectiveness of this QA system is evaluated with both synthetic and in situ R-rs spectra and it is found to be robust. Further testing is performed with the NOMAD data set as well as with satellite R-rs over coastal and oceanic waters, where questionable or likely erroneous R-rs spectra are shown to be well identifiable with this QA system. Our results suggest that applications of this QA system to in situ data sets can improve the development and validation of bio-optical algorithms and its application to ocean color satellite data can improve the short-term and long-term products by objectively excluding questionable R-rs data.