Evaluation of GOCI Remote Sensing Reflectance Spectral Quality Based on a Quality Assurance Score System in the Bohai Sea

Xiaoyan Liu,Yunhua Wang,Yu Zhang,Qian Yang

doi:10.3390/rs14051075

Abstract

In the application of ocean color remote sensing, remote sensing reflectance spectral (Rrs(λ)) is the most important and basic parameter for the development of bio-optical algorithms. Atmospheric correction of ocean color data is a key factor in obtaining accurate water Rrs(λ) data. Based on the QA (quality assurance) score spectral quality evaluation system, the quality of Rrs(λ) spectral of GOCI (Geostationary Ocean Color Imager) obtained from four atmospheric-correction algorithms in the Bohai Sea were evaluated and analyzed in this paper. The four atmospheric-correction algorithms are the NASA (National Aeronautics and Space Administration) standard near-infrared atmospheric-correction algorithm (denoted as Seadas—Default), MUMM (Management Unit of the North Sea Mathematical Models, denoted as Seadas—MUMM), and the standard atmospheric-correction algorithms of KOSC GOCI GDPS2.0 (denoted as GDPS2.0) and GDPS1.3 (denoted as GDPS1.3). It is shown that over 90% of the Rrs(λ) data are in good quality with a score ≥4/6 for the GDPS1.3 algorithm. The probability of Rrs(λ) with a QA score of 1 is significantly higher for the GDPS1.3 algorithm (57.36%), compared with Seadas—Default (37.91%), Seadas—MUMM (35.96%), and GDPS2.0 (33.05%). The field and MODIS measurements of Rrs(λ) were compared with simultaneous GOCI Rrs(λ), and they demonstrate that the QA score system is useful in evaluating the spectral shape of Rrs(λ). The comparison results indicate that higher QA scores have higher accuracy of the Rrs band ratio. The QA score system is helpful to develop and evaluate bio-optical algorithms based on the band ratio. The hourly variation of QA score from UTC 00:16 to 07:16 was investigated as well, and it demonstrates that the data quality of GOCI Rrs(λ) can vary in an hour scale. The GOCI data with high quality should be selected with caution when studying the hourly variation of biogeochemical properties in the Bohai Sea from GOCI measurements.

Highlights

IntroductionSensor), OLCI (Ocean and Land Color Instrument), and COCTS (Chinese Ocean Color and Temperature Scanner)
The total QA score of all the six GOCI bands is expressed as n/6 (n = 0,1,2,3,4,5,6), and n is the total number of bands where the score of the specific band is 1
It can be seen that the frequency increases with scores, especially for scores from GDPS1.3

Summary

Introduction

Sensor), OLCI (Ocean and Land Color Instrument), and COCTS (Chinese Ocean Color and Temperature Scanner) They all generally covered the world once every 1–2 days or more, which made them unsuitable for studying the temporal and spatial variation of short time series on the coast. Compared with traditional polar-orbiting ocean water color satellites, the GOCI can provide 8 observations per day, while the second GOCI(GOCI-II) can provide 10, making it possible to observe hourly variations in biogeochemical parameters [4]. It can help monitor short-term changes in water quality, red tides, green tides, etc., in the nearshore waters [5,6]. Many researchers used GOCI data to retrieve water environmental parameters, such as chlorophyll, suspended particle matter (SPM), water transparency, CDOM, sea ice, etc. [7,8,9,10,11]

Results

Discussion

Conclusion