An Extended Quasi-Analytical Algorithm for Retrieving Absorption Coefficient Using 510-620 nm Bands from OLCI and MERIS Satellite Data

This study focuses on deriving the total absorption coefficients based on field measurements and satellite data. An extended quasi-analytical algorithm (QAA-GRI) was developed based on the two in situ datasets collected from inland waters of Lake Qiandaohu (QDH) and oceanic waters of the East China Sea (ECS). The key model between absorption coefficients at 510 nm (a(510)) and green red index (GRI) was established using power function in the extended QAA-GRI algorithm. The results reveal that the extended QAA-GRI algorithm performs better than the original quasi-analytical algorithm (QAA-v5) and Garver-Siegel-Maritorena's algorithm (GSM), and the red-green quasi-analytical algorithm (QAA-RGR), at least for the two in situ datasets from the ECS and QDH. For QAA-GRI, the averaged mean absolute percentage error (MAPE) value of retrieved versus in situ total absorption coefficients is approximately 20%. Subsequently, the extended QAA-GRI algorithm was applied to the OLCI satellite imagery, which is the new successor of MERIS with three specific bands (510, 560, and 620 nm). The implementation of the extended QAA-GRI algorithm on OLCI imagery yielded similar results comparable to that of the QAA-v5 in the ECS region. Furthermore, the application of the algorithm on seasonal and annual MERIS satellite imagery help clarify the combined influences from Yangtze River discharge and coastal currents on the distribution of total absorption in the ECS waters. This study suggests that the extended QAA-GRI algorithm is an alternative for retrieving total absorption coefficient, although it is not recommended for highly turbid waters.