ESTIMATION OF OPTICAL PROPERTIES USING QAA-V6 MODEL BASED ON MODIS DATA

Abstract

Optical property parameters play an important role in ocean colour studies. As a key variable, the absorption coefficient is of great significance for calculating the content of each component in water and simulating the physical, chemical and biological properties of water. The inversion algorithms mainly include empirical model, semi-analytical model and neural network model. In this study, we focused on the QAA_V6, which is the newest version of Quasi-Analytical Algorithm (QAA). It is necessary to test the QAA_V6 model in different conditions. IOCCG data set is used to verify the accuracy of QAA_V6. Additionally, MODIS data of case 1 waters and case 2 waters were selected. After extraction and matching, the data was finally imported into QAA_V6 model to calculate the absorption coefficient with a R2 of 0.999 in both case 1 waters and case 2 waters, thus the QAA_V6 model showed a high accuracy and robust applicability in the inversion of inherent optical properties. Subsequently, it can be further verified for the waters in more complicated areas, providing a firm foundation for implementing QAA into the research of ocean colour remote sensing.