Optical Characteristics And Remote Sensing Retrieval Of Phytoplankton In Eastern China Seas

Phytoplankton is an important part of the earth’s ecosystem.Due to the differences of morphological structure and growth law,the contribution of different phytoplankton to biogeochemical cycle and ecosystem is different.In order to improve the understanding of the role of phytoplankton in marine ecosystem,it is necessary to effectively observe the temporal and spatial distribution of phytoplankton.The development of remote sensing technology provides important data for large-scale and continuous observation of phytoplankton.Remote sensing observation takes electromagnetic wave as the medium,so it is necessary to study the optical separability based on the inherent optical characteristics of phytoplankton.For class II water bodies,it is also necessary to investigate the effects of Chlorophyll a（Chl a）concentration,Colored Dissolved Organic Matter（CDOM）and Non-Algal Particles（NAP）on the remote sensing reflectance(R_rs)spectral characteristics of phytoplankton.In the past decades,the research of phytoplankton using satellite has been fully developed in the ocean with relatively simple ocean color components.However,there are great challenges in the eastern China seas with complex optical characteristics.In the eastern China seas,the remote sensing retrieval model of phytoplankton groups is often established with Chl a concentration and phytoplankton absorption coefficient products as inputs.However,there are still high uncertainties in the Chl a concentration and phytoplankton absorption coefficient products retrieved from R_rs in this area.Therefore,it is necessary to study the direct retrieval of phytoplankton groups from R_rs.This study takes the eastern China seas as the study area and carries out the following research:（1）Based on the absorption coefficient of phytoplankton of pure algae species,the absorption spectrum characteristics of differences of different phyla of algae,different dinoflagellates and different diatoms were investigated by derivative analysis and divergence index.Combined with the pigment data corresponding to pure algae species,the reasons for the differences of absorption spectra of different algae species were analyzed.It is found that there are great differences in the absorption spectra of different phyla of algae,especially between chlorophytes or cyanobacteria and other phyla.The main reason is that different phyla of algae species contain different types and contents of pigments.There are also some differences among the absorption spectra of the three dinoflagellate species,mainly because the characteristic pigment types of different dinoflagellates species are quite different.Because six diatom species contain the same type of pigments,there is little difference between the absorption coefficient spectra of different diatoms species.（2）Using the measured inherent optical characteristics of algae species,the R_rs of different algae species under different ocean color components is simulated,and the effects of Chl a concentration,CDOM,NAP concentration and spectral resolution of R_rs on the remote sensing classification of phytoplankton are analyzed.It was found that with the increase of Chl a concentration,the difference of R_rs under the action of different algae species increased.When the concentration of Chl a is low,it is a great challenge to distinguish phytoplankton from R_rs.With the increase of the concentration of CDOM or NAP,the spectral characteristics of R_rs by phytoplankton in the short-wave position will be gradually masked.With the decrease of spectral resolution,the distinguishability of different algae species decreases.Hierarchical clustering results show that cyanobacteria and chlorophytes can be well distinguished from other algae species when the concentration of non algal particles is low,and it is difficult to distinguish among diatoms,cryptophyte and xanthophyta.There are great challenges discrimination between different algae species of the same phylum by R_rs.（3）By using three modeling methods,namely band combination method,multiple linear regression method based on singular value decomposition（SVD+MLR）and XGBoost regression method based on singular value decomposition（SVD+XGBoost）,the phytoplankton group is retrieved from R_rs data.Verified by the in-situ measured data set,the Chl a concentration retrieval model of eight phytoplankton groups by SVD+XGBoost has the highest accuracy,and the determination coefficient（R~2）of Chl a concentration inversion model of diatoms and dinoflagellates in the validation set is greater than 0.7.In contrast,the accuracy of Chl a concentration of chlorophytes,cyanobacteria and chrysophytes estimated by the three modeling methods is low（the R~2 of the validation results is less than 0.45）.At the same time,the applicability of four atmospheric correction methods of OLCI images（ACOLITE C2RCC,MUMM and POLYMER）in the eastern China seas is evaluated.The results show that compared with the other three atmospheric correction algorithms,C2RCC has better performance in each band(root mean square error is less than 0.0048 sr^-1).（4）The phytoplankton group inversion model is applied to the atmospheric corrected OLCI image.The validation results show that the Chl a concentration of diatoms model established by SVD+MLR has better accuracy（the R~2 is 0.56）.The remote sensing inversion model of Chl a concentration of diatoms is applied to OLCI images to retrieve the mean Chl a concentration of diatoms in the eastern China seas in May 2020 and August 2020.The results show that the high value areas of Chl a concentration of diatoms is concentrated in the coastal waters,and the low value areas are mainly in the middle of the Yellow Sea and the sea off the East China Sea,as well as the turbid waters with high suspended sediment content along the coast of northern Jiangsu coast and Hangzhou Bay.