| Harmful Algal Bloom (HAB) is one of the most common disasters in the East China Sea (ECS), and the establishment of an accurate remote sensing algorithm of HAB extraction is the primary concern of timely and effective monitoring and predicting to minimize the harm. The Ocean Color remote sensing algorithms of HAB extractions now mainly concentrate on chlorophyll concentration anormaly or spectral (Apparent Optical Properties) extraction algorithms. The seawater properties in the HAB highly occur area in ECS is very complicated, which is under severe influences of colored dissolved organic matter as well as suspended particles, and thus the spectral extraction algorithms are usually prone to be invalid. In order to extract the HAB effectively, the seawater Inherent Optical Properties (IOPs) including algal cell size and physiological properties need to be analyzed. Typically, researchers are more willing to develop a targetable algorithm for a typical algal type, which usually tends to be more harmful and popular, so as to prevent and govern the disasters more effectively. Currently, research in this area is little yet.IOPs can reflect the physiological and biochemical properties of the water body and reflect differences due to the substance changes. It plays significant role in developing proper extraction algorithms, and possesses huge potentials in HAB monitoring and identification. Accordingly, the thesis starts with the IOPs of seawater of dinoflagellates and diatom type HAB and the normal environment in ECS to establish the extraction algorithm. The content and achievement of this thesis is as follows:(1) Based on the research and analyses of seawater IOPs parameters from the two large scale investigations conducted in ECS in summer and winter,2009. the seasonal and spatial distributions and variations of seawater absorption and scattering coefficients are analyzed, and it forms the background of HAB in ECS. It is found that, in moderate turbid seawaters, the terrestrial colored dissolved organic matter as well as non-algal detritus particles will apparently interfere the pigment absorption spectra.(2) By analyzing the HAB events occurred in the last ten years in ECS, it is found that the main type of HAB is dinoflagellates (i.e. Prorocentrum donghaiense and karenia mikimotoi) and diatom (i.e. Skeletonema costatum). and the dinoflagellates type usually forms toxic HAB. And accordingly, the IOPs of these type HAB events measured from the Changjiang Estuary and Nanji Islands respectively are analyzed, and the differences of seawater absorption and scattering coefficient are gained for discrimination.(3) The IOPs data from insitu and remote sensing of HAB waters in ECS are analyzed, and a model for eliminating the HAB region and identifying the algal type is established, based on the pigment absorption ratio, the chlorophyll specific phytoplankton absorption coefficient, the back scattering-to-total absorption coefficient ratio, and the backscattering coefficient ratio, respectively. With aid of reflectance spectral properties, the extraction and identification of different algal classes such as diatom and dionflagellates are achieved.(4) The established model is applied to the big HAB events in ECS and the final result of extraction and identification is satisfied. The accuracy rate of identification for the test of the 16 samples is up to 92%.The main innovations of this work are:(1) The characteristics and discrimination of IOPs between HAB water and normal seawater as well as dinoflagellates and diatom type HAB seawater in ECS are eliminated, which is of significance to the scientific research on HAB development.(2) A series of extraction models including the spectra relative height, the pigment absorption proportion and the backscattering ratio based on IOPs of seawater absorption and backscattering coefficient are established and applied for HAB extraction and class type discrimination, and it is proved to be practical and of reference value for automatic HAB detection. |
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