Remote sensing retrieval method for extracting chlorophyll concentration distribution information of complex water body

Abstract

The invention relates to a remote sensing retrieval method for extracting chlorophyll concentration distribution information of a complex water body, which comprises the steps: receiving MODIS L0 data of a CMACast data transmission system in real time, and decoding to convert to a MODIS L1b data product in a hdf format; performing atmosphere correction on the MODIS L1b data product; performing dual optimization iteration chlorophyll inversion by reflection rate data subject to atmosphere correction. A GSM algorithm and a semiempirical algorithm of LI Zhongping are combined with a chlorophyll inversion algorithm, absorption scattering optical characteristics of phytoplankton are inverted by adopting twice nonlinear optimization iteration, thus avoiding influence of absorption fluorescent characteristics of CDOM on a reflection rate spectrum, more accurately extracting chlorophyll concentration information, and providing technical support for a water color remote sensing inversion algorithm.

Description

technical field [0001] The invention relates to a water quality analysis method, in particular to a method for extracting chlorophyll concentration distribution information of complex water bodies. Background technique [0002] The chlorophyll concentration distribution data products retrieved based on satellite remote sensing images MODIS can be used to analyze the water quality conditions of oceans, coastal areas, and lakes, the probability of red tide outbreaks, the eutrophication of water bodies, and the level of primary productivity. Accurate inversion of chlorophyll concentration distribution data is of great significance to the study of seawater harmful algal blooms, marine biological processes, marine carbon cycle and even global climate change. [0003] In recent years, the remote sensing inversion algorithm for extracting chlorophyll concentration distribution has received great attention and attention, and it is the most researched field of ocean color. A variety...

AI Technical Summary

Problems solved by technology

A variety of algorithms have been established for chlorophyll inversion methods, but the current algorithms still have the following problems: the first is that the semi-empirical remote sensing inversion algorithm and standard empirical algorithm for chlorophyll are better for a type of water body, but for Nearshore water bodies with complex optical characteristics, poor application effect and low reliability

In the nearshore, the water body is generally relatively turbid, and the influence of the absorption and scattering characteristics of particles will cause large errors in the semi-empirical remote sensing inversion algorithm and the standard empirical algorithm generally used for a type of water body

Therefore, it is necessary to establish a specific model for a specific specific offshore water body in order to retrieve the chlorophyll concentration product more effectively; the second problem is that the current algorithm is not strong enough to distinguish the optical signals of CDOM and chlorophyll. High turbidity and high CDOM near the coast will seriously affect the accuracy of these chlorophyll empirical algorithms

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