Remote sensing of suspended sediment water research: principles, methods and progress

被引:0
|
作者
Shen, Ping [1 ]
Zhang, Jing [1 ]
机构
[1] Wuhan Polytech, Sch Biol Engn, Wuhan 430074, Peoples R China
关键词
remote sensing; suspended sediment; atmospheric correction; adjacent effect; artificial neural network(ANN); genetic algorithm(GA); support vector machine(SVM); Bayesian networks(BN);
D O I
10.1117/12.899297
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
In this paper, we reviewed the principle, data, methods and steps in suspended sediment research by using remote sensing, summed up some representative models and methods, and analyzes the deficiencies of existing methods. Combined with the recent progress of remote sensing theory and application in water suspended sediment research, we introduced in some data processing methods such as atmospheric correction method, adjacent effect correction, and some intelligence algorithms such as neural networks, genetic algorithms, support vector machines into the suspended sediment inversion research, combined with other geographic information, based on Bayesian theory, we improved the suspended sediment inversion precision, and aim to give references to the related researchers.
引用
收藏
页数:8
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