Water-Color Remote Sensing Principle And Retrieval Of Suspended Sediment Concentration With Satellite Remote Sensing Method

The concentration of suspended sediment in water is one of important water quality parameters. It is very important to retrieve suspended sediment concentration in the research of water quality, Coast engineering etc. The conventional survey method has many limitations. From these data we can only get few discrete point values in temporal and spatial distribution. While the suspended sediment concentration varies rapidly and complicatedly with the current especially in coast areas. So the data acquired with conventional method can't satisfy concentration research.The application of remote sensing technology makes it possible to get water image in large scale and quickly. And the images contain a great deal useful information on suspended sediment. Through the processing and analysis of these images we can retrieve suspended sediment concentration. Now it gradually becomes a very important method to study suspended sediment.At present, many researchers dedicate to retrieving suspended sediment concentration both home and abroad. And there are many algorithms for suspended sediment concentration developed by remote sensing. This paper focuses on the algorithm of suspended sediment concentration retrieval based on Neural Network. First, many research jobs on this subject are introduced. Then the concept of water-color remote sensing is addressed, including spectrum feature, absorption and scattering coefficient of pure water. Second, Seawater spectrum feature and optical property are also addressed. The relationship between absorption and scattering coefficient of pure water and diffuse attenuation coefficient is important to water color study. In Chap.2 the classification of water and feature of case 2 water are described, as well as spectrum feature of suspended sediment water. Third, A lot of retrieval representative algorithms are also described. The principles and method of water spectrum survey are included in Chap 4. And the function and structure of Neural Network Model is in Chap5. Chap 6 involves data collection and processing. The spectrum feature of water in dalian Bay is also analyzed. Last, in chap 7 neural network model is employed to retrieve suspended sediment concentration from TM image in Dalian Bay. The regression analysis is also applied to these data. The results from two different methods are compared. It is shown that the neural network model gives better result than statistic ones for those data.