| Technology and Methodology |
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A Method to Retrieve the Oceanic Absorption Coefficient Based on Artificial Neural Network |
| ZHU Jin-shan1,2, LIANG Shi-ying1, SU Xun-bo3 |
1. Geomatics College, Shandong University of Science and Technology, Qingdao 266590, China;
2. Key Laboratory of Surveying and Mapping Technology on Island and Reed, SBSM, Qingdao 266590, China;
3. College of Civil and Architectural Engineering, Shandong University of Science and Technology, Qingdao 266590, China |
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Abstract The absorption coefficient of water is an inherent optical parameter and constitutes the foundation of research on water optics remote sensing. A method for retrieving the oceanic absorption coefficient using the data of remote sensing reflectance (Rrs) and based on the artificial neural network (ANN) is presented in this paper. The algorithm retrieves the oceanic absorption coefficient with 440 nm as its wavelength, using the situ data of remote sensing reflectance (Rrs) to establish BP neural network. 80% of the situ data of Rrs were used for training data set, and the other 20% were used for testing data set. The results show that making the right choice of the hidden layer joints, transfer function and train function is very important. If we choose the optimal hidden layer joints, transfer function and train function, the correlation coefficient between testing data and situ data can be as high as 0.978, which shows that the method for retrieving the oceanic absorption coefficient based on the artificial neural network is effective.
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| Keywords
remote sensing interpretation
melange zone
slices assemblage
ophiolite
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Issue Date: 20 August 2012
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2012,
Vol. 24
