Prediction of Chlorophylla Concentration in Dahuofang Reservoir Based on BP Neural Network 〓

doi:10.12068/j.issn.1005-3026.2013.12.028

Abstract

Abstract: With the CCD data of HJ1 satellite and the calculation of MATLAB， this paper analyzes the relationship between chlorophylla concentration and 65 band combinations which consist of four bands(nearinfrared band， red band， green band and blue band) of multispectral CCD data. The study finds that band combination of T1=B4/B3 has the highest correlation with the chlorophylla concentration. Then onedimensional linear model was established by taking T1 as the argument. The degree of fitting R2， the root mean square error and the relative error of the verification points were compared based on the BP neural network. It shows that it is feasible to predict the chlorophylla concentration of Dahuofang reservoir with BP neural network， and the method is better than linear model.

Key words: HJ1, Dahuofang reservoir, chlorophylla, linear model, BP neural network

CLC Number:

WANG Qi， MENG Wei， MA Yunfeng， HU Xiaomin. Prediction of Chlorophylla Concentration in Dahuofang Reservoir Based on BP Neural Network 〓[J]. Journal of Northeastern University(Natural Science), 2013, 34(12): 1792-1795.

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