Author(s)

Huibin Wang, Tanghuai Fan, Aiye Shi, Fengchen Huang, Huimin Wang

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To improve the monitoring precision of lake chlorophyll a (Chl-a), this paper presents a fusion method based on Choquet Fuzzy Integral (CFI) to estimate the Chl-a concentration. A group of BPNN models are designed. The output of multiple BPNN model is fused by the CFI. Meanwhile, to resolve the over-fitting problem caused by a small number of training sets, we design an algorithm that fully considers neighbor sampling information. A classification experiment of the Chl-a concentration of the Taihu Lake is conducted. The result shows that, the proposed approach is superior to the classification using a single neural network classifier, and the CFI fusion method has higher identification accuracy.

Water Quality Monitoring, Remote Sensing, Neural Networks, Fuzzy Integral, Information Fusion

H. Wang, T. Fan, A. Shi, F. Huang and H. Wang, "Fuzzy Integral Based Information Fusion for Water Quality Monitoring Using Remote Sensing Data," International Journal of Communications, Network and System Sciences, Vol. 3 No. 9, 2010, pp. 737-744. doi: 10.4236/ijcns.2010.39098.