Int. J. Environ. Res. Public Health 2010, 7 2446 According to the correlation analysis results, the R861.1/R865.7 reflectance ratio with the maximum correlation coefficient of Chl-a concentration was selected for linear modeling. For the measured data, the R2 of the model reached 0.8605. The model based on correlation analysis was better than the one with empirical characteristic band combinations. The reflectance radio of different bands reduces the noise for Chl-a concentration estimation and improves the reflectance information of Chl-a, which can be used to improve the accuracy of Chl-a retrieval. Reflectance ratio model shown in Figure 6 is different from the models established in our studies. It indicates that the optimal bands should be indentified before application of reflectance radios for Chl-a estimation. 4. Results The objective of this study is to obtain the optimal model and its most suitable band combination for Chl-a concentration estimation based on remote sensing data in Tangxun Lake. Linear regression models were adopted in the paper for comparison. As shown in Table 2, distinct bands are selected with accuracy for three models. Table 2. Regression models for Chl-a with three types of spectrum indices. Model Single-band First-derivative Reflectance Ratio Optimal Bands 733.1 nm 446.9nm R861.1/ R865.7 Model Chla = −0.0227×R733.1 + 0.0568 Chla = −0.3301R’446.9 + 0.023 Chla = 0.2293 × (R861.1 / R865.7) − 0.2146 R2 0.705 0.863 0.861 MRE 26.3% 11.2% 13.8% The bands between 726.5 nm and 734.4 nm are selected for Chl-a concentration in Tangxun Lake with the single-band algorithm, and the R2 of the linear model is approximately 0.705. For the first-derivative algorithm, the optimal band for Chl-a retrieval is at 446.9 nm with a highest R2 value of 0.863. And R861.1/R865.7 ratio is the best band combination for the reflectance radio algorithm, whose accuracy is slightly lower than first-derivative one with a R2 value of 0.861. The mean relative error (MRE) is also calculated for three kinds of models. The MRE is expressed as: MRE = 1n ni yi − yfi (xi ) *100% (3) where yi is the ith observed test sample value, n is the number of samples and f(xi) is the estimated ith value. The MRE of first-derivative model is the lowest with a value of 11.2%, and the MRE of reflectance ratio model is slightly higher, with a value of 13.8%. Meanwhile, the largest error exists in the single-band model with an MRE of 26.3%. It can therefore be concluded that it is feasible to to estimate Chl-a concentrations in Tangxun Lake with the algorithms of first-derivative and reflectance radio, which are better than the single-band model. While in practical Chl-a monitoring, it is necessary to select the most suitable one according to the available data. The results of three kinds of regression models are shown in Figure 8, Figure 9 and Figure 10 respectively.