A new method for estimating chlorophyll-a concentration in the Pearl River Estuary

Abstract

Accurate and reliable assessment of chlorophyll-a (Chl-a) concentration in turbid waters by remote sensing is challenging due to optical complexity of case II waters. Recently, an optimization procedure based on minimizing root mean square error (RMSE) with three-band model was suggested to retrieve the Chl-a concentration in the Pearl River Estuary (PRE) in China. However, it is sensitive to initial values of model parameters and it doesn’t consider other two bands information to determine each optimal band. To estimate the Chl-a concentration according to information of all bands without initial values, we proposed an optimization procedure based on maximizing correlation of the Chl-a concentration in situ and the Chl-a concentration estimated. Firstly, correlations are computed with the three-band model, in which each band varies from the minimal value to the maximal value. Secondly, the sum of correlations for all values of other two bands is computed to find the optimal value for the first band. Lastly, the sum of correlations for all values of other one band with the first optimal band is computed to find the second and third optimal bands. The calibrated three-band model is applied to retrieve the Chl-a concentration from the reflectance data in the PRE on May 16, 2008. RMSE and correlation indices of our method and two state-of-the-art methods in this dataset are shown the effectiveness of our method. These findings imply that the extensive database of remote sensing could be used to quantitatively monitor the Chl-a concentration in the PRE.