Semi-analytical approach combined & neural network technology model chlorophyll-a concentration by remote sensing

The accurate assessment of chlorophyll-a concentration in turbid coastal waters by means of remote sensing is quite challenging. In this study, a semi-analytical approach is used to analyze the mathematical relationship between chlorophyll-a concentration and remote sensing reflectance. Through evaluation by field measurements, it is shown that our model produces 31.4% uncertainty in quantifying chlorophyll-a concentration from the YS & ECS. Moreover, the performance of new model was compared with four existing models, and the results indicate that the use of our model for quantifying chlorophyll-a in the YS & ECS can decrease uncertainty by >58% in comparison to the four existing models. The atmospheric influences on MODIS data are removed using a near-infrared-shortwave infrared model.