Quantitative Retrieval of Chlorophyll-a by Remote Sensing in Taihu Lake based on TM data

Based on TM(ETM) data and in-situ measurements of chlorophyll-a concentration(Chla) in Taihu Lake,analysis was conducted to decide the correlation between Chla and the ratios of different reflectance corrected by the 6S model.The results show that Chla is closely related to TM3/(TM1+TM4) and the inverse model to infer Chla in Taihu Lake can be written as ln(ChlA)=-9.247*(TM1+TM4)/(TM2+TM3)-27.903*TM3/(TM1+TM4)+24.518.However,the accuracy of this model can not be enssured due to the complexity of spectral reflectance strongly depending on water quality in Taihu Lake.Thus a further 2-layer BP neural net model based on 4 input nodes,7 hide nodes and 1 output node was made to decide Chla in the lake.The derived results reveal that the BP model has much higher accuracy than the linear model.A test was made based on the chosen 16 samples and the results suggest that the maximum relative error(RE) of BP model was only 35.43%.Of all the samples,15 ones had a RE of less than 30%,accounting for 93.7% of the total samples.However,there were only 3 with RE less than 30% from the results derived from the linear model.The comparison shows that the BP model has high availability for inferring Chla of surface water having complex spectral reflectance.