Establishing a ANN model with in-situ hyperspectral data for estimation chlorophyll-a concentrations in Nanhu Lake of Changchun, China

Chlorophyll is main part of algae components, chlorophyll-a (Chi-a) exists among all algae, can reflect the water quality to certain degree. Because hyperspectral reflectance can obtain the diagnostic spectrum characteristic, which show a good prospective for environmental problems monitoring that are impossible for multispectral remote sensing. This paper uses the ASD spectrometer to collect the spectrum reflectance of Nanhu lake water body in Changchun. Studies on the relationship between the water body spectrum reflectance and chlorophyll-a concentrations were carried out. It was found that spectra reflectance in green, red and near infrared have a close relationship with chlorophyll-a concentration. Finally spectral ratio, ANN-BP model were applied for chlorophyll-a concentration estimation in Nan Lake with eutrophic water body. Analyses result show that ratio spectrum model obtain determination coefficient (R-2) about 0.6778, while ANN-BP model's estimation determination coefficient is greater than 0.970. It can be seen that ANN-BP inversion model play better in accuracy for chlorophyll determination with hyperspectral reflectance data collected in-situ than spectral ratio model. Still future work need to be done to test the result of our model for eutrophic lake water quality monitoring with hyperspectral reflectance data, as for inversion the spatial variation of chlorophyll distribution in the surface of Nanhu Lake with remotely sensed imagery data, there is even more work and effort should be carried out