Remote Sensing Inversion of Water Quality Parameters in Longquan Lake Based on PSO-SVR Algorithm

The paper uses the PSO-SVR algorithm to inverse the water quality parameters based on GF-1 remote sensing image in Longquan lake where is located in Chengdu, Sichuan Province. Longquan Lake is a key drinking water source in Chengdu, so its water quality is very critical. Particle swarm optimization (PSO) optimizes the parameters of the support vector regression (SVR) inversion model to establish the new PSO-SVR inversion model, and PSO can effectively improve the efficiency and the accuracy of the SVR inversion model. At the same, the empirical inversion model was established by using the measured hyperspectral data and concentration of water quality parameters. Comparing with SVR inversion model, PSO-SVR inversion model achieves a better result in the application of suspended solids and Chlorophyll concentration inversion.