Multi-spectral remote sensing based water quality monitoring for Lake Tai

In this paper, a practical and operative method is presented for water quality classification in Lake Tai using multi-spectral remote sensing data. The remote sensing models of chlorophyll-a and suspended sediments are developed by integration of Landsat5 TM images and in situ measurements in the period of from year 2003 to 2004. The key issues in applying multi-spectral satellite imagery to water quality are first given, including radiation calibration, geometric correction, atmospheric correction, noise elimination by spatial filtering and the spectral reflectance obtain. The multi-spectral band analysis is further studied to determine the relations between various bands emissivity, the emissivity combination and the water quality parameters. The regression models for chlorophyll-a and suspended sediments are derived, and the accuracies and correlation coefficients of the models are analyzed. The water quality parameters obtained from the regression models are tested with the in situ measurements, which proves the uniformity between these two results. This means the feasibility of the multi-spectral remote sensing data for monitoring the water quality in Lake Tai.