Approximate bottom contribution to remote sensing reflectance in Taihu Lake, China
2011
Ma, Ronghua | Duan, Hongtao | Liu, Qinhuo | Loiselle, Steven Arthur
Remote sensing is a fundamental tool for the analysis of spatial and temporal trends in lake ecosystems. A major challenge in using these approaches is determining the possible influence of reflectance from submerged vegetation or the lake bottom. In the present study, we examine the water leaving radiance measured in a large number of sites in Taihu Lake, a large shallow lake in southeast China. Due to the high concentrations of suspended sediment and phytoplankton biomass, a majority of the lake can be considered optically deep (i.e. bottom reflectance could be ignored). However, optically shallow waters were present in the shallow bays on the eastern side of the lake. In these areas, submerged vegetation was present. To explore the contribution of the lake bottom and submerged vegetation on remotely sensed reflectance, we compared two modeling approaches (Hydrolight and the LEE). The results show that differences in optical and physical characteristics of the lake bottom strongly influence the spectral characteristics of the measured reflectance. The resulting impact on the estimate of chlorophyll-a concentrations was tested using datasets with and without sites where bottom effects may occur. A significant improvement in the predictive capacity of the reflectance based estimated of phytoplankton biomass was made when areas with bottom influences were removed from the calibration procedure.
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