Abstract
Shallow water, strong sediment resuspension, complex river inputs and frequent cyanobacterial blooms characterize the waters of Lake Taihu. In such shallow, eutrophic lakes, the remote sensing of phycocyanin (PC), a characteristic pigment of cyanobacteria, is dependent on the estimation precision of phytoplankton absorption. For Lake Taihu, we monitored the seasonal–spatial variation of phytoplankton absorption, and a three-band model was calibrated and validated to estimate phytoplankton absorption (aph(665)) from a dataset of the spatial and temporal patterns of the bio-optical properties collected, during five cruises in January (winter), April (spring), July (summer), and October (autumn) in 2006 to 2007. Two distinct situations prevailed; in winter tripton strongly predominated over particulate matter, and in spring-summer-autumn phytoplankton made an important contribution. In winter, meteorology mainly determined the bio-optical properties of the water column, whereas in the spring-summer-autumn the biological activity was an additional active factor. The three-band remote sensing model 1⁄2R 1 rs ð673Þ R 1 rs ð698Þ Rrsð731ÞðRrs: remote sensing reflectance) of aph(665) was calibrated and validated, and its performance was compared and assessed with the published band-ratio method. With the three-band model, the root mean square error and mean relative error were 0.150 m (50.5% accounting for the mean value) and 45.7% respectively; with the published band-ratio method, the values were 0.290 m (97.3% accounting for the mean value) and 213.0% respectively, based on an independent validation dataset. Furthermore, the three-band and band-ratio models worked well in estimating phytoplankton absorption with simulated MERIS bands data with higher precision for the three-band model in Lake Taihu. The result showed that the three-band model was superior to the published band-ratio method, and thus the former can be used to improve the estimation precision of remote sensing of PC.
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