In order to improve the precision of phytoplankton chlorophyll-a (chla) concentration retrieval, this study classified the
data into two groups (the high and the low) by chla concentration with the threshold of 50μg·L-1. And then build the
statistical models for each group. Particularly, a modifying factor OSS/TSS was used to unmixing the spectra in the low
model to improve the low relationship between spectral reflectance and chla concentrations. As a result, the
concentration classification model allowed estimation of chla with a root mean square error (RMSE) of 21.12μg·L-1 and
the determination coefficient (R2) was 0.92, comparing with RMSE of chla estimation was 35.72μg·L-1 and R2=0.72 in
the traditional model. It shows that concentration classification is a helpful method for accurate remote chla retrieval in
eutrophic inland waters.
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