Testing the spectral decomposition algorithm (SDA) for different phytoplankton species by a simulation based on tank experiments

Abstract

The spectral decomposition algorithm (SDA), which is a new approach for the simultaneous estimation of chlorophyll-a (Chl-a) and non-phytoplankton suspended solid (NPSS) concentrations in Case 2 waters using satellite data, was proposed by our previous study. Here, we investigated the effect of phytoplankton composition on the SDA based on the tank experiments using cultured samples for five phytoplankton species (three cyanobacteria, one green algae and one diatom) and lake water samples collected from Lake Kasumigaura from September 2004 to August 2005 except for April 2005. The results showed that the SDA-based models obtained from the cultured samples (culture-based models) showed high accuracies for Chl-a and NPSS estimations in all phytoplankton species (root mean square error [RMSE] about 16.2 μg l^− 1 for Chl-a and about 11.0 mg l^− 1 for NPSS). However, the Landsat Thematic Mapper (TM) band combinations, which gave the smallest RMSE of the Chl-a and NPSS estimations, differed among the species. In addition, the culture-based models could apply to lake water samples with similar accuracies if the optimal standard reflectance spectra (SRS) of end-members in the water body could be determined. This implies the potential of the SDA-based model as follows: (1) it is less site- and time-specific compared with conventional empirical methods (single band, band ratio, and arithmetic band calculation); (2) it can be proposed by a tank experiment or by a simulation using bio-optical modelling.