| Summary: | In this paper empirical algorithms for determining the Secchi disk depth (SDD) are developed and employed using optical (e.g., Landsat TM) and microwave (e.g., ERS-2 SAR) remote sensing data from the Gulf of Finland and the Archipelago Sea. The SDD is an important optical measure of water quality in the study area, where the coastal water considerably attenuates light because of the presence of phytoplankton, suspended matter and yellow substance. The results show that the accuracy of SDD estimation using a neural network-based method is much higher than that of a semi-empirical or multivariate approach. On the other hand, the additional use of SAR data only slightly improved SDD estimation when compared with the use of TM data only. Although the improvement is marginal, the results suggest that there may be some SAR backscattering signatures correlated to SDD measurements in the area. However, such a small improvement is not very helpful for the practical estimation of SDD. In the future, the technique of using combined optical and microwave data still needs to be refined using, e.g., MERIS and ASAR data.
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