Capabilities for the retrieval of coastal water constituents (case II) using multispectral satellite data

The difficulty of the remote sensing of coastal water is the presence of more than one constituent with high variability ranges, different correlation and spectral behavior. They are superimposing in their influence on the resulting total spectrum. Simple ratio algorithms applied to remote sensing data fail on the quantitative determination of the single constituents. However, coastal regions are of great interest for remote sensing since most of the consequences of urbanization are manifested here. For the improvement of remote sensing of coastal zones it is not only necessary to build a new generation of sensors that offer spectrally higher resolved data, but one has to develop a new methodology that allows the separation and determination of the water constituents based on the entire spectral signature of the different components of the water body. The imaging spectrometer MOS flying on the Indian remote sensing satellite IRS-P3 provides since March 1996 remote sensing data in 13 spectral channels for the scientific community. We implemented a new methodological approach to derive different case II water constituents as well as atmospheric turbidity for the application of MOS-data in costal regions. A new point of the method is the uniform consideration of atmospheric and water constituent influences on the remote sensing signal. The paper will present a short overview on the algorithm's essentials and examples for the large variability of coastal waters around Europe basing on the results of the retrieved water constituents using the MOS algorithm. It will demonstrate the promising potential of this new algorithm for discrimination of single constituents under case II conditions. Derived maps of chlorophyll like pigments, sediments and aerosol optical thickness are shown and will be discussed.