Abstract
Semi-analytical remote sensing applications for eutrophic waters are not applicable to oligo- and mesotrophic lakes in the perialpine area, since they are insensitive to chlorophyll concentration variations between 1 and 10â� mg/m3. The neural network based Case-2-Regional algorithm for MERIS was developed to fill this gap, along with the ICOL adjacency effect correction algorithm. The algorithms are applied to a collection of 239 satellite images from 2003-2008, and the results are compared to experimental and official water quality data collected in six perialpine lakes in the same period. It is shown that remote sensing estimates can provide an adequate supplementary data source to in situ data series of the top 5â� m water layer, provided that a sufficient number of matchups for a site specific maximum temporal offset are available.
Odermatt, D