Spectral Discrimination of Submerged Macrophytes in Lakes Using Hyperspectral Remote Sensing Data

Submerged macrophytes give important information about a lake ́s trophic state and its ecosystem. Aquatic macrophytes can therefore serve as useful indicators of water pollution along the littoral zones. The spectral signatures of various macrophyte species were investigated to determine whether species could be discriminated by remote sensing. The spectral reflectance of macrophytes collected from several habitats at different lakes in South Germany were measured in the field with the RAMSES hyperspectral radiometer. Spectral variations of sunangle effects and seasonal changes were also investigated to determine the intraspecific variability. The collected specific reflectance spectra were used as basis for developing algorithms and applied to airborne hyperspectral remote sensing data from HyMap, acquired during the HyEurope flight campaign in July 2003 and June 2004. The imagery were corrected for atmospheric, airwater interface and water body effects using the physical based Modular Inversion Program (MIP). The various macrophyte taxa were classified to bottom cover classes by linear spectral unmixing combined with spectral derivative analysis. The result contains classes of small growing macrophytes (Characeae), high growing macrophytes (Potamogetae) and bottom sediments. Because of the different growth heights between the two macrophyte groups, Chara and Potamogeton could be successfully identified. Spectral discrimination to species level seems to be possible to a limited extent depending on the amount of epithetic growths, water depths and clarity, as well as the size and homogeneity of the patches.