| This research presents routines for semi-automated macrophyte vegetation mapping using remote sensing technologies in Onondaga Lake. The study evaluated the effectiveness of IKONOS and ASTER satellite imagery as an alternative to aerial photograph interpretation. Initial image processing isolated and extracted the Lake's littoral zone using band ratios and digital bathymetry data. The second phase of processing applied an ISODATA clustering algorithm to numerous image and derived image products including NDVI, chromaticity and texture. The derived image data were incorporated to enhance subtle differences in water clarity, color and surface continuity created by macrophyte vegetation. Finally, macrophyte vegetation maps were analyzed and standard error matrices and percent cover calculated. While preliminary results illustrate potential, low classification accuracies create an inability to accurately estimate cover or presence. Factors such as seasonality of image data, size and shape of macrophyte beds contributed extensively to the misclassification of aquatic macrophyte vegetation. |
