Comparative evaluation of ALMAZ, ERS-1, JERS-I and Landsat-TM for discriminating wet tundra

Classification algorithms based on minimum-loss criteria and software have been developed and have been applied to ALMAZ, ERS-1 and JERS-1 SAR and Landsat-TM data to evaluate the relative information content of data for discriminating wet tundra habitats in Northern Alaska. Four vegetation/terrain classification schemes were used as “ground-truth” for evaluating the image classifications. Results suggest that SAR data can be used to concurrently detect a maximum of four or five tundra landcover classes using the methods of this study. Combining two or more SAR images from different satellites improved the detection of same classes, particularly water bodies