THESIS ABSTRACT
Landsat Thematic Mapper (TM) and multi-temporal ERS-1 synthetic aperture radar were used to classify wetlands in the Tanana Flats area, interior Alaska. Thematic Mapper bands 1 through 5 from a single image and 23 separate radar images were co-registered and clipped to create a combined, multitemporal stack of grids. A maximum likelihood classifier was then used to classify: 1) single date, single band radar images, 2) multitemporal radar images, 3) a multispectral TM image, and 4) combined multitemporal radar and multispectral TM imagery.
Overall classification accuracy for the multitemporal radar images was significantly higher than for any single-date radar classification. The TM classification separated classes well within the 'wetland and 'non-wetland' categories. However, the TM classification often confused classes between wetland and non-wetland categories. Overall accuracy for the combined multitemporal radar and multispectral TM imagery was significantly higher than for either the multitemporal radar or the mulitspectral TM classification alone. The combination retained the strengths of each sensor: radar's wetland versus non-wetland delineation, and TM's relatively accurate classification different vegetation types within wetland and non-wetland categories.
email: abalser@lter.uaf.edu
