Abstract
This work presents a comparative analysis of ERS-1 Synthetic Aperture Radar (SAR) and Landsat-5 Thematic Mapper (TM) images used for land use classification. The study area of 361 km2 is located in the City of Campinas, Sao Paulo State, Brazil, and contains several classes of land use, including urban, agricultural and forests. The TM and SAR images were registered and transformed using the principal components transformation. SAR images were also filtered using an average filter. The principal components derived from SAR filtered, SAR, TM and coregistered TM/SAR and TM/SAR filtered images were classified using the maximum likelihood approach. Tests of 'goodness of fit' were also made to assess the statistical properties of the images. The results, confirmed by Kappa statistics, show a significant improvement when classifying the principal components of filtered SAR and TM images for urban, pasture and forest classes.
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