Abstract
Remote classification of land-use/land-cover (LULC) types in Brazil's Cerrado ecoregion is necessary because knowledge of Cerrado LULC is incomplete, sources of inaccuracy are unknown, and high-resolution data are required for the validation of moderate-resolution LULC maps. The aim of this research is to discriminate between Cerrado and agriculture using high-resolution Landsat 7 ETM+ imagery for the western region of Bahia state in northeastern Brazil. The Maximum Likelihood Classification (MLC) and Spectral Angle Mapper (SAM) algorithms were applied to a ∼3000 km2 subset, yielding comparable classification accuracies. The panchromatic band was reserved for validation. User's and producer's accuracies were highest for non-irrigated agriculture (∼94%) but lower for Cerrado Lato Sensu (89%). Classification errors likely resulted from spatial and spectral characteristics of particular classes (e.g. riparian forest and burned) and overestimation of other classes (e.g. Eucalyptus and water). Manual misinterpretation of validation data may have also led to lower reported classification accuracies.
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