Abstract:Given a spatial raster framework F, a set of explanatory feature maps, training and test samples with class labels on F, as well as a base classifier type, the problem of ensemble learning in raster classification aims to learn a collection of base classifiers to minimize classification errors. The problem has important societal applications such as land cover classification but is challenging due to existence of class ambiguity from spatial heterogeneity, i.e., samples with the same feature values may have di… Show more
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