Data mining of multidimensional remotely sensed images

As scientific spatial databases grow at unprecedented rates, new approaches are necessary to enable scientists to efficiently locate data sets pertinent to their needs, One method that shows promise is the augmentation of a metadatabase with information on image content so that users can be heuristically guided to appropriate data sets. This paper motivates a need for building more intelligent databases and examines methods for automatically extracting content from image data, The paper concludes with a discussion of automated discovery aa it pertains to multidimensional remotely sensed images.

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