ScaleMaster 2.0: a ScaleMaster extension to monitor automatic multi-scales generalizations

Little by little, co-existing geographical data sets are integrated into multi-representation databases, where the data sets represent different level of detail, or different point of views for the same geographical features. The ScaleMaster model makes it possible to formalize how to choose the features to map from the different data sets. The paper proposes an extension of the ScaleMaster model that drives automatic generalization rather than guidelines for manual mapmaking. The ScaleMaster 2.0 has been implemented and is tested for use with real data.

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