The Multi-dimensional Problem of Quantifying Cartographic Generalization Uncertainty: Linear Features as an Example.

Ali M. Al-Ghamdi


This paper highlights cartographic considerations relevant during the process of quantification of generalization uncertainties, defined here as Generalization Factor (GF). The paper adds to current research on map or spatial database errors and uncertainties, but focuses on the complex nature of the quantification process of generalization uncertainties. Three main cartographic aspects or contexts are discussed in this paper: namely, feature complexity, map sources, and map purposes. The paper discusses the difficulties in producing a universal index as GF that accounts satisfactorily for generalization uncertainty. As a result, there is a need for a thorough study to account for all types of generalization uncertainty for each feature according to the cartographic consideration discussed in this study, although such contexts are not exhaustive. The study suggests that the uncertainty measures should result in a form of value that can be attached to each feature in the database, especially for those detailed databases that are designed for analysis purposes. The study suggests that it might well be possible to quantify generalization uncertainty more easily once the process of generalization is performed automatically or even semi-automatically, especially with the advent of new generalization tools.



Cartographic Generalization, Generalization Uncertainty, Generalization Factor, Cartographic Context, Database Accuracy.

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Copyright (c) 2017 Ali M. Al-Ghamdi

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