ABSTRACT
Generalization is one of the most important factors in the efficient and effective visualization of spatially referenced data. The relationship between scale and accuracy is especially important at the data capture stage, where all sorts of generalization may have been carried out on the source material. In the mapping context, generalization can be defined as the process of reducing the amount of detail so that the character or essence of the original features is retained at successively smaller scales. An extensive body of literature, consisting of many rules and guidelines, which describes the generalization operations employed in manual map production has been drawn up over many decades. An important question about where automation should be introduced is whether scalefree generalization is required. Changes in the landscape, usually the built environment, invariably lead to changes in the basic scale digital data.
