Automated evaluation of generalized topographic maps

To meet the increasing demand for geospatial information at multiple scales, and to shorten update cycles for up-to-date geo-data, national mapping agencies (NMAs) and other data providers have introduced, or are considering the use of, (semi-)automated generalization systems in their production lines. Map generalization inevitably changes certain aspects (accuracy, completeness, etc.) of spatial data. Therefore, generalized data/maps should be evaluated to see whether they are in line with the map requirements defined for a target scale and for a certain task (e.g. visualization). The use of (semi-)automated generalization systems, on the other hand, increases the need for automated quality evaluation of generalized data/maps. Automated evaluation techniques provide more objective evaluation results and reduce the time needed for the subjective visual assessment. This thesis has identified the following issues from the state-of-the-art of automated evaluation of generalization output: • Lack of formalized map requirements: cartographic constraints were specified at a knowledge level that is only human readable, thus not suitable for automated evaluation. For example, complex concepts, relationships, and acceptable modifications in some constraints are not well defined. • Lack of balanced map requirements for a meaningful evaluation: previous research focused more on readability constraints and constraints for one object, or between two objects. The evaluation based on unbalanced constraints may lead to misleading (e.g. over-optimistic) results. • Lack of explicit information/knowledge, such as characteristics, relationships and patterns in topographic data, and links between corresponding entities between different scales.