Generalization Expert System (ges): a Knowledge- Based Approach for Generalization of Line and Polyline Spatial Datasets

Current map production systems provide reasonably complex tools and procedural cartographic protocols, however, cartographers’ interactions are essential for selecting information, symbolizing features, maintaining topological relationships, and visualizing graphical conflicts. Although an efficient generalization technique would improve the graphical quality and legibility of maps, existing techniques use an “ill-structured” approach because it is hard to devise an algorithm to solve the problem. On the other hand, expert systems use a collection of “rules of thumb” that are mainly heuristics methods or principles for decision making. It is an alternative solution to the aforementioned problem. This paper presents “Generalization Expert System (GES)”: a knowledge-based solution. Key steps undertaken in building GES and its components are presented. GES is developed in Java and Python for the delivery of simplified spatial data. Its capabilities are demonstrated in a case study through simplifying roads, native vegetation and elevation data to derive 1:500,000 scale from the source maps at 1:250,000 scale over Canberra, Australian Capital Territory, Australia. Although a number of advanced applications have been developed with high technical skills, GES has a simple and user-friendly GUI that can benefit users with lesser technical skills and knowledge of spatial data management.