Models and Experiments for Adaptive Computer-Assisted Terrain Generalization

The project described in this article had two primary objectives: to design a strategy for terrain generalization that is adaptive to different terrain types, scales, and map purposes, and to implement and evaluate some components of this approach to assess its potential. The strategy includes three different generalization methods: a global filtering procedure, a selective (iterative) filtering method, and a heuristic approach based on the generalization of the terrain's structure lines. For a given generalization problem that is constrained by the terrain character, map objective, scale, graphic limits, and data quality, the appropriate technique is selected through structure and process recognition procedures. Some of the key components of the strategy have been implemented and some experiments were conducted. Other parts were covered by proposing models that could serve as implementation guidelines. Our work was intended to break ground for future research. Recommendations for appropriate parameter settings in relation to scale, terrain character, and other controls of generalization still need to be established. Some alternatives for knowledge acquisition for cartographic generalization are proposed, including the development of a high-level interactive “terrain generalizer.”