Preserving Changes After Cartographic Generalization: A Framework and Example of Line Simplification

Given the increasing collection and availability of multi-temporal geodata (e.g., on ecological, epidemiological, or social topics), there is a growing need to visualize changes in geometry and content in a clear and interpretable way.Cartographic generalization must therefore be required not only to preserve important geometric and thematic features, but also their patterns of change.The problem is that this aspect has so far been addressed in only a very small number of scientific studies (exceptions include, for example, Schiewe 2024 or Cybulski 2022), let alone offered as a feature in GIS software.Consequently, this paper has two objectives: First, it presents a framework that explicitly highlights the various options for preserving change properties following a cartographic generalization.Second, it focuses on a typical generalization operation-the simplification of lines-and demonstrates how algorithmic extensions of the Douglas-Peucker algorithm can follow the idea of this framework.