Polygon Generalization
Definition
Polygon generalization simplifies complex geometries to make maps legible at smaller scales while preserving essential shape and topology. Techniques include Douglas–Peucker simplification, Visvalingam–Whyatt, bend simplification, smoothing, squaring, and collapse/merge operations for small features. Good generalization is context-aware: shorelines simplify differently from city blocks; islands must not disappear; shared boundaries must remain coincident between layers; and topology must avoid gaps and overlaps. Multi-scale cartography uses multiple geometry representations tuned to zoom levels. Beyond aesthetics, generalization affects analytics—area, perimeter, and adjacency change—so provenance and limits should be documented. Automated pipelines often combine heuristics with manual oversight for critical areas.
Application
National basemaps and atlases use generalized boundaries for readability. Navigation maps reduce noise at small scales. Habitat and land-cover products publish small-scale versions to speed web delivery while preventing misleading detail. Disaster maps generalize complex coastal lines to communicate evacuation zones clearly.
FAQ
How do you keep shared borders aligned after simplification?
Generalize in a topologically integrated dataset or apply the same operations to both sides of shared edges to prevent slivers.
What’s a safe tolerance value?
It depends on scale and feature importance. Test print/preview at target scale and iterate; use adaptive tolerances tied to local curvature.
Can simplification distort statistics?
Yes—area and perimeter change. For analysis, use unsimplified geometry; reserve generalized layers for visualization unless metrics are adjusted.
How to prevent tiny polygons from vanishing?
Use collapse rules that convert small features to points or emphasize them with symbols; maintain a minimum area threshold with exceptions for critical sites.