Polygon simplification and aggregation play an important role in automatic cartographic generalization. Design of this kind of operator algorithm requires to consider geometric and topological characteristics

and needs to find a spatial data model to support extraction of interesting adjacent area

such as bend feature

gap region between polygons

neighbor area between islands within polygon. In this process

detection of neighbor relation is a key step. Delaunay triangulation structure is a powerful tool of spatial neighbor analysis due to its circumcircle principle and closest to equilateral properties. Applying Delaunay triangulation principles

this paper presents a spatial data model and constructs formal selection strategies. On the basis of constructed model

the study systematically investigates the problem of polygon bend simplification

exaggeration as well as neighbor polygon aggregation. The paper divides polygon simplification into steps: islands selection

concave part fill

shallow area skeletonizing

concave part exaggeration and convex part clip. As for polygon aggregation

it is classified as three cases: absorbing

enclosing and separating and three methods are discussed respectively. Some of operator algorithms are presented in the paper and corresponding experiment results are illustrated.