A TAXONOMY OF 2D SPACE TESSELLATION
Y. C. Lee, Zhilin Li · 1998
When we map an area or create a digital database for it, the first task is often to partition the space into smaller units. There are traditionally two methods of partition called vector and raster. A vector partition delineates the boundary of features by lines while a raster partition subdivides space into a regular matrix of square or rectangular pixels. The two partitions are complementary methods of subdividing space either by feature or by arbitrary space cells. With advances in data modeling, variations of the two traditional methods have been developed, such as the representation of a feature by pixels and not by vector lines. At present, there is a lack of terminology to describe the various methods of tessellation. In this paper, we will propose a taxonomy for two-dimensional space tessellation. Its essential feature is to distinguish between a conceptual model for tessellation and a set of geometric primitives used to implement the tessellation cells. This allows us to systematically describe the various structures resulting from combining an abstract tessellation with different geometric primitives.