Aggregation of 3d Buildings with a Hybrid Data Model

The cartographic generalization prepares and arranges the contents of a map for a given scale and application in order to improve its comprehensibility. In recent years, the data sets for map-like presentations in 3D has become widespread available. Concerning urban areas, the most important objects therein are buildings. Whereas quiet a number of generalization algorithms for 3D data have been proposed, most are concerned with the geometric simplification of buildings models under building-specific constraints. However, the simplification of single objects can only reach a certain degree of abstraction. To obtain further levels, adjacent buildings or even blocks of buildings have to be regarded, e.g. by aggregation or typification. In previous work, a simplification approach for 3D building models by means of cell decomposition has been proposed. A simplified version of a polyhedral 3D building model is constructed by intersecting a minimum number of planes that approximate well the initial shape. In this process, the space around a building is decomposed into building and non-building cells. To determine which cells are building cells, an overlap test with the original building is conducted in raster space. As the cell decomposition features already the necessary cells for an aggregation of buildings, which are, however, discarded due to their low overlap, it is suggested to use morphological operations to close the space between buildings in the raster model and therefore improve the overlap value of the cells. It is shown that the morphology of raster data can help the algorithm to aggregate polyhedral building models.