Other metrics such as the level of spatio-semantic coherence and resolution of the texture can be considered a part of the LOD. For example, CityGML defines five LODs for building models:   There exist also approaches to generalize a given detailed 3D city model by means of automated generalization. For example, a hierarchical road network (e.g., OpenStreetMap) can be used to group 3D city model components into "cells"; each cell is abstracted by aggregating and merging contained components. GIS data provide the base information to build a 3D city model such as by digital terrain models, road networks, land use maps, and related geo-referenced data. GIS data also includes cadastral data that can be converted into simple 3D models as, for example, in the case of extruded building footprints. Core components of 3D city models form digital terrain models (DTM) represented, for example, by TINs or grids. Typical sources of data for 3D city model also include CAD models of buildings, sites, and infrastructure elements. They provide a high level of detail, possible not required by 3D city model applications, but can be incorporated either by exporting their geometry or as encapsulated objects. Building information models represent another category of geo-spatial data that can be integrated into a 3D city model providing the highest level of detail for building components. Complex 3D city models typically are based on different sources of geodata such as geodata from GIS, building and site models from CAD and BIM. It is one of their core properties to establish a common reference frame for heterogeneous geo-spatial and geo-referenced data, i.e., the data need not to be merged or fused based on one common data model or schema. The integration is possible by sharing a common geo-coordinate system at the visualization level. The simplest form of building model construction consist in extruding the footprint polygons of buildings, e.g., taken from the cadaster, by pre-compute average heights. In practice, 3D models of buildings of urban regions are generated based on capturing and analyzing 3D point clouds (e.g., sampled by terrestrial or aerial laser scanning) or by photogrammetric approaches. To achieve a high percentage of geometrically and topologically correct 3D building models, digital terrain surfaces and 2D footprint polygons are required by automated building reconstruction tools such as BREC.