Most of the algorithms used for research in mesh simplification and discrete levels of detail (LOD) work well for simplifying single objects with a large number of polygons. For a city-sized collection of simple buildings, using these traditional algorithms could mean the disappearance of an entire residential area in which the buildings tend to be smaller than those in commercial regions. To solve this problem, we developed a mesh-simplification algorithm that incorporates concepts from architecture and city planning. Specifically, we rely on the concept of urban legibility, which segments a city into paths, edges, districts, nodes, and landmarks. If we preserve these elements of legibility during the simplification process, we can maintain the city's image and create urban models that users can understand more effectively. To accomplish this goal, we divide our algorithm into five steps. During preprocessing, it performs hierarchical clustering, cluster merging, model simplification, and hierarchical texturing, at runtime, it employs LOD to select the appropriate models for rendering.