In this thesis a new method to show the generalization process is proposed and assessed - parallel step assignment. It investigates the feasibility and applicability of this method with respect to three proposed generalization approaches and tries to evaluate the possibility of vario-scale map representation. First, the generalization sequence is created for each of these approaches. It is then processed with a greedy algorithm in order to decide which generalization operations can be shown at the same time. After that, two aspects are assessed: the generalization of the map quality and the assignment itself. The results show that the method is feasible for the vario-scale maps, however, the proposed generalization techniques need to be improved and none of them can be considered as suitable at its current state of development. Nevertheless, the main aspect of the interaction is significantly improved and the solution can be considered feasible. At last, based on various observations and conclusions from the project, some ideas for future work are proposed together with an evaluation of the chosen methodology with underlined drawbacks.

With the rapid growth in point cloud acquisition technologies the recent years we have the ability to measure large quantities of 3D points of significantly detailed and geometrically composite scenes such as urban environments. This advantage can be exploited and used for direct analysis on point clouds. A direct point cloud analysis has several advantages over for example 3D surface reconstruction, such as the end result having more details and the computation being less expensive. In order to make a point cloud representation a suitable alternative for other types of 3D city models, they need to be semantically enriched, resulting in a rich point cloud. One element of this enrichment is the detection of objects, such as windows. Extracting these from facades is specifically what this research revolves around, which can be done by taking advantage of the fact that they show up as holes, since lasers of the point cloud scanner do not properly reflect on them. Two different general approaches are taken to detect windows in a by mobile laser scanner obtained point cloud of Noordereiland, Rotterdam, The Netherlands.