Parallel step assignment for continuous generalization constrained with target map

Abstract

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.