Paralleling generalization operations to support smooth zooming: case study of merging area objects

When users zoom out on a digital map, some area objects become too tiny to be seen, resulting in visual clutters. To avoid this problem, the relatively unimportant areas should be merged with their neighbors to form larger
areas. In order to provide small and smooth changes so that users can easily keep their contexts, we merge a pair of areas by expanding one over the other and parallel the merging operations. We also require that the area objects involved in paralleled merging operations should not have any common neighbor so that the topology of the map can be easily maintained. The zooming of our map is realized based on the topological area partitioning tree (GAP-tree) and the spacescale cube (SSC). Our case study shows that our method improves the zooming visualization. We consider that paralleling generalization operations is an important step towards continuous map generalization.