Vizualizing Large Spatial Datasets in Interactive Maps

This paper addresses the problem of reducing cluttering in interactive maps. It presents a new technique for visualizing large spatial datasets using hierarchical aggregation. The technique creates a hierarchical clustering tree, which is subsequently used to extract clusters that can be displayed at a given scale without cluttering the map. Voronoi polygons are used as aggregation symbols to represent the clusters. This technique retains hierarchical relationships between data items at different scales. In addition, aggregation symbols do not overlap, and their sizes and the number of points that they cover is controlled by the same parameter. The scalability analysis shows that the method can effectively be used with datasets of up to 1000 items.