A Linear-Time Algorithm for the Aggregation and Visualization of Big Spatial Point Data

The visualization of spatial data becomes increasingly important in science, business and many other domains. In geography, data often corresponds to a large number of point observations that should be displayed on a constrained screen with limited resolution. This causes, however, a loss of information due to an overloaded and occluded visualization. In this paper we present a new visualization algorithm that avoids this problem by aggregating point data into a set of non-overlapping circles that capture all important information. Our algorithm based on a quadtree computes the circles in linear time with respect to the number of points.