Integrated Spatial Uncertainty Visualization using Off-screen Aggregation

Abstract

Visualization of spatial data uncertainties is crucial to the data understanding and exploration process. Scientific measurements, numerical simulations, and user generated content are error prone sources that gravely influence data reliability. When exploring large spatial datasets, we face two main challenges: data and uncertainty are two different sets which need to be integrated into one visualization, and we often lose the contextual overview when zooming or filtering to see details. In this paper, we present an extrinsic uncertainty visualization as well as an off-screen technique which integrates the uncertainty representation and enables the user to perceive data context and topology in the analysis process. We show the applicability and usefulness of our approach in a use case.