Multi-resolution visualization of geographic network traffic

Flow visualization techniques are vastly used to visualize scientific data among many fields including meteorology, computational fluid dynamics, medical visualization and aerodynamics. In this thesis, we employ flow visualization techniques in conjunction with conventional network visualization methods to represent geographic network traffic data. The proposed visualization system integrates two visualization techniques, flow visualization and node-link diagram, in a level of detail framework. While flow visualization emphasizes general trends, node-link diagram visualization concentrates on the detailed analysis of the data. Usability studies are performed to evaluate the success of our approach

Localized flow, particle tracing, and topological separation analysis for flow visualization

Since the very beginning of the development of computers they have been used to accelerate the knowledge gain in science and research. Today they are a core part of most research facilities. Especially in natural and technical sciences they are used to simulate processes that would be hard to observe in real world experiments. Together with measurements from such experiments, simulations produce huge amounts of data that have to be analyzed by researchers to gain new insights and develop their field of science

Spotting Structure in Complex Time Dependent Flow

Analysing structure in complex time dependent flow fields is a challenging problem. Spot noise is a technique which utilizes texture for the visualization of flow fields. In this paper, two extensions of spot noise are discussed. These extensions allow spot noise to be used for very detailed analysis of time dependent flow fields. Two applications are discussed: a large data set resulting from a direct numerical simulation of turbulence and a data set resulting from a global climate data