| The sheer size and complexity of available field-collected and simulated data poses a problem for visual data analysis and can result in the loss of information or proper context. Size and complexity also limit the ability to combine (fuse) multiple datasets and thus interconnected information is rarely explored. A set of interactive 3D visualization and exploration algorithms and techniques was developed to facilitate the analysis of large unstructured earth systems datasets.; A distributed parallel visualization approach for large terrain height fields was developed that uses distributed computing, parallel processing, level-of-detail mesh construction, view-dependent refinement, out-of-core data management, and data compression to provide interactive rendering rates. This approach shows a significant improvement in rendering capacity over existing methods for continuous terrain rendering.; In addition, several applications and case studies are presented. Digital Elevation Models (DEMs) are used in combination with 3D rendering, shading and data augmentation techniques to form easily interpretable and quantitative landscapes. A variety of imagery is texture mapped on top of the DEMs to better define the inter-connectivity between diverse scientific information. Data fusion allows multiple datasets to be combined to establish statistical trends for the studied topographic regions.; The presented distributed parallel visualization approach outperforms existing state-of-the-art methods by an order of magnitude. The presented interactive environment also facilitates the exploration of large-scale seismic datasets and weather data analysis. |
