Feature ArticleVisualizing Large Environmental Data Sets in a Global 4D Viewer
By Duke J. Hartman
Ocean and Chemical Engineer
Dr. John C. Anderson
Technical Lead, Advanced Visualization Division
Makai Ocean Engineering Inc.
Having an accurate understanding of physical environmental conditions is essential to all ocean-related industries. Numerical models, informed by sensor data, have been developed for many of these industries to describe and predict the behavior of physical systems. Recently, there has been an exponential increase in the size, quality and complexity of environmental data from surveys, sensors and numerical models.
Models often produce gigabytes or terabytes of data containing multiple variables of interest that can change in both space and time. However, the tools to process and visualize these large environmental data sets have not kept pace with the increase in data generation. Scientists, engineers and executives are facing the fundamental problem of how to efficiently manage and interpret the vast amount of oceanographic, geologic and atmospheric data being collected and modeled. Scientific and oceanographic activities are often limited to using subsets of environmental and sensor data, which increases the possibility of missing critical information. Furthermore, most data are still being presented as sequences of flat 2D images, which is an inefficient and time-consuming method of analyzing data that is inherently 3D and 4D (3D plus time).
Well-known, highly interactive software systems that are used to view large amounts of terrain and image data, such as Google Earth, Microsoft Virtual Earth and the leading GIS software, are not capable of displaying large scientific data sets, such as volumetric (3D) data that changes in time (4D). They are primarily restricted to displaying imagery, terrain and static 3D objects. On the other hand, many existing scientific programs were not designed to easily incorporate georeferenced data such as lidar point clouds, large image files, elevation and bathymetry, and GIS data. These shortcomings in existing data fusion and visualization motivated Makai Ocean Engineering to create a tool called Makai Voyager that could combine and view all relevant scientific data in an interactive global 4D view. The software has applicability in oceanography, marine sciences, offshore oil and geophysical exploration, underwater mining and construction, coastal and environmental engineering, ROV planning and simulation, resource assessment for offshore renewable energy and defense tactical displays.
Specifications for Makai Voyager were established early in the development process five years ago. Main requirements included the ability to visualize imagery, bathymetry, terrain and true volumetric (voxel) data simultaneously in an interactive georeferenced environment; fuse georeferenced terrain and imagery data from different sources with different datum and projections; and render dynamic isosurfaces and full volumes of grids greater than 5123 voxels, including visualization of scalar and vector (e.g., flow) data. The viewer would also be able to visualize large lidar point clouds; incorporate real-time data from remote sensors; visualize and track 3D objects (e.g., vessels, buoys, biological organisms) using GPS; view georeferenced video; query and analyze data with user tools (e.g., distance measurement, cutting planes, slicing, graphing); and operate at more than 15 to 20 frames per second without a loss in data fidelity on a standard PC. The software also needed to be platform independent (Windows, Macintosh or Linux) and expanded into a Web-based system.
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Duke J. Hartman is the marketing manager for Makai Ocean Engineering Inc. He received a bachelor’s degree with honors in mechanical engineering from the University of Hawai’i at Manoa. His interests are 3D and 4D visualization, ocean thermal energy conversion and seawater air conditioning.
Greg Rocheleau is an ocean and chemical engineer for Makai Ocean Engineering Inc. and has been the primary developer for its OTEC plume model. He received a bachelor’s degree in chemical engineering from the University of Colorado at Boulder and a master’s in physical oceanography from the University of Hawai’i at Manoa.
Dr. John C. Anderson is the technical lead of the advanced visualization division of Makai Ocean Engineering Inc. He earned a master’s and Ph.D. in computer science from the University of California, Davis in 2009. He has authored numerous papers on surface extraction, multivariate analysis and query-driven scientific visualization methods.