Keeping pace with technology through the development of an intuitive data fusion, management, analysis & visualization software solution

A significant challenge facing researchers is the bridging of domains between the natural and physical sciences through the integration, analysis & visualization of multivariate environmental data from a variety of sources. Typically the temporal, visual and analytical components are not well handled within a single software application or by existing tools, and the final products are often difficult to share with collaborating researchers and managers. To address these issues, Myriax has launched Eonfusion; the next generation of geospatial analysis software which provides a state-of-the-art 4D-analysis environment that is intuitive and readily extensible. The software significantly enhances the ease with which scientists can integrate diverse data types (raster, vector and media) and share methods across disciplines. The powerful 4D-visualization interface also incorporates a range of analysis and plotting tools as well as a time-navigation capability that allow users to explore the temporal evolution of spatial structure and resolved relationships. Its revolutionary fusion capability allows data at different temporal or spatial scales to be reconciled, attributes merged and topological relationships identified. The software is customizable, through an integrated coding environment for algorithm implementation and an application programming interface (API), to facilitating the development of modules. It is ideal for both undertaking complex analyses and communicating syntheses. This paper introduces the concepts behind fusion of irregular vector data in Eonfusion. Multiple data sets, including modeled and sampled data, can be fused into a single set with shared coordinates, enabling the discovery of topological relationships between coincident data items. These relationships also allow data attributes to be directly compared and transferred between data sets. A corresponding process also allows raster data attributes to be directly compared with vector data a- ttributes through a raster mapping form of fusion. Both the raster and vector data sets can be visualized together, and the attribute transfer results displayed and used for further analysis. Vector data is introduced to the application as sets of spatial features (e.g. points, lines or polygons). Attributes may vary from vertex to vertex across a spatial feature (vertex attributes, e.g. x, y, z, t), or may be constant across a feature (feature attributes). Fusion typically takes place in a space defined by a subset of common vertex attributes. The implementation is sufficiently general to use any such collection of attributes, for example temperature or mean volume backscatter. A simple yet powerful example is the fusion of video data with camera trajectory data for ground truthing acoustic data. This architecture enables user-positioned "probes" in scenes on the camera trajectory line to locate the corresponding video frames. Along track acoustic integration data can also be fused with the trajectory data, providing tools for seabed classification or combined net/acoustic studies. This example represents the simple application of a powerful set of tools for oceanographic and ecological studies. Eonfusion was developed with the support of leading researchers around the world to meet the demands of the latest marine research tools, technology and methodology. Eonfusion moves the technology horizon far beyond simultaneous 4D visualization of coincident data, to the elegant integration of data via fusion. The ability to fuse data from multiple sources in a versatile 4-dimensional visualization environment provides new opportunities for observation insights into marine ecosystems. It will ultimately yield the analysis methodologies of the future.