Marine environmental datasets are obtained from observations and simulations and are diverse, complex, and heterogeneous. However, oceanographers often settle for mere statistics displayed in 2D time-series graphs or fragmentary figures. Such piecemeal analysis of oceanic processes and marine phenomena can’t capture the ocean’s complex dynamics and relationships.
Instead, we need dimensionally advanced statistical and scientific visual analysis of long-term accumulated data. The first challenge for such analysis is handling the data, owing to their enormous size and varied formats. The next challenge is fusing the information for knowledge discovery. Finally, developing effective visualizations that tap into humans’ visual-reasoning ability is key to successful analysis.
Thus we’ve developed a visual analytics (VA) tool with an embedded GIS (geographic information system) for location-based oceanographic data. We find that it’s intuitive to employ geographic grids that integrate marine environmental data, geographic information, and multidimensional spatiotemporal distribution.
These observation stations consist of observatories, buoys, moored equipment, and devices for water and geological sampling.
Water quality distribution charts depicting chemical oxygen demand (COD), using a dasymetric map, for August 2003 (top), September 2005 (middle), and May 2009 (bottom). We divide water quality into six grades, with grade VI being the worst.
Zooplankton distribution charts using a proportional-symbol map with pie charts, for July 2007 (top), July 2008 (middle), and September 2009 (bottom). Zooplankton populations appeared to increase after the dyke’s completion. However, species diversity significantly decreased; only the copepod population increased.