Explorative coastal oceanographic visual analytics:oceans of data
George, Richard Llwyd Simon Frost
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The widely acknowledged challenge to data analysis and understanding, resultingfrom the exponential increase in volumes of data generated by increasinglycomplex modelling and sampling systems, is a problem experienced by many researchers,including ocean scientists. The thesis explores a visualization and visualanalytics solution for predictive studies of coastal shelf and estuarine modelled,hydrodynamics undertaken to understand sea level rise, as a contribution to widerclimate change studies, and to underpin coastal zone planning, flood prevention andextreme event management.But these studies are complex and require numerous simulations of estuarinehydrodynamics, generating extremely large datasets of multi-field data. This typeof data is acknowledged as difficult to visualize and analyse, as its numerous attributespresent significant computational challenges, and ideally require a widerange of approaches to provide the necessary insight. These challenges are not easilyovercome with the current visualization and analysis methodologies employedby coastal shelf hydrodynamic researchers, who use several software systems togenerate graphs, each taking considerable time to operate, thus it is difficult to exploredifferent scenarios and explore the data interactively and visually.The thesis, therefore, develops novel visualization and visual analytics techniquesto help researchers overcome the limitations of existing methods (for examplein understanding key tidal components); analyse data in a timely manner andexplore different scenarios. There were a number of challenges to this: the sizeof the data, resulting in lengthy computing time, also many data values becomingplotted on one pixel (overplotting).