Nearly one third of the world's population live in coastal areas, and ten of the fifteen most populous cities in the world lie on a coast. Inhabitants of the Low Elevation Coastal Zone (LECZ) - defined as the contiguous area along the coast that is less than 10 meters above sea level - make up 10% of the world's population and 13% of the world's urban population. Sea level rise, coastal inundation and associated shoreline retreat have emerged as one of the primary threats to these populations and the resources located near the coastal fringe.
In order to assess the potential impacts in these zones, researchers at several universities are using Eonfusion to model and predict the effects of sea level rise and hopefully prevent damage to populations and resources in these low-lying areas. Combining LiDAR data from the Antarctic Climate & Ecosystems Cooperative Research Centre (ACE CRC) with sea level rise scenarios published by the Intergovernmental Panel on Climate Change (IPCC) and other research on the geomorphic structure of the local area, researchers have been able to develop a model for coastal inundation and damage in these low-lying areas.
To date the main challenge in the development of such a model has been that there has not been any single software application with the capability to combine the various types of data, model dynamic systems and multiple scenarios and then produce 4D visualizations of the results for further study or communication to stakeholders. This has forced researchers to cobble together methods and analysis in a series of steps using a number of different software applications and then produce flat 2D graphs of their results.
Eonfusion enables the complex modeling and visualization of the coastal zone and can easily convey complex changes in both the sea level and land surface through time. In a small study in southern Tasmania, researchers have used two publically available datasets in a first pass assessment of vulnerable areas.
Starting with a detailed LiDAR data set from ACE CRC, Eonfusion was used to process the data into a 3D surface representing the ground. The surface was then color coded for height above mean sea level and overlaid with an aerial photo to provide a visual spatial context. Sea level rise data was converted into a time series of surfaces which represented three possible IPCC sea level rise scenarios and were also integrated with the model. This basic model enabled a rapid analysis and visualization of the sea level rise scenarios and allowed users to easily visualize storm surge events of any magnitude.
Figure 1: Storm Surge at Kingston, Australia was modeled in Eonfusion. An aerial photo was overlaid on the topology to provide visual context.
The model was then enhanced to predict shoreline retreat. Utilizing knowledge of the local geology, a 3D model of the terrain and its vulnerability to erosion was fused with the original model. The Bruun Model - which states that for every 1 cm of sea level rise an unconsolidated shoreline will retreat by 50 to 100 cm - was implemented in Eonfusion's Expression Evaluator and used to calculate shoreline retreat in 10 year intervals out to the year 2120.
The result were animations of the predicted rise in seal level combined with shoreline retreat over this period. To view two animation examples captured directly from Eonfusion, follow the links at the end of this article.
Figure 2: Eonfusion is used to predict the retreat of the shoreline in the year 2030 based on IPCC's sea level rise predictions. White areas indicate regions where shoreline is eroded.
Figure 3: Eonfusion is used to predict the extent of high tides in the Year 2030 based on IPCC's sea level rise predictions. Yellow areas indicate regions where tides will cover the present shoreline.
