Are Current Scientific Visualization and Virtual Reality Techniques Capable to Represent Real Soil-Landscapes?

Real soil-landscapes are complex consisting of an inextricable mix of patterns and noise varying continuously in the space-time continuum. Soils and parent material show gradual variations in the horizontal and vertical planes forming 3D bodies that are commonly anisotropic. There is no real beginning and end point in soil-landscapes because environmental conditions are dynamically changed through water flow, biogeochemical processes, and human activities. The strengths of soil-landscape modeling lies in hypothesis testing, understanding causal linkages between environmental factors, and their interrelationships within a spatial and temporal explicit context. To develop virtual soil-landscape models entails: (i) conceptualization, i.e. defining the model framework (e.g. finite space elements) (ii) reconstruction, i.e. describing and quantifying underlying conditions and behavior and (iii) scientific visualization (SciVis), i.e. abstracting real soil-landscapes into a format that we can comprehend and that helps us to understand the complexity of soil-landscapes. The primary objective in data visualization is to gain insight into an information space by mapping data onto graphical primitives. Capabilities and limitations of SciVis and virtual reality techniques are discussed in this chapter. Only recently 3D soillandscape models have been emerging. We present a case study that translated the spatiotemporal water table dynamics of a flatwood soil-landscape in Florida into a virtual domain using a geostatistical method to reconstruct the soil-landscape and Virtual Reality Modeling Language enhanced with External Authoring Interface for visualization and implementation of interactive functions. Just as maps can visually enhance the spatial understanding of phenomena, interactive spatio-temporal applications can enhance our understanding of complex environmental systems and the underlying transport processes driving soil and water quality. 43.