Visualization Fundamentals
This section covers the foundational concepts for understanding how data is visualized in Earth Volumetric Studio.
As defined above, our discussion of environmental data will be limited to data that includes spatial information. When spatial data is collected with
Many methods of environmental data visualization require mapping (interpolation and/or extrapolation) of sparse measured data onto some type of grid.
Although there is great value in directly visualizing measured data; it does have many limitations. Without mapping sparse measured data to a grid, co
Rectilinear (a.k.a. uniform) grids are among the simplest type of grid. The grid axes are parallel to the coordinate axes and the cells are always rec
The convex hull of a set of points in two-dimensional space is the smallest convex area containing the set. In the x-y plane, the convex hull can be v
Triangular networks are defined as grids of triangle or tetrahedron cells where all of the nodes in the grid are exclusively those in the sample data.
Spatial interpolation methods are used to estimate measured data to the nodes in grids that do not coincide with measured points. The spatial interpolation methods differ in their assumptions, methodologies, complexity, and deterministic or stochastic nature. Inverse Distance Weighted Inverse distance weighted averaging (IDWA) is a deterministic estimation method where values at grid nodes are determined by a linear combination of values at known sampled points. IDWA makes the assumption that values closer to the grid nodes are more representative of the value to be estimated than samples further away. Weights change according to the linear distance of the samples from the grid nodes. The spatial arrangement of the samples does not affect the weights. IDWA has seen extensive implementation in the mining industry due to its ease of use. IDWA has also been shown to work well with noisy data. The choice of power parameter in IDWA can significantly affect the interpolation results. As the power parameter increases, IDWA approaches the nearest neighbor interpolation method where the interpolated value simply takes on the value of the closest sample point. Optimal inverse distance weighting is a form of IDWA where the power parameter is chosen on the basis of minimum mean absolute error.
The choice of surface rendering technique has a dramatic impact on model visualizations. Figure 1.25 is a dramatization that incorporates many common
The choice of color(s) to be used in a visualization affects the scientific utility of the visualization and has a large psychological impact on the a
The following provides hints and tips for obtaining optimal quality when printing. This assumes you are using a color printer, but it is important to
Once the model of the site has been created, visually communicating the information about that site generally requires subsetting the model. Subsettin