Data points and axes improve accuracy of terrain analysis.
While a smooth terrain creates a 3D heat map of data able to aggregate and fuse large numbers of data points, in some circumstances the smoothing and interpolation algorithm may set the terrain surface away from the actual data points. It is, however, possible to verify the terrain accuracy by superimposing data point highlights over its surface, e.g. see this view of the total numbers of traffic accidents in the Melbourne CBD area, Australia.
Another function of glowing data points is to provide visual enhancement to some dull terrains where the colour shift is not able to extract any distinct data features. This could be the case of data sets where all values are in a very similar range. For example, consider this top view of the CBD.
As evident from the following screen shot, other terrain layouts, such as cylindrical, granular and smooth peaks, do not suffer from the heat map malady.
In fact, granular terrains provide better clarity to sparse data, especially when the underlying geographical features need to be visible.
In such examples a simple granular view of data peaks, with a backdrop of variable axes greatly improve the terrain readability.
In a similar fashion, smooth terrains with axes and white divisors over the terrain surface assist the accuracy of important observations.
For more information see the Immersive and Collaborative Analytics.
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