Path: utzoo!mnetor!uunet!tektronix!zeus!bobr From: bobr@zeus.TEK.COM (Robert Reed) Newsgroups: comp.graphics Subject: Re: Diplaying data... Message-ID: <3241@zeus.TEK.COM> Date: 11 Mar 88 20:22:39 GMT References: <4007@batcomputer.tn.cornell.edu> Reply-To: bobr@zeus.UUCP (Robert Reed) Organization: CAE Systems Division, Tektronix Inc., Beaverton OR Lines: 39 In article <4007@batcomputer.tn.cornell.edu> irizarry@tcgould.tn.cornell.edu (Gil Irizarry) writes: Suppose I have a bunch of data for groundwater on a certain planet (say Mars). Say the data consists of two numbers for every square meter of ground, on number representing concentration of the water, and the other representing the depth at which the water is found. What is the best way to display this data? Depends. Do you need to be able to see surface relief? Is there only one concentration/depth pair per geographic position? What sort of continuity exists in the data? (Are adjacent values of concentration more likely to be the same than depth?) What is the resolution of your display medium? The first approach which occurred to me was to use hue and saturation to represent concentration and depth. This would leave intensity available to show relief (by shadow casting or whatever), so that you could more easily connect moisture features with land features. The best assignment of hue and saturation depends on the data. Adjacent hue changes are much more visible than adjacent saturation changes, so hue would be better for highlighting the variance of a subtly changing parameter. Using all three axes of the color space requires adequate resolution to differentiate. If depth is lacking (like 8 bits per pixel rather than 24), the subtle changes in intensity and saturation will be lost in the quantization noise. If your data does include multiple points per location, it will be difficult to avoid muddiness in a two dimensional projection. Perhaps a series of sectional plots arranged by depth might be a better solution. If you have a graphics system of sufficient performance, providing an interactive fly-through of the 3-D data may be advantageous. Individual depths and locations would provide the 3-D positioning, and hue or intensity could be used for concentration. Using semiopaque voxels would allow the investigator to grasp the shape of the moisture concentrations. There are lots of alternatives, some of which I've only alluded in this note. I hope some of this helps. -- Robert Reed, Tektronix CAE Systems Division, bobr@zeus.TEK