Most geophysical data-sets consist of numerical values, usually collected at regular intervals, on a grid system. These groups of numbers mean something, but staring at them, in the flesh, so to speak, is often not the best way to figure out what that meaning is. Interpreting the data is much easier if you convert those values into some kind of visual image.

Three formats commonly used to display geophysical data are: the X-Y trace, the Dot Density plot and the Grey/Colourscale image.

The introduction to this site shows an example of an X-Y trace. In this display format each row (x-axis) of numbers is plotted as a line graph, with the y-axis showing the numerical values. Then the next row is plotted as a line graph and so on. The height of the y-axis is known as the "vertical plotting scale" e.g. 1cm = 1 unit value, 1cm = 2 unit values etc.

In a dot density plot each data point is represented by a small square. Each square contains black dots, with the number of dots (density) being proportional to the data value. Exactly how many dots are assigned to each square depends on the range of data values and the "plotting levels" selected. For example, say you had a grid where most of the readings were between -1 (yes you can get negative readings - in magnetic data!) and 2, but every so often there were values of, say 200. You could assign dots in direct proportion to the values - so all values between 0 and 1 get one dot, all values between 1 and 2 get two dots and the values of 200 get two hundred dots. Simple - but the resulting plot would look very silly...and how on earth would you plot a negative dot?? Instead what you would do is set plotting levels of 0 to 2. This would ignore all the negative values - they show as blank squares; and treat all the values over 2 as being "over range" - plotting them as solid black squares. Then you would look at all the values between 0 and 2 and divide them up into smaller ranges; e.g. 0-0.2, 0.21-0.4...etc. Then assign a certain number of dots to each range and - Hey Presto! A meaningful dot density plot.

The grey or colourscale image uses the same principle of plotting levels as the "dotty" plot, only in this case negative values can be represented. Again you would look at the range of your data values and decide on a maximum and minimum cut off point. All values above maximum would be assigned one colour or shade of grey (usually black) and all values below minimum given another colour or grey shade (usually white). The values in between max and min cut off points are divided into smaller ranges and each range is assigned a unique colour or shade of grey.