Designing and Choosing symbols 159
symBolIzIng AReAl dAtA
Representing qualitative data with polygons is straightforward. The variables most
often employed are hue, pattern, and orientation. Different hues represent different
nominal categories, such as vegetation types, or land-use categories on color presen-
tations. The main concern here is that there be logic to the choice of hues, as we saw
in Chapter 4.
If color is not an option, the mapmaker must rely on pattern for different catego-
ries. Shades of gray cannot be used because these imply differences in amount. GIS
and illustration software have a number of stock patterns available and some permit
the user to design his or her own. These patterns may be pictorial or abstract, made
up of varying line patterns and orientations.
Representing Uncertainty and overlap
Phenomena in the real world are not always clear-cut even though they appear so on
many maps. There are many instances of uncertainty, overlap, and even simultane-
ous occupation of phenomena. Two examples are language and religion. One method
that has been used is interdigitation, which shows a blended area; a second is overlap-
ping patterns that form a third pattern; or a third is transparent colors that blend into
one another (see Figure 7.8). Lines at boundaries can also be portrayed as fuzzy or
blurred. The method used depends on the capabilities of the software used.
symBolIzIng VolUme dAtA
Many geographic phenomena can be thought of as volumes. If a phenomenon occurs
over an area rather than at a point or along a line, and the data have magnitude, then
the data values may be thought of as having height and the phenomenon as three-
dimensional. For example, land surface can be visualized as a volume whose three
dimensions are latitude, longitude, and elevation above sea level for each point.
For other kinds of data, such as population, rainfall, or housing values, the vol-
ume cannot be seen, but we can conceive of a three-dimensional surface with hills
and valleys of population, rainfall, or housing values. This imaginary three-dimen-
sional surface is called a
statistical surface (Figure 8.17). The concept of a statistical
surface is especially useful in visualizing the nature of statistical distributions and in
symbolizing those distributions. If the coordinate system of the statistical surface is
represented graphically, the locational coordinates are on the
x and
y axes, and the
value
is represented along the z axis
and is often called the z-value (Figure 8.18).
If a phenomenon is found everywhere within the mapping area, such as tempera-
ture, that is, it is continuous, the surface is smooth and undulating. If there are sharp
breaks or areas with an absence of the phenomenon, that is, discontinuous, such as
population,
the surface is step-like, made up of a series of cliffs and plateaus.
The statistical surface may be symbolized with
either area or line symbols,
depending on the nature of the surface, the way in which the data are gathered, and
the aspect of the surface that is of greatest interest.
