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THEMATIC MAPS
A thematic map shows numeric
or character data by colors or
symbols. Data displayed in this
manner is referred to as a theme.
The example shows the numeric
data Pop_1990 (population
1990) displayed as a theme on a
U.S. base map. Notice that
shades of color are used to
represent ranges of numeric
data. This is probably the most
common of the thematic maps the ranged thematic map or
choropleth map.
Note: It’s common to have overlapping
ranges like those shown above; by
convention, “to” means “up to, but not
including.”
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Data Classification: a ranged thematic map uses shades of color to
represent ranges of data values. How are the ranges determined? All
data classification methods revolve around two essential questions,
"How many data ranges should there be?" and, “Where does each
range begin and end?” The answers to these questions are
determined in part by the classification method selected. Some
common data classification methods are:
·
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EQUAL-COUNT
EQUAL RANGES
NATURAL BREAKS
STANDARD DEVIATION
CUSTOM
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The object of Equal-Count
classification is to have an equal
number of cases in each range
(depending on the data table, this
will be approximate only). In the
example, 50 states and the
District Of Columbia could not
be exactly divided by 4 (the
selected number of data ranges).
The result is that the number of
cases in each range varies from
10 to 14. Notice also that the size
of ranges varies greatly - from
about 1.1 million (the smallest
range) to about 24 million (the
largest range).
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The object of Equal Range
classification is to have equalsized ranges. In the example,
every range has an interval of
about 7 million. This method
does not always reflect the data
very well. Notice that the
lowest range has 42 cases and
the highest range has only 1
case, making for a very
"unbalanced" map.
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The object of Natural
Breaks classification is to
create ranges based on
clusters or gaps within the
data itself. This makes for
ranges that reflect the data
very well. Note however,
that the number of cases
per range and the size of
ranges can vary
considerably.
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Standard Deviation classification
creates classes 1 standard
deviation in size around the
average. In the example, the
average value is about 4.9 million
and the standard deviation (SD) is
about 4.5 million. In effect, the
map shows above and below
average values. This type of
classification is popular for
highlighting extremes of data
(either much smaller or much
The 4th range would be -4.1 million to 0.4
bigger than the average). Three
million (2 SD below average), but no data
values fall into this range.
ranges cover all the data values
(range 1 = 1 SD below the
average; range 2 = 1 SD above the
average; range 3 = 2 SD above the
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average).
Custom Ranges you can
customize the map to highlight
particular features of the data
(for example, population
between 1 and 3.7 million) or to
modify ranges defined by one
of the other methods. One of
the features of the custom
method not available to the
other methods is that data
ranges can be discontinuous in other words there can be
gaps between the ranges, as
shown in the example. This is
acceptable, as long care is taken
to ensure that no data values
fall into the gaps.
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General Rules:
•Notice that all of the examples shown
illustrate a convention in thematic mapping
- progressively darker shades represent
progressively higher value ranges.
dark
high
light
low
•On the question of how many ranges to use
- research has shown that between 4 and 6
ranges is the most visually effective.
•Also notice that all of the examples are showing exactly the same
data. Clearly the appearance of a thematic map can vary greatly
depending on the classification method used.
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Which method should be used? Again, in terms of visual
effectiveness, maps look better when there is a balance between
data ranges (about the same number of values in each range) - for
this reason, the Equal Count and Natural Breaks methods are
probably the best choices for most general mapping purposes
(although all these methods are perfectly valid and the actual
choice of classification usually depends on the nature of the data
being displayed and the purpose of the map).
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Color Schemes:
Usually, mixing up different colors does not look good!
A progressively darker shade of one color is usually a better choice.
Uuk!
Better!
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An example data array of 20 values:
2,3,7,9,11,15,17,18,18,20,21,23,27,28,29,31,33,34,34,34
How would this array be divided into 4 equal count, equal
range and natural break classes?
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2,3,7,9,11,15,17,18,18,20,21,23,27,28,29,31,33,34,34,34
4 equal count: 20/4 = 5 values in each class:
2,3,7,9,11 15,17,18,18,20 21,23,27,28,29 31,33,34,34,34
2-11
15-20
21-29
31-34 discontinuous
Or, 2-13,
13-21,
21-30,
30-34 continuous
Equal range: lowest value= 2, highest value = 34, difference =
32. 32/4=8; each range will have an interval of 8:
2-10, 10-18, 18-26, 26-34
Natural break: based on 4 largest gaps in array:
2-3, 7-11, 15-23, 27-34 (all gaps of 4 values).
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