Lecture Note
Map Design: Symbolization and Classification
-
University:
California State University, Northridge -
Course:
GEOG 206/L | Introduction to Geographical Information Science and Lab Academic year:
2009
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Views:
42
Pages:
19
Author:
Pompanin8za
Lecture 5
MAP DESIGN: PART I
Symbolization and
Classification
A picture is worth a thousand words… Outline
Symbolization
Types of Maps
Classifying Features
Visualization Considerations Symbolization
Symbolization is the process of assigning colors,
markers, sizes, widths, angles, transparency and
other properties to features. Symbolization
Visual resources cartographers can use to symbolize
information on a map.
3 Types of Symbols:
Point
Line
Polygon
Options for Symbolization: Color
Three "dimensions" of color: hue, lightness, and saturation.
Hue: Color can be described by its wavelength; red at one
end of the visible spectrum, violet on the other. A change in
wavelength of visible light is manifested by a change in hue.
"Red," "green," and "violet" are all hues.
Lightness: Color can also be described by its shade, or its
degree of lightness. a.k.a "value," or "brightness.“
Saturation: A third dimension of color describes how "pure"
the color is. If a color is made up of only one hue, it is called
"saturated." However, if you imagine mixing together many
hues, the result is a desaturated color. Symbolizing Values
Nominal:
Values are discrete (that
is, mutually exclusive) and
are classed according to
type or quality. For
example, a line could
represent either a road or
river, and a land use
polygon could be
residential, commercial, or
a recreational area.
Ordinal:
Ordinal values
determine position.
These measurements
show place, such as
first, second, and third,
but they do not establish
magnitude or relative
proportions. It is not
possible to measure the
differences between
ordinal data.
Ratio:
The values from the ratio
measurement system are derived
relative to a fixed zero point on a
linear scale. Mathematical
operations can be used on these
values with predictable and
meaningful results. Examples are
age and distance. Types of Maps
The form of your data dictates the form (type) of the map.
General Reference Maps
Graduated Symbol Maps (Proportional Symbol Maps)
Chloropleth Maps
Isopleth Maps
Area Qualitative Maps
Dot Density Maps General Reference Maps
Generalized map
Examples: world maps, road maps, atlas maps, etc. Graduated Symbol Maps
(Proportional Symbol Maps)
The proportional size of symbols represents the value of
the attribute.
These maps scale icons (most often circles) according to
the data they represent.
Proportional symbol maps are not dependent on the size of
the spatial unit associated with its attribute. Chloropleth Maps
Numerical data is classified into categories and the categories are
shaded. Polygons are often based on politically defined features.
This will yield a display that puts visual emphasis on the largest area
units of the map.
Example: Indicate differences in population. Isopleth Maps
The concentration of an attribute is represented by connecting
points of identical values to create lines.
Ideal for continuous area data (i.e. data exists at every point) that
varies smoothly over space. It does not change abruptly at any
point (like tax rates do as you cross into another political zone).
Examples: Temperature and Elevation Area Qualitative Maps
Shows the distribution of pre-existing geographic
classes (forest types, soils, land-use, vegetation,
etc.) Dot Density Maps
Dot maps create a visual impression of density by placing a
dot or some other symbol in the approximate location of one or
more instances of the variable being mapped.
Used to represent themes that vary smoothly over space but
are discrete.
Examples: livestock farms, utility poles, and population
distribution in a region. Classifying Features
Groups attributes into classes to help discern patterns.
Make choices about not only how many different classes that the data
should be categorized into, but what the value ranges of those
classes should be. A slight adjustment of the "breaks" in the value
ranges of ordered data, for example, might alter the map significantly
and reveal trends that were not detected previously (or are not in fact
there).
You can define your own classes OR Use one of the standard
methods:
3 Frequently Used Standard Methods:
– Natural Breaks
– Equal Interval
– Quantile Natural Breaks
(Jenks Optimization)
Default method in ArcGIS (Also called
“Jenks Optimization” classification)
Identifies natural groupings of values that
are inherent in your data.
The features are divided into classes
whose boundaries are set where there are
relatively big jumps in the data values.
This method works well with data that is
not evenly distributed and not heavily
skewed toward one end of the distribution. Equal Interval
This method is like a ruler: the interval
between each class is the same. For
example, you might have classes with
intervals of 10 percent (1-10%, 11-20%,
21-30%, etc.)
This method sets the value ranges in
each category equal in size. The entire
range of data values (max - min) is
divided equally into however many
categories have been chosen.
This option is useful to highlight changes
in the extremes of data values. It is
probably best applied to continuously
distributed data ranges such as
percentages or temperature. Quantile
Each class contains an equal number of
values.
For example, you might have 100 counties
grouped into 5 classes—each class would
contain 20 counties regardless of the values of
the attributes.
Misleading Legends: In order to have an equal
number of features in each class, features with
greatly different values can be placed in a
single class. One solution is to manually
increase the number of classes – this may
separate dissimilar values.
Because the intervals are generally wider at
the extremes, this option is useful to highlight
changes in the middle values of the
distribution. Map Visualization Considerations
A vital task in creating effective graphics for visually relating ideas is
the filtering of vast fields of data into units that are simple enough to
be understood quickly and intuitively but detailed enough to convey
useful information
Effective interpretation of the results of your analysis -- both by you
and by others -- depends to a large extent on the design of the onscreen display.
A slight alteration of the color scheme or classification method of a
map, for example, might produce two different graphics that appear
to tell two very different stories -- even though they represent the
exact same data. Next Week…
Map Design: Part II
– Map Layouts
– Graphics
– Text, Annotation and Labels.
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