The guts of making a decent map! Symbology

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Symbology
The guts of
making a decent
map!
1
The module has….
• Lots of detail on just HOW to
symbolize your data mod 2
• BUT before you start wielding the
electronic paint brush you need to
know what you want to communicate
to whom.
• And that is the most difficult part of
making a map!
2
Damn…
3
About what?
• Colors – themselves and re others
• Symbols – random or standard
• Classifications --
4
According to Brewer…
• “Many Factors affect the colors you
choose.
• The perceptual structuring of the
colors should correspond with the
logical structuring in the data…
• Make sure the character and
organization of the colors match the
logic of your data…”1
1
Cynthia Brewer, Designing better maps. ESRI Press
5
“When choosing map colors…
• You should not be overly concerned about which colors
your audience likes.
• Everyone has an opinion
• Regardless of context , it seems that most people like
blue and do not like yellow…
• People like maps with many colors so focus your
attention on
– presenting your data clearly and
– don’t worry about whether you have picked everyone’s favorite
colors.”1
1 Cynthia Brewer, Designing better maps. ESRI Press
6
BUT…
• “When choosing map colors, you should not be
overly concerned about which colors your
audience likes. Everyone has an opinion …
Regardless of context , it seems that most
people like blue and do not like yellow… People
like maps with many colors so focus your
attention on presenting your data clearly and
don’t worry about whether you have picked
everyone’s favorite colors.”1
1
Cynthia Brewer, Designing better maps. ESRI Press 7
And…
• “When choosing map colors, you should not be
overly concerned about which colors your
audience likes. Everyone has an opinion …
Regardless of context , it seems that most
people like blue and do not like yellow… People
like maps with many colors so focus your
attention on presenting your data clearly and
don’t worry about whether you have picked
everyone’s favorite colors.”1
1
Cynthia Brewer, Designing better maps. ESRI Press 8
However
• Usually students don’t have too much
trouble with making decent maps with
reasonable symbolizations
• It comes naturally
• But you do need to keep some things
straight when working with
classifications of data
• And you usually have to classify
9
• Nominal
Data Types
– are categorical data where the order of the
categories is arbitrary
• Ordinal
– categorical data where there is a logical
ordering to the categories
• Interval
– continuous data where differences are
interpretable, but where there is no "natural"
zero
• Ratio
– continuous data where both differences and
ratios are interpretable
10
ESRI talks more about…
• Quantitative data is numerical
–
–
–
–
Ratio, Interval, ordinal data types
continuous data like elevation (interval)
depth-to-bedrock (ratio)
Usually contrasting color between classes
• Qualitative data is not necessarily numeric
– Nominal data – soil type, road classification
– Limit of 10-12 colors (classes) and you want
contrast – 5 is better yet
– Usually smooth transitions of color between
classes
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Exercise 2
• Lots of symbols for points, lines, &
polys
• Labeling features –
– Dynamic and Interactive
– Annotation
• Symbolizing based on attribute
– Category
– Quantity
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Quantity
• Graduated colors
– Color ramps – which work best?
• Graduated Symbols (classification)
• Editing legend entries for the TOC
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Classification
• How many classes
• What method to use for placing the
values into classes
• What kind of Symbology to use (e.g.,
graduated colors or graduated
symbols)
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Maps - Categorical
• Categorical symbolization is typically
used for NOMINAL data
– Quite often similar colors will be used
for related categories
– You want the user to be able to discern
the categories
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Classifications
• Natural breaks : finds groupings
inherent in the data. Default
• Equal interval : interval between each
class is the same.
• Quantile : each class contains an
equal number of values (features).
• Manual : you decide
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Quantitative maps
• Displays quantitative data – interval
or ratio data and even ordinal data
• A graduated ramp or palette is used
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