Symbology - ArcGIS
(copied from Learning ArcGIS9 Virtual Campus course)
Feature symbology greatly affects how readers interpret a map. The right symbols can mean the difference between confusion and clarity—between conveying a little information or a lot. The right symbols can also reveal patterns in your data that may not be obvious. Listed below are key points you should remember about symbolizing maps.
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Point, line, and polygon symbols have properties that you can set, such as shape, size, color, outline, and width. |
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Effective symbols take advantage of common associations that people make, such as blue for water or a larger dot for a more populated city. |
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Symbolizing features by attributes allows you to communicate more information. |
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You can symbolize features to show categories (names, types, ranks) or quantities (counts, amounts, rates, measurements). |
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Quantity attributes can be classified using different methods, including natural breaks (the default), quantile, equal interval, and manual. |
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Which classification scheme you choose depends on the purpose of the map and the characteristics of the data—there is no one "correct" choice. |
Review questions
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When you label map features in ArcMap, where does the text come from?
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When classifying a layer, what rule of thumb can you use to decide how many classes to use?
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Name two things you can learn from a classification histogram.
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Name two ways that density can be symbolized on a map.
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In ArcMap, label text comes from a feature attribute or you can manually add your own text to a map.
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When classifying data, fewer classes is generally better.
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You can learn many things from a classification histogram. Your answer could have been any of the following:
How attribute values are distributed across the whole range of values
The minimum attribute value
The maximum attribute value
The number of classes
The class breaks (maximum value for each class)
The size of classes relative to one another
The number of features that have a particular attribute value.
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You can show density on a map by normalizing an attribute by area and using graduated color or graduated size symbols; you can also create a dot density map.
Key terms
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