Questions and Answers
What is a proportional symbol map?
A thematic map in which point symbols are scaled in proportion to the attribute value associated with the point symbols.
Do proportional symbol maps convey enumerated or individual information?
What is enumerated information?
Aggregated attribute values of a set of objects within a given region, not a set data point.
What is individual information?
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What visual variables do proportional symbol maps use the most?
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What is a split symbol?
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What is the scaling ratio?
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Match the following approaches to scaling with their descriptions:
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What is Flannery's power function used for?
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What is a graduated symbol map?
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What is the Ebbinghaus Illusion?
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What are some solutions for handling symbol overlap?
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What are the kinds of proportional symbol legends?
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What is the purpose of a linear legend?
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What is a nested legend?
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Study Notes
Proportional Symbol Map
- A thematic map with point symbols scaled according to associated attribute values.
- Origin dates back to at least 1837.
Information Conveyed
- Proportional symbol maps can represent both enumerated and individual information.
- Capable of conveying raw or normalized data.
Enumerated Information
- Represents aggregated values across a defined region, not specific data points.
- Example includes overall hate metrics, like homophobic tweets in specific regions.
Individual Information
- Reflects attribute values of unique locations like state-level presidential election results.
Visual Variables
- Primarily utilizes size for symbol representation.
- Other visual variables can accompany size for enhanced representation.
Split Symbol
- A symbol divided in half to represent two distinct attributes.
Scaling Ratio
- Indicates the relationship between symbol size and corresponding attribute value.
- Essential for the overall accuracy of proportional symbol maps.
Approaches to Scaling
- Mathematical Scaling: Direct correlation between symbol size and attribute value.
- Perceptual Scaling: Adjustments to size based on human visual perception.
- Range Grading: Classifies data into discrete groups with uniform symbol sizes for each group.
Mathematical Scaling
- Direct mapping of symbol size to attribute values for precise representation.
Perceptual Scaling
- Adjusts symbol sizes considering human perceptual tendencies, emphasizing area rather than diameter for accuracy.
Range Grading
- Classifies data into ranges, creating graduated symbol maps where all cases in a range share the same symbol size.
Flannery's Power Function
- An equation designed to correct underestimation issues of circular area symbols.
Graduated Symbol Map
- A proportional symbol map utilizing range grading for data classification.
Ebbinghaus Illusion
- Perception of size influenced by neighboring sizes, affecting how symbols are viewed.
Solutions for Handling Symbol Overlap
- Employ smaller scaling ratios.
- Position larger symbols beneath using contrasting designs.
- Use transparency for overlapping symbols.
- Incorporate proportional rings.
- Utilize symbol anchors like leader lines for clarity.
Kinds of Proportional Symbol Legends
- Linear Legend: Symbols arranged by size with examples from the smallest to largest.
- Nested Legend: Symbols layered atop one another, sharing a common baseline for visual comparison.
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Description
Explore the key concepts of proportional symbol maps with these flashcards. Learn definitions, historical context, and the types of information these maps convey, including enumerated and individual data. Perfect for geography enthusiasts and students alike!
