Proportional symbol map
Thematic map using symbol size to represent quantitative data.
A proportional symbol map (or proportional point symbol map) is a type of thematic map that uses map symbols varying in size to represent a quantitative variable. Typically, the area of each symbol is mathematically proportional to the variable, though indirect methods such as categorizing symbols as 'small,' 'medium,' and 'large' are also used. This technique is generally applied to point symbols, distinguishing it from cartograms and flow maps, though gray areas exist between these types. For example, a Dorling cartogram replaces area polygons with proportional point symbols, while a linear cartogram distorts line length proportionally to a variable like travel time.
The technique originated with Henry Drury Harness, who produced an 1838 map of railroad traffic in Ireland using proportional widths to show city populations. W. Bone later created range-graded proportional symbol maps for the 1851 British Census, including early legends. Charles Joseph Minard advanced the method by using proportional symbols for regions and incorporating color and statistical charts within point symbols. In the early 20th century, cartographers like Sten de Geer and Guy-Harold Smith experimented with spheres proportional by volume, while Smith and Floyd Stilgenbauer introduced transparency to handle overlapping symbols. Psychophysical research, notably James J. Flannery's 1956 study, applied Stevens's power law to show that map readers underestimate circle area, leading to the Flannery Scaling Adjustment still used today. Since the 1990s, most proportional symbol maps are created with GIS and graphics software, and interactive versions emerged with web mapping platforms after 2005.
Point locations on these maps come from either a point dataset with single coordinates for each feature or an aggregation district dataset where a point represents a predefined region. The variable chosen should be one where size is intuitively interpreted; Jacques Bertin noted that size is the visual variable most directly tied to a single quantitative interpretation.
- field
- Cartography
- known_for
- Using symbol size to represent quantitative variables on thematic maps
Lore & Background
Proportional symbol maps use point symbols, most often circles, whose size varies to represent a quantitative variable, such as a city’s population or total votes cast in an election. The area of each symbol is typically calculated to be mathematically proportional to the variable’s value, though simpler methods like categorizing symbols as small, medium, or large are also employed. The map’s point locations come from two sources: a point dataset with a single coordinate for each feature (e.g., cities or businesses) or an aggregation district dataset where summary statistics from predefined regions are assigned to a representative point. The most effective variables for this technique are those where size is intuitively interpreted, as size is the visual variable most directly tied to a single quantitative meaning. The technique was pioneered by Henry Drury Harness on an 1838 map of Irish railroad traffic that showed city population, and later refined by cartographers such as W. Bone, who produced range-graded maps for the 1851 British Census, and Charles Joseph Minard, who innovated by using proportional symbols for regions and incorporating pie charts within the symbols. Early 20th-century academic cartographers experimented with proportional volume (spheres) and transparency to resolve overlapping symbols. Psychophysical studies, notably James J. Flannery’s 1956 dissertation, revealed that map readers underestimate circle area predictably, leading to the Flannery Scaling Adjustment. Since the 1990s, most proportional symbol maps are created with GIS and graphics software, and modern web mapping platforms enable interactive versions.
Reader's Guide
The proportional symbol map is significant for its intuitive visual encoding: larger symbols are interpreted as representing larger quantities, making it effective for ratio variables such as total population or agricultural production. Flannery found that Stevens's power law applies to circle area perception, leading to the Flannery Scaling Adjustment still used to correct underestimation. Since the early 1990s, GIS and graphics software have dominated production, and since 2005, interactive web maps have been enabled by platforms like Esri ArcGIS Online and CARTO. The technique complements choropleth maps by representing spatially extensive variables that are problematic for choropleths. Variables with negative values or qualitative categories are inappropriate, and high variance in data can cause overcrowding or invisibility of symbols.
Did You Know?
- Since the early 1990s, almost all proportional symbol maps have been created using GIS and graphics software.
Frequently Asked Questions
What is a proportional symbol map?
It is a thematic mapping technique in which the size of a point symbol on the map encodes a numerical value, so bigger symbols stand for bigger quantities. The symbol's area is typically scaled in direct mathematical proportion to the data value being displayed.
How does a proportional symbol map differ from a cartogram or a flow map?
Proportional symbol maps keep every geographic location fixed and only vary the size of discrete point markers, whereas cartograms reshape and resize entire regions to reflect values. Flow maps, in turn, encode quantities through the width of connecting lines rather than through symbol area.
Why are proportional symbol maps still a staple in cartography?
They let a reader compare magnitudes across many locations at a glance while preserving the underlying geography. The technique is simple to produce, easy to interpret, and adaptable to fields ranging from trade statistics to disease incidence.
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