Choropleth map
A choropleth map (from Ancient Greek χῶρος (khôros) 'area, region' and πλῆθος (plêthos) 'multitude') is a type of statistical thematic map that uses pseudocolor, meaning color corresponding with an aggregate summary of a geographic characteristic within spatial enumeration units, such as population density or per-capita income.
The choropleth is likely the most common type of thematic map because published statistical data (from government or other sources) is generally aggregated into well-known geographic units, such as countries, states, provinces, and counties, and thus they are relatively easy to create using GIS, spreadsheets, or other software tools.
The earliest known choropleth map was created in 1826 by Baron Pierre Charles Dupin, depicting the availability of basic education in France by department.
[4] More "cartes teintées" ("tinted maps") were soon produced in France to visualize other "moral statistics" on education, disease, crime, and living conditions.
[5]: 193 The term "choropleth map" was introduced in 1938 by the geographer John Kirtland Wright, and was in common usage among cartographers by the 1940s.
This is in direct contrast to chorochromatic and isarithmic maps, in which region boundaries are defined by patterns in the geographic distribution of the subject phenomenon.
Although representing specific data in large regions can be misleading, the familiar district shapes can make the map clearer and easier to interpret and remember.
Alternatively, the dasymetric technique can sometimes be employed to refine the region boundaries to more closely match actual changes in the subject phenomenon.
[21][2][22][23] Waldo R. Tobler, in formally introducing the unclassed scheme in 1973, asserted that it was a more accurate depiction of the original data, and stated that the primary argument in favor of classification, that it is more readable, needed to be tested.
[2] The debate and experiments that followed came to the general conclusion that the primary advantage of unclassed choropleth maps, in addition to Tobler's assertion of raw accuracy, was that they allowed readers to see subtle variations in the variable, without leading them to believe that the districts the fell into the same class had identical values.
To avoid confusion, any classification rule should be mutually exclusive and collectively exhaustive, meaning that any possible value falls into exactly one class.
A variety of types of classification rules have been developed for choropleth maps:[26][1]: 87 Because calculated thresholds can often be at precise values that are not easily interpretable by map readers (e.g., $74,326.9734), it is common to create a modified classification rule by rounding threshold values to a similar simple number.
There are a variety of different approaches to this task, but the primary principle is that any order in the variable (e.g., low to high quantitative values) should be reflected in the perceived order of the colors (e.g., light to dark), as this will allow map readers to intuitively make "more vs. less" judgements and see trends and patterns with minimal reference to the legend.
[35] This technique is generally used to visualize the correlation and contrast between two variables hypothesized to be closely related, such as educational attainment and income.
While the general strategy may be intuitive if a color progression is chosen that reflects the proper order, map readers cannot decipher the actual value of each district without a legend.
