![]() ![]() Thus, real-world spatial patterns may not conform to the regional unit symbolized. For example, a city may include neighborhoods of low, moderate, and high family income, but be colored with one constant "moderate" color. However, it can result in a number of issues, generally due to the fact that the constant color applied to each aggregation district makes it look homogeneous, masking an unknown degree of variation of the variable within the district. A prime example of this would be elections, in which the vote total for each district determines its elected representative. Using pre-defined aggregation regions has a number of advantages, including: easier compilation and mapping of the variable (especially in the age of GIS and the Internet with its many sources of data), recognizability of the districts, and the applicability of the information to further inquiry and policy tied to the individual districts. 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. That is, boundaries of the colored districts may or may not coincide with the location of changes in the geographic distribution being studied. ![]() In a choropleth map, the districts are usually previously defined entities such as governmental or administrative units (e.g., counties, provinces, countries), or districts created specifically for statistical aggregation (e.g., census tracts), and thus have no expectation of correlation with the geography of the variable. In this choropleth map, the districts are countries, the variable is spatially intensive (a mean allotment) with a modified geometric progression classification, and a spectral divergent color scheme is used. In the other view, which may be called "variable dominant", the focus is on the variable as a geographic phenomenon (say, the Latino population), with a real-world distribution, and the partitioning of it into districts is merely a convenient measurement technique. There are two common conceptual models of how these interact in a choropleth map: in one view, which may be called "district dominant", the districts (often existing governmental units) are the focus, in which a variety of attributes are collected, including the variable being mapped. Structure Ī choropleth map brings together two datasets: spatial data representing a partition of geographic space into distinct districts, and statistical data representing a variable aggregated within each district. Also in 1938, Glenn Trewartha reintroduced them as "ratio maps", but this term did not survive. The term "choropleth map" was introduced in 1938 by the geographer John Kirtland Wright, and was in common usage among cartographers by the 1940s. When Chromolithography became widely available after 1850, color was increasingly added to choropleth maps. : 158 Choropleth maps quickly gained popularity in several countries due to the increasing availability of demographic data compiled from national Censuses, starting with a series of choropleth maps published in the official reports of the 1841 Census of Ireland. More " cartes teintées" ("tinted maps") were soon produced in France to visualize other "moral statistics" on education, disease, crime, and living conditions. ![]() ![]() The earliest known choropleth map was created in 1826 by Baron Pierre Charles Dupin, depicting the availability of basic education in France by department. History Dupin's 1826 map of literacy in France 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. A heat map or isarithmic map is similar but uses regions drawn according to the pattern of the variable, rather than the a priori geographic areas of choropleth maps. Ĭhoropleth maps provide an easy way to visualize how a variable varies across a geographic area or show the level of variability within a region. The selected districts are local government areas, the variable is spatially intensive (a proportion) which is unclassed, and a part-spectral sequential color scheme is used.Ī choropleth map (from Greek χῶρος (choros) 'area/region', and πλῆθος (plethos) '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. Type of data visualization for geographic regionsĪ choropleth map that visualizes the fraction of Australians that identified as Anglican at the 2011 census. ![]()
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