For example, the red–green bi-polar progression described in the section above is likely to cause problems for dichromats. The map user should be able to easily identify the implied magnitude of the hue and match it with the legend.Īdditional considerations include color blindness and various reproduction techniques. Generally five to seven color categories is recommended. When using any of these methods there are two important principles: first is that darker colors are perceived as being higher in magnitude and second is that while there are millions of color variations the human eye is limited to how many colors it can easily distinguish. It is clearly understood by the user and easy to produce in print. this is the best way to portray a magnitude message to the map audience. Although any color may be used, the archetype is from black to white with intervening shades of gray that represent magnitude. Value progression maps are monochromatic. The following are described in detail in Robinson et al. There are several different types of color progressions used by cartographers. When mapping quantitative data, a specific color progression should be used to depict the data properly. Compare the circled features in the maps at right. This is problematic because the eye naturally integrates over areas of the same color, giving undue prominence to larger polygons of moderate magnitude and minimizing the significance of smaller polygons with high magnitudes. Though the UK’s 60 million inhabitants occupy an area of about 240,000 km 2, and the population density is therefore about 250/km 2, arbitrary halves of equal area would not also both have the same population density.Īnother common error in choropleths is the use of raw data values to represent magnitude rather than normalized values to produce a map of densities. Spatially Intensive data are things like rates, densities and proportions, which can be thought of conceptually as field data that is averaged over an area.The population of the UK might be 60 million, but it would not be accurate to arbitrarily cut the UK into two halves of equal area and say that the population of each half of the UK is 30 million. Spatially Extensive data are things like populations.Broadly speaking choropleths represent two types of data: Spatially Extensive or Spatially Intensive. The dasymetric technique can be thought of as a compromise approach in many situations. Incorrect (population, left) and correct (population density, right) application of a choropleth to data for Boston, Massachusetts Choropleth maps are frequently used in inappropriate applications due to the abundance of choropleth data and the ease of design using Geographic Information Systems. Where real-world patterns may not conform to the regions discussed, issues such as the ecological fallacy and the modifiable areal unit problem (MAUP) can lead to major misinterpretations, and other techniques are preferable. Thus, where defined regions are important to a discussion, as in an election map divided by electoral regions, choropleths are preferred. The term “choroplethe map” was introduced 1938 by the geographer John Kirtland Wright in “Problems in Population Mapping”.Ĭhoropleth maps are based on statistical data aggregated over previously defined regions (e.g., counties), in contrast to area-class and isarithmic maps, in which region boundaries are defined by data patterns. The earliest known choropleth map was created in 1826 by Baron Pierre Charles Dupin. The choropleth map provides an easy way to visualize how a measurement varies across a geographic area or it shows the level of variability within a region.Ī special type of choropleth map is a prism map, a three-dimensional map in which a given region’s height on the map is proportional to the statistical variable’s value for that region. Now, before we look at the map, let’s discuss what a choropleth map is.Ī choropleth map ( Greek χώρο– + πλήθ), (“area/region” + “multitude”) is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per-capita income. Today I am going to show you a fantastic choropleth map created by Matthew Bloch, Matthew Ericson and Tom Giratikanon from The New York Times.
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