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A choropleth map (from Greek χώρο ("area/region") + πλήθος ("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. 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. == Overview == The earliest known choropleth map was created in 1826 by Baron Pierre Charles Dupin.〔Michael Friendly (2008). ("Milestones in the history of thematic cartography, statistical graphics, and data visualization" ).〕 The term "choroplethe map" was introduced in 1938 by the geographer John Kirtland Wright in "Problems in Population Mapping". Choropleth 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. Thus, where defined regions are important to a discussion, as in an election map divided by electoral regions, choropleths are preferred. 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.〔T. Slocum, R. McMaster, F. Kessler, H. Howard (2009). ''Thematic Cartography and Geovisualization'', Third Edn, pages 85–86. Pearson Prentice Hall: Upper Saddle River, NJ.〕 The dasymetric technique can be thought of as a compromise approach in many situations. Broadly speaking choropleths represent two types of data: spatially extensive or spatially intensive. * Spatially extensive data are things like populations. 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 intensive data are things like rates, densities and proportions, which can be thought of conceptually as field data that is averaged over an area. Though the UK's 60 million inhabitants occupy an area of about 240,000 km2, and the population density is therefore about 250/km2, arbitrary halves of equal area would not also both have the same population density. Another common error in choropleths is the use of raw data values to represent magnitude rather than normalized values to produce a map of densities.〔Mark Monmonier (1991). ''How to Lie with Maps''. pp. 22–23. University of Chicago Press〕 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. Compare the circled features in the maps at right. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Choropleth map」の詳細全文を読む スポンサード リンク
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