Of all the different methods of statistical mapping, the choropleth method has benefited the most from the computerization of maps. The shading or tinting of areas to depict attribute values is now the most common way to map all forms of socioeconomic data, far eclipsing other methods of statistical mapping that were more common in the manual era.
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The areas mapped may be naturally occurring, as with land cover types, or may be arbitrarily defined by humans, as in the case of states, counties, or census enumeration areas. Often mispronounced as “chloropleth,” the name comes from the Greek choros (place) and plethos (value). This symbolization method is used for both qualitative and quantitative data. In mapping quantitative data, the data are usually classified into categories using one of a variety of data classification schemes. The main purpose of choropleth mapping is to discover and present spatial patterns. Conveying the actual data values is seen as a secondary purpose, as this can best be done with a table.
Issues in Choropleth Mapping
Implied with this mapping method is that the value assigned is consistent throughout any enumeration unit. While this may be the case with qualitative data, especially when symbolizing jurisdictional units (e.g., school districts or counties), it would rarely be the case with quantitative data (e.g., income or rainfall). A second concern arises when this method is used with enumeration units that vary considerably in size, resulting in the visual dominance of larger areas. This issue is explored further below.
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Qualitative Choropleth Mapping
A land use or land cover map is an example of a qualitative choropleth map. Shadings with varying textures or colors are used to symbolize the mapped classes, for example, to differentiate land areas from water areas or urban from rural. In symbolization, care must be taken to not include so many categories that it becomes impossible to distinguish slightly different colors or shades, making it difficult to match the shading in the map with the same shading in the legend. Colors or textures must be chosen to be as different from each other as possible. In interactive mapping environments, the association between the shadings in the map and the legend can be enhanced by highlighting areas in the map as the mouse is passed over the corresponding color or shading in the legend, and vice versa
Quantitative Choropleth Mapping
By far the most common quantitative choropleth maps are those that involve the progression of gray shadings or sequence of colors to represent interval or ratio data over areas. Usually, the data are reduced to ordinal, or classed, data before mapping through one of many different types of data classification. Since the data classes assigned will have so me relative ordering, tinting schemes, referred to as color progressions or sometimes color ramps, that progress from light to dark, with higher values receiving a darker shading or color, should be used. In some cases, the color progression may be bipolar, with two different colors or hues around a zero value. An example of this would be a map of percent population change that includes both positive and negative values. In this case, the negative values might be shown using a red progression that gradually decreases in lightness as the values move toward zero, and the positive values shown with a blue progression that increases in darkness as the values get larger
A significant problem with this mapping method for quantitative data occurs when tints or colors are used that do not progress in a visually consistent manner from a lighter shading or color to a darker shading or color. The inappropriate selection of a color sequence detracts from the visual recognition of spatial patterns. When using gray-scale shadings, a nonlinear perceptual adjustment must be made to compensate for the visual underestimation of values. For example, a shading with a 65% reflectance value (35% ink) will generally be perceived as 50%.
The use of the choropleth mapping method for absolute values is often discouraged. For example, a map of the number of Hispanics by state (absolute numbers) would have California and Texas in the top category. New Mexico, which may have a higher percentage of Hispanic population than either California or Texas but Choropleth Map———37 has a much smaller total population, would be in a lower category. The large population in the states of California and Texas leads to the high number of Hispanics, and the map would therefore be more a reflection of differences in population rather than differences in Hispanic population. For this reason, mapping percentages or ratios rather than absolute numbers is preferred.
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What are the benefits and types of choropleth method statistical mapping ?
Of all the different methods of statistical mapping, the choropleth method has benefited the most from the computerization of maps. The shading or tinting of areas to depict attribute values is now the most common way to map all forms of socioeconomic data, far eclipsing other methods of statistical mapping that were more common in the manual era. The areas mapped may be naturally occurring, as with land cover types, or may be arbitrarily defined by humans, as in the case of states, counties, or census enumeration areas. Often mispronounced as “chloropleth,” the name comes from the Greek choros (place) and plethos (value). This symbolization method is used for both qualitative and quantitative data. In mapping quantitative data, the data are usually classified into categories using one of a variety of data classification schemes. The main purpose of choropleth mapping is to discover and present spatial patterns. Conveying the actual data values is seen as a secondary purpose, as this can best be done with a table.
Issues in Choropleth Mapping
Implied with this mapping method is that the value assigned is consistent throughout any enumeration unit. While this may be the case with qualitative data, especially when symbolizing jurisdictional units (e.g., school districts or counties), it would rarely be the case with quantitative data (e.g., income or rainfall). A second concern arises when this method is used with enumeration units that vary considerably in size, resulting in the visual dominance of larger areas. This issue is explored further below.
Qualitative Choropleth Mapping
A land use or land cover map is an example of a qualitative choropleth map. Shadings with varying textures or colors are used to symbolize the mapped classes, for example, to differentiate land areas from water areas or urban from rural. In symbolization, care must be taken to not include so many categories that it becomes impossible to distinguish slightly different colors or shades, making it difficult to match the shading in the map with the same shading in the legend. Colors or textures must be chosen to be as different from each other as possible. In interactive mapping environments, the association between the shadings in the map and the legend can be enhanced by highlighting areas in the map as the mouse is passed over the corresponding color or shading in the legend, and vice versa
ADVERTISEMENTS:
Quantitative Choropleth Mapping
By far the most common quantitative choropleth maps are those that involve the progression of gray shadings or sequence of colors to represent interval or ratio data over areas. Usually, the data are reduced to ordinal, or classed, data before mapping through one of many different types of data classification. Since the data classes assigned will have so me relative ordering, tinting schemes, referred to as color progressions or sometimes color ramps, that progress from light to dark, with higher values receiving a darker shading or color, should be used. In some cases, the color progression may be bipolar, with two different colors or hues around a zero value. An example of this would be a map of percent population change that includes both positive and negative values. In this case, the negative values might be shown using a red progression that gradually decreases in lightness as the values move toward zero, and the positive values shown with a blue progression that increases in darkness as the values get larger
A significant problem with this mapping method for quantitative data occurs when tints or colors are used that do not progress in a visually consistent manner from a lighter shading or color to a darker shading or color. The inappropriate selection of a color sequence detracts from the visual recognition of spatial patterns. When using gray-scale shadings, a nonlinear perceptual adjustment must be made to compensate for the visual underestimation of values. For example, a shading with a 65% reflectance value (35% ink) will generally be perceived as 50%.
The use of the choropleth mapping method for absolute values is often discouraged. For example, a map of the number of Hispanics by state (absolute numbers) would have California and Texas in the top category. New Mexico, which may have a higher percentage of Hispanic population than either California or Texas but Choropleth Map———37 has a much smaller total population, would be in a lower category. The large population in the states of California and Texas leads to the high number of Hispanics, and the map would therefore be more a reflection of differences in population rather than differences in Hispanic population. For this reason, mapping percentages or ratios rather than absolute numbers is preferred.