Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series

摘要: Our research goal was to determine which choropleth classification methods are most suitable for epidemiological rate maps. We compared seven using responses by fifty-six subjects in a two-part experiment involving nine series of U.S. mortality Subjects answered wide range general map-reading questions that involved individual maps and comparisons among series. The addressed varied scales map-reading, from enumeration units, regions, whole-map distributions. Quantiles minimum boundary error were best suited these tasks. Natural breaks (Jenks) hybrid version equal-intervals classing formed second grouping the results, both producing less than 70 percent as accurate quantiles. Using matched legends across (when possible) increased map-comparison accuracy approximately 28 percent. advantages careful optimization procedures chorop...