Nusrat Sabrina, Alam Muhammad Jawaherul, Scheidegger Carlos, Kobourov Stephen
IEEE Trans Vis Comput Graph. 2018 Oct;24(10):2675-2688. doi: 10.1109/TVCG.2017.2765330. Epub 2017 Oct 23.
We describe bivariate cartograms, a technique specifically designed to allow for the simultaneous comparison of two geo-statistical variables. Traditional cartograms are designed to show only a single statistical variable, but in practice, it is often useful to show two variables (e.g., the total sales for two competing companies) simultaneously. We illustrate bivariate cartograms using Dorling-style cartograms, yet the technique is simple and generalizable to other cartogram types, such as contiguous cartograms, rectangular cartograms, and non-contiguous cartograms. An interactive feature makes it possible to switch between bivariate cartograms, and the traditional (monovariate) cartograms. Bivariate cartograms make it easy to find more geographic patterns and outliers in a pre-attentive way than previous approaches, as shown in Fig. 2 . They are most effective for showing two variables from the same domain (e.g., population in two different years, sales for two different companies), although they can also be used for variables from different domains (e.g., population and income). We also describe a small-scale evaluation of the proposed techniques that indicates bivariate cartograms are especially effective for finding geo-statistical patterns, trends and outliers.
我们描述了双变量统计图，这是一种专门设计用于同时比较两个地理统计变量的技术。传统统计图仅用于展示单一统计变量，但在实际应用中，同时展示两个变量（例如，两家竞争公司的总销售额）通常很有用。我们使用多林风格的统计图来说明双变量统计图，不过该技术简单且可推广到其他类型的统计图，如连续统计图、矩形统计图和非连续统计图。交互式功能使我们能够在双变量统计图和传统（单变量）统计图之间进行切换。如图2所示，双变量统计图比以前的方法更容易以预注意的方式发现更多地理模式和异常值。它们在展示来自同一领域的两个变量（例如，两个不同年份的人口、两个不同公司的销售额）时最为有效，尽管它们也可用于来自不同领域的变量（例如，人口和收入）。我们还描述了对所提出技术的小规模评估，结果表明双变量统计图在发现地理统计模式、趋势和异常值方面特别有效。
