Multivariate map: Difference between revisions

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A '''bivariate map''' displays two [[variableVariable (mathematics)|variables]]s on a single [[map]] by combining two different sets of graphic symbols or colors. Bivariate mapping is an important technique in [[cartography]]. Given a set of geographic features, a bivariate map displays two [[variableVariable (mathematics)|variables]]s on a single map by combining two different sets of graphic symbols. It is a variation of simple [[choropleth map]] that portrays two separate phenomena simultaneously. The main objective of a bivariate map is to find a simple method for accurately and graphically illustrating the [[relationship]] between two spatially distributed variables. A bivariate map has potential to reveal relationships between variables more effectively than a side-by-side comparison of the corresponding univariate maps.

A bivariate map is recent graphical method which is intended to convey the spatial distribution of two variables and the geographical concentration of their relationship. A bivariate choropleth map uses color to solve a problem of representation in four dimensions; two spatial dimensions — longitude and latitude — and two statistical variables. Data classification and graphic representation of the classified data are two important processes involved in constructing a bivariate map. The number of classes should be possible to deal with by the reader. A rectangular legend box is divided into smaller boxes where each box represents a unique relationship of the variables.

In general, bivariate maps are one of the alternatives to the simple univariate [[choropleth map|choropleth maps]]s, although they are sometimes extremely difficult to understand the distribution of a single variable. Because conventional bivariate maps use two arbitrarily assigned color schemes and generate random color combinations for overlapping sections and users have to refer to the arbitrary legend all the time. Therefore, a very prominent and clear legend is needed so that both the distribution of single variable and the relationship between the two variables could be shown on the bivariate map.

== References ==

*Dunn R., (1989). A dynamic approach to two-variable color mapping. The American Statistician, Vol. 43, No. 4, pp. 245-252245–252.

*Jeong W. and Gluck M., (2002). [[Multimodal]] bivariate thematic maps with auditory and haptic display. Proceedings of the 2002 International Conference on Auditory Display, Kyoto, Japan, July 2-5.

*Leonowicz, A (2006). Two-variable choropleth maps as a useful tool for visualization of geographical relationship. Geografija (42) pp. 33-3733–37.

*Liu L. and Du C., (1999). Environmental System Research Institute (ESRI), online library.

*Olson J. (1981). Spectrally encoded two-variable maps. Annals of the Association of American Geographers. 71 (2): 259-276.

*Trumbo B. E. (1981). A theory of coloring bivariate statistical maps. The American Statistician, Vol. 35, No. 4, pp. 220-226220–226.

==See also==