A '''bivariate map''' displays two [[Variable (mathematics)|variables]] 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 [[Variable (mathematics)|variables]] 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 illustratingillustrate the [[Correlation and dependence|relationship]] between two spatially distributed variables. A bivariate mapIt has potential to reveal relationships between variables more effectively than a side-by-side comparison of the corresponding univariate maps.
ABivariate bivariate mapmapping is a comparatively 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|choropleth]] map uses color to solve a problem of representation in four dimensions; two spatial dimensions — longitude and latitude — and two statistical variables. DataTake classificationthe andexample graphicof representationmapping ofpopulation thedensity classifiedand dataaverage aredaily twomaximum importanttemperature processessimultaneously. involvedPopulation incould constructingbe given a bivariatecolour map.scale Theof numberblack ofto classesgreen, shouldand betemperature possiblefrom blue to dealred. Then an area with bylow thepopulation reader.and Alow rectangulartemperature legendwould boxbe isdark dividedblue, intohigh smallerpopulation boxesand wherelow eachtemperature boxwould representsbe acyan, uniquehigh relationshippopulation ofand thehigh temperature would be yellow, while low population and high temperature would be dark red. The eye can quickly see potential relationships between these 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]]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.
