When placed above our election results layer in the Table of Contents we can see how the transparent layer works: We end up with a layer that looks like this with the transparent areas showing white because that’s the background color of the map: We’ll then apply it to a copy of the counties data so that areas with relatively low voter population density are shaded in the darker colors and counties with relatively high levels of voter population density are increasingly transparent. Using the Color Scheme Editor we can easily create a Continuous Color Scheme that goes from near black to fully transparent by simply defining two endpoints of the color scheme. A value by alpha map uses a layer that represents the population density of voters as a way to subdue areas that have relatively fewer voters and focus our attention on the areas that have relatively more voters, and therefore more of an impact in the final tally. As we know, different counties have very different numbers of voters. It’s a diverging color scheme that varies away from 50% equal share of votes by using colors that make sense as you go further towards a strong majority.īut this isn’t the full picture because it’s not just the majority share (as a percentage) that is important…it’s also the population density and, consequently, the voter density. The marginal counties are those that occupy the merged purple colorspace. For instance, in the following map of the 2012 Presidential election we can see how the share of votes goes from a rich blue for counties that are predominantly Democrat to a vibrant red for those that are predominantly Republican. In this case, though, the bottom layer contains the choropleth and the top layer contains a layer that represents some characteristic such as uncertainty. It uses the same principles as the bivariate choropleth by combining two layers. It’s an interesting way to visualize the relationship between variables…and it’s possible to take this concept further to create a trivariate choropleth, again simply by changing the layer’s transparency settings.Īnother way to use transparency to represent more than one variable on a thematic map is to create a value by alpha map. We can very quickly see which countries are in the highest class on both variables, the lowest on both variables or perhaps where anomalies occur where countries are high on one variable and low on another. As a way to quickly see the relationship between two variables a bivariate choropleth is useful. If we’d have used 4 then we’d get a 4 x 4 bivariate grid with 16 separate colors and it starts to get a little tricky to differentiate them. Because of the new way in which transparency is controlled (which directly uses your graphics card to do the processing) the result appears on-the-fly and fast!Īs an aside, when creating a bivariate choropleth it’s important to limit the number of classes for each of the input layers. On the cyan colored map the legend shows the increasingly saturated color going left to right and on the magenta colored map the increasingly saturated color goes from bottom to top.īy setting the layer transparency of the top layer to 50% using the slider on the Appearance ribbon you end up with a map where the layer colors are properly combined. The small 9 x 9 grid is added to act as a legend so you can see what’s going on when the colors are combined. Simply position one layer on top of the other in the Table of Contents and then apply 50% transparency to the top layer using the transparency tool on the Appearance ribbon…hey presto, the colors blend and create a bivariate map.īreaking it down, the following two maps show different attributes, each classified into three quantiles showing the high, medium and low distribution of each variable.
![us population density map transparent us population density map transparent](https://i.redd.it/gqgrfttly9l31.png)
Let’s say we’re interested in creating a bivariate choropleth map, which is essentially the graphical combination of two choropleth maps. Let’s take a quick look at how modifying transparency for your map layers and symbols can begin to extend your cartographic possibilities. The completely redesigned graphics engine in ArcGIS Pro supports a rich array of possibilities for improved control over your graphics which has major benefits for your mapping. This is something of which we’ve been acutely aware as we began the process of designing and building ArcGIS Pro. Most people who have a long history with ArcMap have at one time or another wanted to apply a little transparency to their symbols and have been frustrated to find the options limited (I’m one of these people!). One of the main benefits of redesigning a software package from the ground up is you can reflect on some of the limitations of what went before and deal with them head on.