Choropleth chorofails
Choropleth maps hold a certain fascination for me. More specifically, a fascination with how so many people get them so wrong. They are a really simple map type but there are numerous pitfalls. Here, I take a brief look at a couple of published maps that show what sort of issues arise through poor data processing, classification and design.
The problem with Figure 2 is the use of black for the highest class. Black connotates totality and taken on face value, the map would appear to suggest total infant mortality in many African countries which is unlikely to be the case. Dark grey would have been more appropriate. Better, the scheme should not mix pattern fill styles. All dots or lines would be more effective, varied in width and density to create the light-dark effect. A secondary problem of using black is it masks the country borders. While were on Figure 2, note that white has been used to show areas excluded from the study. While we are familiar with the world map, showing Greenland as excluded in the same colour as the map background isnt too much of a problem...but for choropleths in areas many readers may be unfamiliar with, avoiding using colours that clash with the map background is important so readers can discern what is part of the map and what is part of the background.
Take another look, yes, you saw correctly. There arent just overlapping classes (where would a value of 2% go for instance?) but the classes make absolutely no sense. Thats the tip of the iceberg. No change is symbolised in white...the same as the map background and also the same as the excluded area on Figure 2. It could be argued that no change is important and ought to be shown in something other than blank. Just as black infers totality, so white infers emptiness...and clearly no change is not the message communicated here. If we juxtapose the two maps on the same page, the reader already has in mind that white has been used on Figure 2 to show excluded so do they similarly make that connection here?
Then we look at Greenland which is shown in solid black. But wasnt Greenland excluded in Figure 2? Well, yes...and it is here as well but it stands out as a really important feature now its in black. Remember, darker features are more prominent visually yet Greenland is possibly the least important part of this map since its excluded from the study. And what of the shading scheme across the numerical classes? There is no attempt to go from light to dark and the design simply shows a range of four arbitrary patterns. It simply doesnt work.
Now lets take a look at one final example from a different publication which was created by a former colleague of mine to show in- and out-migration. It amused my former students immensely that this map was produced by someone with Professor and GIS in their title. So whats wrong with this one?
First of all...where is this place? Here we see the problem I alluded to earlier that unless youre familiar with a place the use of white for geographic areas and map background is a problem. In fact, its Wales in the UK and the area on the left of each map is actually the Irish Sea, symbolized the same as land to the north of the shaded areas. So is it all of Wales? Well no...its actually only a part of Wales and its not clear what the external boundary represents or, indeed, what the internal boundaries represent. Theyre possibly some census reporting areas but it would be helpful for this to be described in a title. Oh...theres no title, OK, lets move on to the legend. Well weve got that old favorite...overlapping classes on each map. This could simply be a labelling issue but equally, its unclear where values on the class breaks actually get reported.
Weve also got shading problems and while a dark grey is used for the upper end of the scheme we have white for the lowest class which isnt, actually empty at all. Now take a look at the small area just above left of the north point. Its shaded yet not inside the apparent study area boundary. So its been included in the data processing and classification but is on its own on the map. What do we infer from this? Ive no idea because its unexplained but if it isnt part of the study area then it should be excluded from the classification...and if thats the case the whole classification scheme is out by a fraction as there is one less area to map. Finally, we get a north arrow (when it isnt really necessary on a choropleth) yet in addition to lacking a title we also dont get a scale bar or an inset map showing us where this place is.
So the moral of this story? Firstly, be careful when you create a choropleth to ensure the data processing, classification and design make sense and readers see the patterns properly without confusion. Secondly, dont always believe what you see published whether in books, journals or via the web.