Cartogram Maps: Data Visualization with Exaggeration

cartogram maps

GIS typically focuses on drawing spatial features with accuracy. However, the cartogram does the opposite!

Cartogram maps distorts reality to convey information. They resize and exaggerate any variable using a polygons geometry.

Pretty neat, don’t you think?

We’ll show you the different cartogram maps that exist along with the GIS software you can use to create your own.

1 The Density-Equalizing Cartogram

Density-equalizing (contiguous) cartograms are your typical cartograms. In density-equalizing cartograms, map features bulge out a specific variable. Even though each feature becomes distorted, it remains connected during its creation.

For example, in this density-equalizing cartogram, we use population as the main driver to exaggerate area. In QGIS, you can accomplish this with the QGIS Cartogram Plugin.

density equalizing cartograms

As you can see, it’s easy to get information at only a glance. Which states stick out like a sore thumb in this population map? Straightaway you can see that a high proportion of population live in California and New York. While states like Montana and North Dakota are dwarfed in it and shrink to bite-size proportions.

As objects shrink and grow in density-equalizing cartograms, cartographers have to consider resizing polygons appropriately while maintain their true geometry.

2 The Non-Contiguous Cartogram

Features in non-contiguous cartograms don’t have to stay connected. Objects can freely move from adjacent polygons and be resized appropriately. Because of this free movement, shape remains in tact for non-contiguous cartograms such as in this population map of the United States below created in ArcGIS.

non-contiguous cartogram

Again, the geometry and space of the map gets distorted to convey information of the population variable. For example, the state of California has grown significantly because of their large population.

The main difference between density-equalizing cartograms is that it moves each feature’s centroid to avoid any overlapping.

Although overlaps sometimes exist in non-contiguous cartograms, they can be more difficult to differentiate between resized polygons.

3 The Dorling Cartogram

The Dorling Cartogram (named after professor Danny Dorling) uses shapes like circles and rectangles to depict area. These types of cartograms make it easy to recognize patterns. In the example below, we used GeoDa software to generate the Dorling cartogram.

dorling cartogram

As you can see, states are substituted with appropriately-sized circles to represent clusters of population in the United States. Without a doubt, it is highly effective at conveying information and patterns.

However, the downfall for Dorling Cartograms is that the centroid and shape are not maintained. This means that readers may have difficulty understanding features in the map. You may not have even known this was the United States if I didn’t tell you!

Now, It’s Your Turn

Cartograms exaggerate the size of the geography proportional to the statistic being shown. To clarify, the variable substitutes land area or distance.

But what they do is really distort our view of mapping by breaking the golden rule – sacrificing geometry to convey information.

Another key point is each type of cartogram has its pros and cons to effectively visualize data with the variable determining the size of the polygon.

To begin creating your own cartograms, give QGIS, GeoDa and ArcGIS a test-drive. Alternatively, read more on choropleth map as another method of data visualization.

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