Not All Reds Are Equal: What Maps Don't Tell You

(This article has been published on LinkedIn)

Photo by Mary Anne Twimbers on Unsplash

People love maps, for good reason. When geography is an important factor, maps are one of the fastest ways to communicate information. And when data is available at regional or country level, the default choice is often the choropleth map. It’s easy to make (yes, even in Excel), widely used, and sometimes misleading.

The problem isn’t that choropleths are wrong. It’s that they’re often used without considering alternatives and that can quietly distort the message.

The first issue is well-known. Our brains read area as importance. Bigger shapes feel more significant.

If you look the map on the left, your eye is naturally drawn to the large countries on the top right. Yet those regions may represent less than 30% of the European area and about 4% of the entire population. Ask yourself: is this really the most important information in your map?

The second issue is subtler, and more dangerous when dealing with climate risk. I am no theory expert so I will go straight to an example. Imagine that the map on the left is showing climate risk by country. A reader in France looks at the map and sees their country labelled “high risk”. They live near Lyon and own a farm. Can they assume their farm carries that same risk?

Technically, no. We can talk about aggregation, averages, and uncertainty. But this is not how it works: remember, when you publish a data visualisation you lose control on the narrative. People translate shapes and colours into meaning instinctively. If their country is classified “red”, they will tend to treat everything inside it as “red”, even when that is false or highly uncertain at local scale. And that’s often the case when dealing with climate risk, when often you can reasonably say something at national scale that becomes too uncertain at postcode level.

This matters especially for risk communication. What is true at national level often breaks down at regional, municipal, or postcode level. If your audience includes local decision-makers, entrepreneurs, or citizens, the scale of the visualisation must match the scale of their decisions.

There’s no one-size-fits-all solution. Sometimes a different map works better. Sometimes a different chart altogether. The point is simple: don’t default to the default. Look at the map on the right side, it conveys the same information but it makes clear that the data is at country level.

Maps are powerful. That’s exactly why we need to use them with care.