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Maps as advocacy

The Detroit Geographical Expedition and Institute, 1971

Maps are a form of data visualization. In fact, they are the oldest form of data visualization. Maps are not objective, omniscient representations of the world. They are deliberately painted pictures of the world, designed to make us see it a certain way.

On the right is a famous protest map, published in 1971 by the Detroit Geographical Expedition and Institute, a collaborative of radical geographers. The map’s makers hunted down data on how many children had been killed by cars in the city, when and where those accidents occurred, and the race of the driver and the victim. The map shows a pattern: huge numbers of Black children were killed by cars along the east-west roads, but rarely along the north-south ones. The east-west roads are the commuter routes linking wealthy white suburbs like Grosse Pointe, just off the right side of the map, with downtown, just off the left side of the map. The city was killing Black children by placing their low-income neighborhoods in the path of fast-driving, mostly-white commuters.

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The Detroit Geographical Expedition and Institute, 1971

And the deadly design of the city was no accident – it was created on purpose, by a map. Here’s the red-lining map of Detroit. Red-lining maps were created in the 1930s as a guide for banks and home lenders. The red and yellow areas were considered high risk, and so the maps kept banks from lending there, meaning people living in those neighborhoods could not get a mortgage to own a home. Green and blue neighborhoods were considered low risk, so it was easy to get a home mortgage there. The maps were created by people who literally and explicitly decided to classify minority neighborhoods as high risk and white neighborhoods as low risk. Thus, red-lining maps took a picture of existing segregation and inequality and then, through their influence over the banks, made segregation and inequality much worse.

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The Detroit Geographical Expedition and Institute, 1971

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The 2016 U.S. presidential election

(Donald Trump vs. Hillary Clinton)

map by M.E.J. Newman (CC-BY-2.0)

Electoral College results by state

Let’s discuss the supposed objectivity of maps by taking a look at the 2016 U.S. presidential election, in which Donald Trump defeated Hillary Clinton. Here’s a typical map of the election outcome, with the states that voted Republican colored in red, and the states that voted Democratic colored in blue.

Does anybody know when this color scheme -- red states for Republicans, blue states for Democrats – got started? (Students respond and discuss)

In case you didn’t know, it began with the TV news coverage of the contested 2000 election between Al Gore and George W. Bush, when the outcome of the election was in doubt for weeks, and the news stations kept showing the electoral map constantly. Prior to 2000, there was no set color scheme for the two major political parties. The entire concept of “red states” being different from “blue states” is a well-entrenched story American political division that was started by a map, and maps are primarily what keep it going.

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The 2016 U.S. presidential election

(Donald Trump vs. Hillary Clinton)

map by M.E.J. Newman (CC-BY-2.0)

Electoral College results by county

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The 2016 U.S. presidential election

(Donald Trump vs. Hillary Clinton)

map by M.E.J. Newman (CC-BY-2.0)

Electoral College results by county

sliding scale: more blue = more Democratic votes

more red = more Republican votes

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The 2016 U.S. presidential election

(Donald Trump vs. Hillary Clinton)

map by M.E.J. Newman (CC-BY-2.0)

Cartogram: results by county

size of area represents the number of votes:

bigger area = more votes

But there are other ways to represent geography in graphics. This is called a cartogram. It’s the same map you just saw, but now the size of each county is proportional to its population rather than to its geographic area. What did we give up by moving to this kind of map, and what did we gain? (Students respond and discuss)

Obviously we have sacrificed geographical accuracy. You wouldn’t want to try to use this as a roadmap. We have also sacrificed some usability – for example, it’s very difficult to decide where Denver is. But we’ve gained another kind of accuracy, because now, for the first time in this series of maps, one pixel always equals the same number of votes. This is the first map we’ve seen that hasn’t substantially minimized Democratic voting power from a visual standpoint.

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The 2016 U.S. presidential election

(Donald Trump vs. Hillary Clinton)

map by Ali Zifan (CC-BY-SA-4.0)

Electoral College results by state

Discretized cartogram: one square = one vote

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The 2016 U.S. presidential election

(Donald Trump vs. Hillary Clinton)

maps by M.E.J. Newman and Ali Zifan

Popular votes

Clinton: 65,853,514

Trump: 62,984,828

Electoral votes

Trump: 306

Clinton: 232

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https://www.youtube.com/watch?v=kIID5FDi2JQ

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Ask students whether they can identify what they are looking at in this map (students respond and discuss).

This is a 1944 US Army Corps of Engineers map of old Mississippi river channels in the historic floodplain. This particular section is on the Mississippi – Arkansas border. This was published as a series of maps that stretched all the way from Missouri to Louisiana.

Historically, the Mississippi River used to flood regularly, and when the floodwaters receded, the river would usually be running in a different channel than before the flood. By going out and walking the floodplain, mapmakers could figure out which former river channels cut across which other ones, and that allowed them to date the different flood channels. Here, the different colors show the former path of the river in different years.

Besides being beautiful, what story does this map tell? (students respond and discuss)

Answers may include:

The river changes course all the time; it is not static, but very dynamic.
This map challenges the notion that maps depict unchanging geography.
If you live near the floodplain, be prepared for radical change.

Let’s say you’re an engineer who wants to build support for building dams, dikes, and levees for flood control. How might this map support your argument? (Students respond and discuss)

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Migration routes of 118 bird species

Nowadays, maps don’t have to sit still.

This is an animated GIF (it runs in slideshow view).

Each dot represents the average location of all members of a different bird species on a particular day of the year
From data uploaded to the web by birdwatchers around the world each day

What stories does this map tell?

You may not realize it, but birds don’t just fly north in spring and south in fall – many birds are in near-constant movement all year as they seek the resources they need
Conservation is not (just) a local issue – creating a bird reserve in the U.S. is not enough if our birds spend 8 months of the year outside the country!
The hemisphere (actually, the planet) is one big interconnected biological system, and birds don’t see national boundaries

Alongside all the other maps we’ve looked at today, I hope this one helps convince you that maps don’t just show the world as it is: map designers are always telling stories and making arguments.