Tag Archives: maps

Mapping wealth by locating iPhone, Android, and Blackberry owners

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Check out the maps of cell phone owners in Washington, D.C., New York, Chicago, and a number of other major American cities:

Among other things, cell phone brands say something about socio-economics – it takes a lot of money to buy a new iPhone 5 (and even more money to keep up with the latest models that come out faster than plan upgrades do). Consider, then, this map of Washington, D.C., which uses geolocated tweets, and the cell phone metadata attached to them, to illustrate who in town is using iPhones (red dots) and who’s using Androids (green dots)…

That picture comes from a new series of navigable maps visualizing some three billion global, geotagged tweets sent since September of 2011, developed by Gnip, MapBox and dataviz guru Eric Fischer. They’ve converted all of that data from the Twitter firehose (this is just a small fraction of all tweets, most of which have no geolocation data) into a series of maps illustrating worldwide patterns in language and device use, as well as between people who appear to be tourists and locals in any given city.

The locals and tourists map scales up a beautiful earlier project from Fischer. You could kill a few hours playing with all of these tools, built on the same dataset. But we particularly liked looking at the geography of smart phone devices. As in Washington, above, iPhones are often more prominent in upper-income parts of cities (and central business districts), while Androids appear to be the dominant device in lower-income areas.

It sounds like there could be some methodological issues here. The data doesn’t cover all Twitter users and then Twitter users are already a small subset of the US population. Nonetheless, these are interesting maps. I saw recently that over 50% of Americans now have smartphones – it jumped from 35% to 56% in several years. But, not all cell phones cost the same or aim for the same markets. iPhones aren’t just expensive. They also have a certain aesthetic and set of features that appeals to a certain set of Americans. Samsung had a set of recent commercials that played off the cool factor of iPhones, raising the idea of the phone as (expired?) status symbol. If you asked smartphone owners why they chose the phone they did, how many would admit that the status of the phone significantly factored into their decision?

More broadly, it would be interesting to think about what other common consumer goods could be mapped in ways that show clear patterns.

American median income, poverty rates, and inequality by county

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Check out these maps of American inequality and income using the latest American Community Survey data.

The below five maps were created by Calvin Metcalf, Kyle Box and Laura Evans using the latest five-year American Community Survey estimates provided by the Census Bureau for last weekend’s National Day of Civic Hacking (we’re geeking out on these projects this week).

Working from Boston, the group has so far mapped nearly a dozen demographic points from the data, including a few they calculated on their own (be sure to check out the very bizarre map of America’s gender ratios by county). These five maps, however, jumped out at us for how they each illustrate deep and lingering differences between the American North and South, as seen through several different data points. Of course, the patterns aren’t perfect, and exceptions abound; major cities in the North turn out to be hotspots of inequality on par with much of the Deep South…

Median income (in annual dollars)

Population living below the poverty line (by percent)

Income inequality (as measured by the Gini coefficient, the closer to zero the better)

There do seem to be seem some regional differences. But, these three maps raise other questions:

1. This may be a good place for population weighted maps. While counties are one unit of geographic measure, they can obscure finer-grained data. For example, the map of median income shows higher incomes in urban areas but this glosses over poor urban and suburban neighborhoods. Plus, many of the counties in the South, Great Plains, and Mountain West have relatively fewer people.

2. The income map shows one story – generally higher incomes in urban areas – and the inequality, measured by the Gini coefficient, shows that these same urban areas have high levels of inequality. This may be an issue with the county measure but it also highlights that while cities are economic engines, they are also homes to pronounced inequality.

Five experts weigh in on global flight-path maps

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An art critic, environmentalist, aviation consultant, data visualization expert, and philosopher offer some interpretations of global flight-path maps.

From the art critic:

It’s almost like contemporary fractalisation – based on fractals, those beautiful divisions of science and nature. A number of artists have exploited them. Max Ernst based a lot of his surreal landscapes on fractalisation.

From the aviation consultant:

Europe looks so bright because it has so many short-haul flights. It’s also one of the busiest global markets and there are several hubs in relatively close proximity in Europe: Paris, Frankfurt, Amsterdam and London…

What we’re going to see in a few years is more connections between Asia and Africa, and South America and Africa, along with more “south-south” trade.

From the expert in data visualization:

You can see the density of the flights, but it doesn’t show you how many people are travelling on them. You could do that by colouring them differently.

From the philosopher:

We are not seeing the life of individual human beings, but the life of the species as a whole, as if the species was one organism, pulsating like a jellyfish. Maybe it represents our collective existence?

Interesting thoughts all around. The quote above from the philosopher is right on in that maps like these allows us to see larger patterns and how we are all connected. It is not just about the flow of passengers or cargo back and forth but also about how these flight paths connect us. The maps could also serve as a proxy for global power and business activity. I remember seeing work from sociologist Zachary Neal along these lines. Take a look at his publications involving cities, networks, and airplanes here.

London’s iconic Tube map turns 80

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First distributed for free on a trial basis in 1933 because officials didn’t think it would be successful, London’s Tube map turns 80 this year:

Instantly recognizable the world over, the simple yet elegant diagram of the 249-mile subway network is hailed as one of the great images of the 20th century, a marvel of graphic design. Its rainbow palette, clean angles and pleasing if slightly old-fashioned font (Johnston, for typography buffs) have endured since hurried passengers first stuffed pocket versions of the map into their raincoats in 1933.

“It’s a design icon,” said Anna Renton, senior curator at the London Transport Museum. “You shouldn’t use that word too often, but it really is.”…

Inspired, some say, by electric-circuit diagrams, Beck straightened out the lines, drew only 45- and 90-degree angles, and truncated distances between outlying stations. Then he submitted his unusual schematic rendering to the London Underground’s publicity department…

The design led to imitations around the world. Within a few years, it was copied by the transit system in Sydney, Australia. The New York subway map of the 1970s also paid homage to Beck’s brainchild.

And it still inspires design efforts today.

It is interesting to read how this map became so successful even as it skewed the actual spatial relationships between lines, stations, and London itself. The map may make more conceptual and aesthetic sense but it doesn’t fit aboveground London. I don’t know if anyone has ever tried to test the mental work London residents have to do to match the map to the city.

Reformatting a zoning map of Chicago to look like SimCity 2000

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Zoning maps can include a lot of categories but what happens if it is converted to a SimCity 2000 format? Check out this recolored Chicago zoning map:

To spice up their interactive “2nd City Zoning” map of Chicago, Derek Eder, Juan-Pablo Velez and Aya O’Connor paid tribute to the SimCity franchise with some familiar color-coding. Blue for commercial, yellow for industrial, green for residential.

Then they got carried away, incorporating a few choice icons from SimCity 2000 as well as some of that legendary game music, which you can listen to while you browse the map.

Zoning is a little more complicated than the tri-color scheme implies, but by the time you get to the portion of the site that explains the difference between Manufacturing and Planned Manufacturing Districts, it’s mission complete for the designers.

Here are more details of the SimCity change from 2nd City Zoning – including a plea to not be sued.

It is too bad there isn’t a longer discussion about the simplicity of SimCity zoning versus real world zoning. Are there benefits to presenting a simpler zoning map to residents? (This assumes that there are a good number of residents that want to look at such maps.) How much complexity compared to real life was SimCity missing in the 2000 version? SimCity players might have learned something by playing the game but might also have been misled by the reductionism.

The music takes me back…

Mapping NFL fandom by county with Facebook likes

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Facebook has put their massive data trove to use and examined the geographies of NFL fandom. Here is what they came up with:

The National Football League is one of the most popular sports in America with some incredibly devoted fans. At Facebook we have about 35 million account holders in the United States who have Liked a page for one of the 32 teams in the league, representing one of the most comprehensive samples of sports fanship ever collected. Put another way, more than 1 in 10 Americans have declared their support for an NFL team on Facebook…

While winning seems to matter, NFL teams have local followings that are probably heavily influenced by family ties and/or where a person grew up,  so we were obviously curious to see where the fans for various teams live now. By considering the physical locations of NFL fans, we can construct a map of the top team for each county in the US. It tells an interesting story about the ways that football rivalries and allegiances alternately divide and unite the country, and sometimes even individual states.

In some cases, whole states and even entire regions of the country uniformly support a single team.  For instance the Vikings are easily the only game in town in Minnesota, while New England appears to be comprised of entirely Patriots fans except for a small portion of Connecticut.

There are some states which are divided into regions by teams.  Florida has three teams–the Tampa Bay Bucs, Miami Dolphins, and the Jacksonville Jaguars–and Facebook users there seems fractured in their support, with some counties even defecting to teams from the North. Ohio is another interesting story, with the Cleveland Browns in the North, Cincinatti Bengals in the South, and Pittsburgh Steelers fans occupying the middle of the state.

Some teams, like the Steelers, Cowboys, and Packers, seem to transcend geography, with pockets of fans all over the country. On the other end of the spectrum, the Jets have to share New York with the Giants and are only the most popular team for a single stronghold county in Long Island.

Five quick thoughts:

1. There are few other organizations that could put together such a map without undertaking a major survey (since this is measured at the county level).

2. The best part for Facebook: users voluntarily provided this data.

3. Could Facebook end up being the most important future source for telling us about American society? There are still difficulties: users have to opt in (in this particular case, they had to “like” a NFL team), not everyone is involved (though it seems like pretty close), and not all users are putting everything in their profiles.

4. Is there a way to weight this map with population density? For example, the Cowboys may have a really broad geographic reach but many of those counties have fewer people. In contrast, teams like the Jets or Eagles have smaller reaches yet more people live in those areas.

5. Is there a way to show the percentage of county respondents who liked the dominant team? I imagine there are plenty of counties where one team does not have a strong majority, let alone even much of a plurality. For example, Jets fans barely show up on the map because they are only the top team in one county. Yet, there are plenty of Jets fans.

Seeing American population density one person at a time

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A MIT graduate student has put together new maps of American population density by plotting each person on a map:

Brandon Martin-Anderson, a graduate student at MIT’s Changing Places lab, was tired of seeing maps of U.S. population density cluttered by roads, bridges, county borders and other impediments.

Fortunately for us, he has the technological expertise to transform block data from the 2010 Census into points on a map. One point per person, and nothing else. (Martin-Anderson explains the process in more depth here.)

At times, the result is clean and beautiful to the point of abstraction, but when you know what you’re looking at, it’s a remarkably legible map. And while it resembles, broadly, Chris Howard’s political map of density that appeared after the presidential election, Martin-Anderon’s map can be magnified at any point. Users can watch each of the country’s metro areas dissolve from black to white. Even stripped of the features (roads, rivers) that shape human settlement, density has its own logic.

The maps show some different spatial patterns. For example, look at the different between some of the Northeast Corridor and the Midwest:

I don’t know that it is right to see density has its own logic; there are underlying factors behind these patterns. Topography is one factor but we could also look into how cities and suburbs expand (and there are a variety of sociological explanations about this including profit-seeking, competition for land, and global forces) and might also think about this in terms of social networks (the Northeast is denser, the Midwest more spread out).

Additionally, what about the flip side of these maps: there is still a decent amount of less dense space in these maps. We tend to focus on the largest population centers, several of which are represented on these maps, but the really dense areas are still limited. I suppose this is a matter of perspective: just how much less dense space do we need or should we have around and between metropolitan areas? Some of this would be affected by land that cannot be used profitably and well or land that is used for farming.

One caveat I have about how these maps were presented: shouldn’t they be at the same scale to really make comparisons?

Mapping Chicago by taking a photo at every major intersection

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Planner Neil Freeman found an interesting way to map Chicago: take a photo of every major intersection. A post on Atlantic Cities describes the map:

Freeman’s first project, called “Chicago mile by mile,” created an unconventional city map of the city based on 212 photos of strategic “mile” intersections. It was inspired by Chicago’s unique grid system, in which every eight blocks measures a full mile, and the city’s corresponding address system, which advances (for the most part) in increments of 800. If you begin at the zero-points of Madison and State streets and go west a mile, for example, you’ll reach the corner of Halsted Street at 800 W Madison Street.

“This arbitrary address system ends up defining what it means to live in Chicago,” he says. “These arbitrary systems that end up underlying our built environment of our daily life are really intriguing to me.”

On the webpage with the map, here is how Freeman describes the map:

 

Chicago mile by mile

Neil Freeman, 2002
213 color photographs
114 x 104 inches

These photographs maps Chicago’s uncomprimising street grid into 212 4″x6″ snapshots. The photographs document every intersection of mile streets, major roads on section lines. The entire city is traversed by this network of arterials. Photographs were taken in January 2002.

It would take a while to look at the thumbnails of all the photographs. However, I think doing so might start to reveal patterns. In other words, are the major intersection on the North Side more alike or different from major intersections on the South Side? Are there patterns across all intersections? I suspect there may be as these major intersections would tend to attract certain kinds of functions and organizations.

Extending this project in three possible ways could also add a lot of information. One way to expand this would be to start filling in more of the intersections between these major ones. A second way would be to track these intersections over time. If Freeman took all of these photographs again in 2012, how much would have changed? A third way would be to collect data on how people experience and visual these intersections and compare this to the photographs. How exactly do residents and visitors perceive these intersections?

Adapting the genre of transit maps to other kinds of data

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Check out this collection of 6 transit-style maps based on different kinds of information: the best movies of all time, the National Parks system, web trends, the Mississippi River, the US Interstate system, and the world’s transit systems.

Within the sociology of culture, this could lead to an interesting discussion regarding genres. The average city-dweller likely has some idea of what transit maps look like: they involve color coding and also possibly symbols to denote different lines as well as marking stops and important junctions. These maps aren’t necessarily about geography but about a coherent traffic map that showcases the lines and the broad outlines of a city. Some maps, particularly London’s, are quite famous for their design.

So what happens if people are presented with transit maps that convey other bits of information? Could they easily understand them? Looking at all six, the one that might be the most difficult is the best movies map as it would take a little time to figure out how the movies are all connected and the map also implies the movies are derived or connected to each other in significant ways (is the genre of movie enough?).

Flipping the question around, could transit system data be easily “translated” into another genre of maps or data presentation?

Mapping secessionist petitions by county as well as looking at gender

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A sociologist and a graduate seminar took data from petitions for secession from the United States as listed on whitehouse.gov and mapped the patterns. Here is the map and some of the results:

While petitions are focused on particular states, signers can be from anywhere. In order to show where support for these secession was the strongest, a graduate seminar on collecting and analyzing and data from the web in the UNC Sociology Department downloaded the names and cities of each of the petition signers from the White House website, geocoded each of the locations, and plotted the results.

In total, we collected data on 862,914 signatures. Of these, we identified 304,787 unique combinations of names, places and dates, suggesting that a large number of people were signing more than one petition. Approximately 90%, or 275,731, of these individuals provided valid city locations that we could locate with a US county.

The above graphic shows the distribution of these petition signers across the US. Colors are based proportion of people in each county who signed, and the total number of signers is displayed when you click or hover over a county.

We also looked at the distribution of petition signers by gender. While petition signers did not list their gender, we attempted to match first names with Social Security data on the relative frequency of names by sex. Of the 302,502 respondents with gendered names, 63% had male names and 38% had female names. This 26 point gender gap is twice the size of the gender gap for voters in the 2012 Presidential election. For signatures in the last 24 hours, the gender gap has risen to 34 points.

So it looks like the petition signers are more likely to be men from red states and more rural counties. On one hand, this is not too surprising. On the other hand, it is an interesting example of combining publicly available data and looking for patterns.