This is a piece I’ve been sitting on for a little while now, okay half a year now. There isn’t too much to it as it’s an illustration overlay on a satellite photo. But the graphic supports an article about the construction of a new roundabout in Philadelphia, coincidentally where I used to live.
That intersection is…tricky to navigate at best as a pedestrian because there are six and a half streets converging at the junction—I give a half to Arizona St because, well, you’ll see shortly. When I lived in the neighbourhood I saw several near accidents between vehicles and pedestrians and vehicles and cyclists. Anything to help improve the safety will be welcome. And that improvement is what the Philadelphia Inquirercovered back in January.
This definitely fits in the category of well done, small graphics. Not everything needs to be large and interactive. This does a great job by using transparency over the satellite image and layering illustration atop the photo.
Now if we could only restore the old rails on Trenton Ave to be some kind of tram/trolley or light rain corridor. Regardless, there are some good restaurants and drinks options in the neighbourhood, so maybe I’ll have to go investigate in person now that going out is an option again. You know, to a do a proper follow-up.
After looking this week at the growth of the physical size of cities due to improvements in transport technologies, the increasing density of cities, and then the contribution of automobile (especially personal cars) to carbon dioxide emissions, today we look at a piece from the Transport Politic comparing US and French mass transit ridership to see whether the recent decline in US ridership is inevitable or a choice made by consumers and policymakers. Spoiler: it’s not inevitable.
The article makes use of a few graphics and an interactive component. The lead-in graphic is a nice line chart that runs with the spaghetti nature of the graphic: lots of line but only two are really highlighted.
Light grey lines and light blue lines encode the US and French cities under study. But only the lines representing the averages of both the US and France are darkly coloured and in a thicker stroke to stand out from the rest. Normally I would not prefer the minimum of the y-axis being 50%, but here the baseline is actually 100% so the chart really works well. And interestingly it shows that prior to the Great Recession, the United States was doing better than France in adoption of mass transit, relative to 2010 numbers.
But then when you directly compare 2010 to 2018 for various US and French cities, you get an even better chart. Also you see that French cities reclaim the lead in transit growth.
These two static graphics, which can each be clicked to view larger, do a really great job of cutting through what some might call noise of the intervening years. I do like, much like yesterday’s post, the comparison of total or aggregate ridership to per capita numbers. It shows how even though New York’s total ridership has increased, the population has increased faster than the ridership numbers and so per capita ridership has declined. And of course as yesterday’s post examined, in the States the key to fighting climate change is reducing the number of people driving.
What I cannot quite figure out from the graphic is what the colouration of the lines mean. I thought that perhaps the black vs. grey lines meant the largest cities, but then LA would be black. Maybe for the steepest declines, but no, because both LA and Boston are grey. I also thought the grey lines might be used when black lines overlap to aid clarity, but then why is Boston in grey? Regardless, I like the choice of the overall form.
But where things go really downhill are the interactive charts.
Talk about unintelligible spaghetti charts. So the good. The designer kept the baseline at 100% and set the min and max around that. After that it’s a mess. Even if the colours all default to the rainbow, the ability to select and isolate a particular city would be incredibly valuable to the user. Unfortunately selecting a city does no such thing. All the other cities remain coloured, and sometimes layered atop the selected city.
I would have thrown the unselected cities into the greyscale and let the selected city rise to the top layer and remain in its colour. Let it be the focus of the user’s attention.
Or the designer could have kept to the idea in the first graphic and coloured American cities grey and French cities light blue and then let the user select one from among the set and compare that to the overall greyed/blued masses and the US and French averages.
Overall, it wasn’t a bad piece. But that final interactive bit was questionable. Unfortunately the piece started strong and ended weak, when the reverse would have been preferable.
The last two days we looked at densification in cities and how the physical size of cities grew in response to the development of transport technologies, most notably the automobile. Today we look at a New York Times article showing the growth of automobile emissions and the problem they pose for combating the greenhouse gas side of climate change.
The article is well worth a read. It shows just how problematic the auto-centric American culture is to the goal of combating climate change. The key paragraph for me occurs towards the end of the article:
Meaningfully lowering emissions from driving requires both technological and behavioral change, said Deb Niemeier, a professor of civil and environmental engineering at the University of Maryland. Fundamentally, you need to make vehicles pollute less, make people drive less, or both, she said.
Of course the key to that is probably in the range of both.
The star of the piece is the map showing the carbon dioxide emissions on the roads from passenger and freight traffic. Spoiler: not good.
Each MSA is outlined in black and is selectable. The designers chose well by setting the state borders in a light grey to differentiate them from when the MSA crosses state lines, as the Philadelphia one does, encompassing parts of Pennsylvania, New Jersey, Delaware, and Maryland. A slight opacity appears when the user mouses over the MSA. Additionally a little box remains up once the MSA is selected to show the region’s key datapoints: the aggregate increase and the per capita increase. Again, for Philly, not good. But it could be worse. Phoenix, which surpassed Philadelphia proper in population, has seen its total emissions grow 291%, its per capita growth at 86%. My only gripe is that I wish I could see the entire US map in one view.
The piece also includes some nice charts showing how automobile emissions compare to other sources. Yet another spoiler: not good.
Since 1990, automobile emissions have surpassed both industry emissions and more recently electrical generation emissions (think shuttered coal plants). Here what I would have really enjoyed is for the share of auto emissions to be treated like that share of total emissions. That is, the line chart does a great job showing how auto emissions have surpassed all other sources. But the stacked chart does not do as great a job. The user can sort of see how passenger vehicles have plateaued, but have yet to decline whereas lorries have increased in recent years. (I would suspect due to increased deliveries of online-ordered goods, but that is pure speculation.) But a line chart would show that a little bit more clearly.
Finally, we have a larger line chart that plots each city’s emissions. As with the map, the key thing here is the aggregate vs. per capita numbers. When one continues to scroll through, the lines all change.
Very quickly one can see how large cities like New York have large aggregate emissions because millions of people live there. But then at a per capita level, the less dense, more sprawl-y cities tend to shoot up the list as they are generally more car dependent.
Credit for the piece goes to Nadja Popovich and Denise Lu.
Yesterday we looked at the expansion of city footprints by sprawl, in modern years largely thanks to the automobile. Today, I want to go back to another article I’ve been saving for a wee bit. This one comes from the Economist, though it dates only back to the beginning of October.
This article looks at the different ways a city can achieve density. Usually one things of soaring skyscrapers, but there are other paths. For those interested, the article is a short read and I won’t cover it here. But for the sake of the graphic below, there are three basic paths: coverage, height, and crowding. Or to put in other terms, how much of the city is covered by homes, how tall those homes go, and how many people fit into each home.
I really like this graphic. It does a great job of using small multiples to compare and contrast three cities that exemplify the different paths. Notably, it keeps each city footprint at the same scale, making it easier to see things such as why Hong Kong builds skyward. Because it has little land. (It is, after all, an island and the tip of a peninsula.)
One area where I wish the graphic had kept to the small multiples is its display of Minneapolis. There, the scale shifts (note the lines for 5 km below vs. Minneapolis’ 10 km). I think I understand why, because the sprawling city would not have fit within the confines of the graphic, but that would have also hammered home the point of sprawl.
I should also point out that the article begins with a graphic I chose not to screenshot, but that I also really enjoy. It uses small multiples to compare cities density over time, running population on the x-axis and people per hectare on the y-. It is not a perfect graphic (it uses I think unnecessary arrowheads at the end of the line), but scatter plots over time are, I think, an underused graphic to show how two variables (ideally related) have moved in tandem over time.
Overall, this is a strong piece from the Economist.
Credit for the piece goes to the Economist graphics department.
This is an older piece from back in August, but I was waiting for a time when I would have some related articles to post alongside it. To start off the series of posts, we start with this piece from CityLab. As my titles implies, it looks at the growth of cities, but not in terms of people or technology but in terms of area/land.
The basic premise is that people look for a 30-minute commute and have done so throughout history. To make that point, the authors look at how transport technology evolved to enable people to live and work at further distances from each other, expanding the urban core.
The designer then chose to overlay the city limits of several cities largely defined by these technologies atop each other.
Conceptually the graphic works really well. The screenshot is of an animated. gif leading into the article that step-by-step reveals each city. However, throughout the article, each de facto section is introduced by a city outline graphic.
The graphic does a really nice job of showing how as technology allowed us to move faster, people chose to be further removed from the city core. Of course there are often multiple factors in why people may move out of the core, but transport certainly facilitates it.
Last week was the climate summit in New York, and the science continues to get worse. Any real substantive progress in fighting climate change will require sacrifices and changes to the way our societies function and are organised, including spatially. Because one area that needs to be addressed is the use of personal automobiles that consume oil and emit, among other things, carbon dioxide. But living without cars is not easy in a society largely designed where they are a necessity.
But over at CityLab, Richard Florida and Charlotta Mellander created an index trying to capture the ability to live without a car. The overall piece is worth a read, but as usual I want to focus on the graphic.
It’s nothing crazy, but it really does shine as a good example of when to use a map. First, I enjoy seeing metro maps of the United States used as choropleths, which is why I’ve made them as part of job at the Philly Fed. CityLab’s map does a good job showing there is a geographic pattern to the location of cities best situated for those trying to live a car-free life. Perhaps not surprisingly, one of the big clusters is the Northeast Corridor, including Philadelphia, which ranks as the 17th best (out of 398) and the 7th best of large metro areas (defined as more than one million people), beating out Chicago, ranked 23rd and 8th, respectively.
Design wise I have two small issues. First, I might quibble with the colour scheme. I’m not sure there is enough differentiation between the pink and light orange. A very light orange could have perhaps been a better choice. Though I am sympathetic to the need to keep that lowest bin separate from the grey.
Secondly, with the legend, because the index is a construct, I might have included some secondary labelling to help the reader understand what the numbers mean. Perhaps an arrow and some text saying something like “Easier car-free living”. Once you have read the text, it makes sense. However, viewing the graphic in isolation might not be as clear as it could be with that labelling.
Though the temperatures might not always feel it, at least in Philadelphia, summer is ending and autumn beginning. Consequently I wanted to share this neat little work that explores urban heat islands. Specifically, this post’s author looks at Massachusetts and starts with a screenshot of the Boston area.
The author points out that the Boston Common and Public Garden are two areas of cool in an otherwise hot Boston. He also points out the Charles River and the divide between Boston and Brookline. I would like to add to it and point out the Fens and the Emerald Necklace.
I wonder if a scale of sorts would help, though the shift from warm yellows and reds to cooler greens and blues certainly helps differentiate between the cooler and warmer areas.
I wish I had more for this post. Saturday morning’s New York Times was delivered with this on the front page, above the fold. It promised a special section including graphics that showed every building in the United States with a pullout poster of a large major city.
I have been through my Sunday paper twice now and cannot find the maps. So while I would love to see the full work, and then probably share a bit of it with all of you, I cannot. Instead, we can only look at the above. Even there though, you can begin to get a sense of the different types of spatial arrangements our cities exhibit.
Credit for the piece goes to the New York Times graphics department.
Yesterday the Economist posted a graphic about Chinese urban clusters, of which the Chinese government is planning to create 19 as part of a development strategy. In terms of design, though, I saw it and said, “I remember doing something like that several years ago”.
The Economist piece looks at just the geography of the Chinese clusters. It highlights three in particular it discusses within the article while providing population numbers for those clusters. Spoiler: they are large.
The Economist graphic does little else beyond labelling the cities and the highlighting of the three features clusters. But that is perfectly okay, because that was probably all the graphic was required to do. I am actually impressed that they were able to label every city on the map. As you will see, we quickly abandoned that design idea.
So back in 2015, using 2014 data, my team worked on a series of graphics for a Euromonitor International white paper on Chinese cities. The clusters that the analysts identified, however, were just that, ones identified by researchers. Since the Chinese government had not yet created this new plan.
We also looked at more cities and added some vital context to the cluster map by working to identify the prospects of the various Chinese provinces. Don’t ask me what went into that metric, though, since I forget. The challenge, however, was identifying the four different tiers of Chinese city and then differentiating between the three different cluster types while overlaying that on a choropleth. Then we added a series of small multiples to show how now all provinces are alike despite having similar numbers of cities.
Credit for the Economist piece goes to the Economist Data Team.
Credit for the Euromonitor piece is mine. I would gladly give a shoutout to those that worked with me on that project…but it’s been so long I forget. But I’m almost certain both Lindsey Tom and Ciana Frenze helped out, if not on that graphic, on other parts of the project.
I have lived in Philadelphia for almost ten months now and that time can be split into two different residences. For the first, I took the El to and from Centre City. For the second, I walk to and from work. I look for living spaces near transit lines. In Chicago I took the El for eight years to get home. But to get to work, I often used the 143 express bus. Personally, I prefer trains and subways to busses—faster, dedicated right-of-way, Amtrak even has WiFi. But, busses are an integral part of a dense city’s transit network. You can cram dozens of people into one vehicle and remove several cars from the road. Here in Philadelphia, however, as the Inquirer reports, bus ridership is down over the last two years at the same time as ride-hailing apps are growing in usage.
For those interested in urban planning and transit, the article is well worth the read. But let’s look at one of the graphics for the article.
The map uses narrow lines for bus routes and the designer wisely chose to alternate between only two shades of a colour: high and low values of either growth (green) or decline (red). But, and this is where it might be tricky given the map, I would probably dropdown all the greys in the map to be more of an even colour. And I would ditch the heavy black lines representing borders. They draw more attention and grab the eye first, well before the movement to the green and red lines.
And the piece did a good job with the Uber time wait map comparison as well. It uses the same colour pattern and map, small multiple style, and then you can see quite clearly the loss of the entire dark purple data bin. It is a simple, but very effective graphic. My favourite kind.
Anyway, from the data side, I would be really curious to see the breakout for trolleys versus busses—yes, folks, Philly still has several trolley lines. If only because, by looking at the map, those routes seem to be in the green and growing category. So as I complain to everyone here in Philly, Philly, build more subways (and trolleys). But, as the article shows, don’t forget about the bus network either.
Credit for the piece goes to the Inquirer graphics department.