The map has many of the design virtues common in graphics from the Times (clean, focused on the data, clearly labeled, small multiples), but when I first viewed it I had trouble parsing the data. It took me a while to figure out that hazard was indicated by color, and the size of each circle denoted ancilliary information (population).
It turns out that our eyes & brains perceive area more strongly than color. Here’s a list of ways to visually compare quantities (described by Bang Wong in his Points of View column for Nature Methods), in order from easiest to hardest:
- Positions on a common scale
- positions on the same but nonaligned scales
- angles, slopes
- volume, color saturation
- color hue
I suspect I’m not the only person who would consider the size of the circles more important than the color, and assume size was correlated with hazard. I had to carefully read the key to figure out the proper way to read the map. Perhaps using size to encode hazard, and color (or opacity, or icons) for population would have worked better.
I recently had the opportunity to attend & give a presentation at the 2011 International Symposium on Remote Sensing of the Environment in lovely Sydney, Australia. (OK, not so recently—the conference ended on the April 15th. I blame jetlag.) Just over 60 people turned up for the talk, which was mostly about our visualization of Eyjafjallajökull. (Which means I had to attempt to learn how to pronounce “Eyjafjallajökull.” Luckily I don’t think anybody made it from Iceland to Sydney to critique me.) If you’re interested, I’ve posted Keynote and PDF copies (originally prepared for last years’s fall AGU).
During sessions many of the talks were a bit on the technical side for me, so I ended up preparing material for NASA’s portable “hyperwall”—9 HDTV screens linked together. It’s useful for either high-res animations, or small multiples. With relatively thick bezels on the monitors, simultaneous display of 9 images worked particularly well:
Compare the small multiples on the hyperwall with the sequential display of the same images from the Earth Observatory’s World of Change.
During my talk I promised the audience that I’d update the blog more frequently, so there should be more posts in the future. I sometimes struggle for good ideas, so if you have a suggestion, please drop a note in the comments.
One of the best things about international travel (at least to a geek like me) is to see how different cultures approach design and signage. Here’s a few from Blue Mountains National Park, near Sydney, Australia.
Russia’s Kamchatka Peninsula is perhaps the most volcanically active spot on the planet. Last week’s Global Volcanism Program weekly report (for February 16–22, 2011) listed three Kamchatkan volcanoes currently in eruption—Karymsky, Kizimen, and Shiveluch—and two others—Bezymianny and Klyuchevskaya—were mentioned earlier in February. In one overpass a NASA satellite captured four of these volcanoes in one narrow overpass, only 60 kilometers wide and 300 kilometers long. All of them exhibit plumes. I zoomed in on the most spectacular—Kizimen and Shiveluch—for our Natural Hazards section, but I’d like to share Klyuchevskaya (below) and the entire image—all 9,822 by 20,729 pixels of it (13 MB JPEG).
NASA Earth Observatory image by Robert Simmon, using data from the NASA/GSFC/METI/ERSDAC/JAROS, and U.S./Japan ASTER Science Team.
A few weeks ago I stumbled on this headline and image from the UK Daily Mail Online:
World of two halves! Map shows most of Northern Hemisphere is covered in snow and ice.
Most of the Northern Hemisphere was covered in snow and ice a few weeks ago? (The image dates from late January/early February—I couldn’t find the exact date.) Really? At first glance it’s a plausible claim, but there’s a problem. The map is in a cylindrical equirectangular projection, which distorts relative areas—regions north and south of the equator appear larger on the map than they are in reality. The higher the latitude, the larger the exaggeration. As a result, a much higher percentage of the Earth’s surface appears to be covered in snow or ice than really is.
After transforming the map to an equal-area projection (in this case Mollweide, which also preserves straight lines of latitude) it’s obvious that most of the Northern Hemisphere remains snow and ice free, even in mid-winter:
A map showing just the Northern Hemisphere (azimuthal equal area, centered on the North Pole) makes is yet more clear:
For maps of measured quantities on the Earth’s surface (like snow, temperature, rainfall, or vegetation) it’s important to choose a projection carefully, to minimize misunderstandings of the underlying data. It’s far too easy for a map to exaggerate one area at the expense of another. It’s also important to keep projections consistent when displaying a time series, or comparing datasets to one another.
Despite the major flaw of not being equal area, cylindrical equirectangular (which goes by many other names) is very useful: it’s the standard projection for importing into a 3D program and wrapping around a sphere, and it’s easy to define the corner points and scale for import into software to transform to other map projections. I did all the reprojections with the excellent tool G.Projector, which I’ve written about before.
For more information about map projections, see the USGS page Map Projections, the National Atlas’ Map Projections: From Spherical Earth to Flat Map, and the Wolfram Mathworld Map Projection site. For an in-depth discussion, read Map Projections—A Working Manual, (PDF) also from the USGS.
(As far as I can tell, the snow and ice map was originally from the NOAA Environmental Visualization Laboratory. Unfortunately, I couldn’t find archived images on their site, so I had to use the original low resolution and highly compressed image from the Daily Mail.)
Over the past week or two, there has been severe flooding in Australia, Brazil, Sri Lanka, and the Phillipines, but all we’ve shown on the Earth Observatory is the flooding in Australia. Why? Here’s a sampling of images of Rio de Janeiro since January 12:
Earth is cloudy. Especially in the tropics. Even more especially when there’s enough rain to cause flooding. The satellite imagery we have easy, fast, and free access to (for example, check out the twice daily MODIS imagery of São Paulo) is primarily based on visible and infrared light, which can’t penetrate clouds, so for many floods we can’t show anything useful.
In addition, the damage in Brazil, Sri Lanka, and the Philippines was caused by flash floods, landslides, and debris flows, which are all much smaller scale than the rivers overflowing their banks near Brisbane. In satellite imaging there’s a tradeoff between spatial resolution (detail) and temporal resolution (frequency) so there are fewer opportunities to capture the high resolution data necessary to show relatively localized events. To view something like a landslide, we have to have both a break in the clouds and the opportunity to aim a high resolution sensor. Which occurred this morning:
With clear skies and an overpass of Earth Observing-1, we may have an image of Teresopolis, Brazil by tomorrow.
P.S.: Despite the dispassionate view afforded by satellites, my thoughts go out to the victims and their families.
Update: For some reason the satellite never acquired the data, and the next viewing opportunity won’t be for another few days.
I got back from AGU last Saturday, picked up the pups from the kennel, and now I’m getting things together here so I can go on vacation right after Christmas.
As always it’s an overwhelming conference—there’s probably 1,000 posters on the floor at any given time, and at least ten simultaneous sessions. I got some very good ideas wandering through the posters (a map of ice flow speed for all of Antarctica, research on a paleo lake in Kenya, and a global dataset of limiting factors for tree growth being highlights) that I’ll hopefully be working on in the New Year. Tuesday’s special session on communicating climate change was also worthwhile (and packed). I think both my talks went pretty well, even if I can’t pronounce Eyjafjallajökull—despite professional help from a native Icelandic speaker. One conclusion we came to in the visualization session: it would be helpful for AGU to start promoting good visualization techniques. I plan on following up on that, hopefully I’ll have more to say soon.
A few words of advice for poster presenters (I originally planned on showing some examples of good and bad design, but chickened out). White space is good: try not to jam your poster full of every last detail of your research. Do not use Comic Sans (avoid it on slides, too). Seriously. Your research may be groundbreaking, but it’s hard for me to take you seriously if you try to be cute. Especially since the new Microsoft typefaces that ship with Vista, Windows 7, and recent versions of Office are very, very good. Make your graphics big. Avoid the rainbow palette. (I’ll have more to say about this—a lot more—soon. It was a big part of my Eyjafjallajökull talk.) Print up a one-page summary to distribute. Include a conclusion, written for non-experts. Your poster will be up all day, you’ll only be there for an hour or two. Finally: if you can figure out a way to add multimedia, do it. Rolf Hut of the Delft University of Technology had an amazing, temperature-sensing interactive LED display:
If anyone is going to the AGU fall meeting in San Francisco and would like to know more about the Earth Observatory and/or data visualization, I’ll be giving two talks, both on Thursday the 16th:
The Communication Strategy of NASA’s Earth Observatory at 8:45 a.m. in session ED41D. Climate Change Adaptation: Education and Communication I.
Visualization Case Study: Eyjafjallajökull Ash at 1:55 p.m. in session ED43B. Visualization of Geophysical Processes for Science, Education, and Outreach II.
I’ll be there all week, so if you want to meet to chat (or know of any sessions you think I’d be interested in, or excellent restaurants), send a message to the “Design Feedback” topic on our contact page, and I’ll get back to you.
One of my (many) pet peeves in data visualization is vertical exaggeration. For example, here’s a 3D rendered view (from the south looking north) of Mount Etna:
Compared to the real thing, photographed from the International Space Station (from the north looking south):
The 3D view is scaled so the volcano appears much higher than it does in real life—perhaps four or five times higher—but it’s impossible to tell since the caption doesn’t say. My big problem with this is that Etna looks like a classic, steep-sided stratovolcano (like Mount Fuji), rather than a complex mountain formed from a combination of viscous lavas (typical of stratovolcanoes), fluid lavas typical of shield volcanoes (like the Hawaiian Islands), and collapses (like Mount St. Helens).
At least it’s not as bad as the infamous image of Maat Mons on Venus, which has a staggering vertical exaggeration of 22.5 times (Maat Mons is actually shaped more like a wad of gum on the sidewalk, not Mount Rainier):
Why does it matter? Because topography gives clues to the underlying geology and processes that form a landscape. For example, the angle of the walls of the Grand Canyon is determined by the rock type: hard rocks form cliffs, soft rocks form slopes. The vertical granite walls of Yosemite are composed of hard granite that resisted the erosion of ice age glaciers.
The reason for the shape of mountains on Venus is perhaps even more interesting. It’s so hot on the surface (465°C) that most of the rocks creep: over time solid materials deform under their own weight. This limits the height of mountains on Venus, and ensures that steep slopes—if they exist at all—are extremely rare (and likely indicative of active tectonics). The vertical exaggeration used in images of Venus’ surface obscures some of the fundamental processes that shaped the planet.
One final note: If you absolutely have to use vertical exaggeration, at least indicate that fact in the caption, or even better, include a scale on the image itself.