New World Meets Old World: How did designers create the NASA ESW Mapping Our World poster? It was a challenge!
I was led to this from a wonderful article by Catlin Dempsey at GIS Lounge.
Game on! Challenge accepted! If someone tells me that a project idea I have is too hard to do, I consider it a personal challenge. And that was my reaction as planning began for a NASA poster to highlight the theme of “Mapping Our World” for Earth Science Week (ESW) October 13-19, 2013.
The initial idea was to highlight a variety of missions as a mosaic, similar to a recently released poster of the sun. The sun poster is a beautiful piece that displays the variety of wavelengths used by NASA missions to observe the sun. Since the NASA missions that observe Earth also use a broad region of the electromagnetic spectrum to produce data about numerous aspects of our Earth system, it seemed like the perfect complement to this earlier poster. This coalesced into a fantastic idea that eventually became the NASA ESW poster (download your copy here).
Once we had a few datasets in the stereographic projection, it was time to start slicing and dicing. The first draft revealed many of the challenges we were up against. Since this is not a type of projection people see everyday, we needed to be sure the shapes of the continents were prominent, otherwise it would look like a couple of bowls of candy. This is tricky if you pick a data set with clouds (such as Hurricane Sandy in the Atlantic) where you lose the coastline completely.
Jesse Allen also played around with data that were not on a global scale such as Landsat data. While the concern for showing clear coast lines is not such as issue inland, the images can allude to false features – such as the appearance of a giant lake with rivers covering the Taklimakan Desert in Western China (courtesy of Corbis Images) or a huge massif, which is a large mountain mass, in Northern Africa.
We explored a few different ways to fit data sets together. Sometimes a good idea doesn’t prove to be as compelling when it gets mapped. For example, we thought it would be interesting to weave together blocks of different data sets that had a relationship to each other such as those relating the El Niño Southern Oscillation (ENSO). During an El Niño event, an area of unusually warm, sea-surface temperatures develops in the Pacific Ocean off the western coast of South America. This causes higher sea surface heights and changes in rainfall. Jesse tried placing these data sets next to each other across the central Pacific but it didn’t look that good and it was difficult to tell the story visually.
Another really fascinating data set we used was the new Raytheon VIIRS lights at night (Black Marble) imagery. At night, places with few lights (such as rural southern Africa) are very hard to tell from places with no lights (such as the middle of oceans). Jesse explored choosing tiles of data in the Black Marble only where there were lots of cities. This seemed to work for Europe, but in southeastern Australia there just were not enough features to tell land from sea. A different data set would be required.
Overall, I found the areas where a ‘checker pattern’ emerged were the most interesting. Adjacent blocks of the same data set created large areas of similar color and contrast and seemed out of place (such as northern South America and in the Arctic). Some groupings we found to be beneficial, such as the Landsat Mosaic of Antarctica. Later we would add the Ozone Hole to the right side for balance. But wherever possible, I tried to maintain a ‘checkering’ distribution of the data sets. Read more.
Editors Note: Special thanks to the good folks at Wikipedia for being there for us all during this government shut-down, as any Federal link goes to one shuttered page. If you can, please contribute to this noble encyclopedia!