Ten years ago, in February 2000, NASA mapped the entire world in eleven days.
It’s true: the mission was called the Shuttle Radar Topography Mission (SRTM), and over the course of eleven days, it used a big radar attached to space shuttle Endeavour to get elevation data from the vast majority of solid Earth; practically all land between 60 degrees North and 56 degrees South was included, with a resolution of 30 meters (100 feet). Over 9 terabytes of data were captured. It then took two years to process that data and make it usable (and it’s still being refined to this day).
This data is freely available to anyone, and the number of possible applications is almost infinite. It’s been used in GIS, cartography, environmental planning, weather modeling (weather patterns are enormously influenced by the topography), flight simulators, Google Earth, and the list goes on.
I’ve become quite familiar with this data because we used it as one of the base layers in our suite of GIS applications for the iPhone. We simply represented it using color-coding, like in most maps, and adding a bit of shading for effect.
In this short article, I’d like to give you a quick tour of the kinds of things this data can reveal. My hope is to get you thinking about what else could be done with this incredible resource.
So what does the data look like?
Imagine being a blind giant, feeling the surface of the Earth with your fingers and trying to guess what you’re touching — that’s what browsing this data is like.
The big mountains, such as Mt. Rainier in Washington state, look pretty much as you’d expect:
Even modest mountains, such as those of southern Ohio, look crisp and present a clear picture of the region’s topography, with water erosion clearly visible.
Some features are quite noticeable. For instance, can you guess what the following is (it’s in southern California)?
If you guessed that it was some sort of fault, don’t feel bad: that’s what I thought too. But it turns out that it’s just a line of sand dunes east of Mexicali:
Which teaches us that not all linear features are faults, even in California. Though a lot of them are. Here’s a portion of central California showing the San Andreas fault:
And here’s the same area, with an extra layer showing currently active faults (color shows recency of movement, line width shows slip rate):
Down to the bare essentials
Seeing nothing but the terrain turns out to be surprisingly useful. Without the distraction of all the other information that is usually displayed on a map, one can really focus on the shape of the landscape. For instance, central Wisconsin shows a subtle contrast between east and west, with the eastern part being more bumpy, and the western part seeming noticeably smoother (look carefully).
This is the limit of the last glaciation. When the glaciers retreated, they left all kinds of material behind, causing the bumpiness of the terrain in that part of the state. Here’s the same location with an additional layer showing the glacial limit:
Cities and buildings
It should come as no surprise that the radar cannot distinguish between natural and man-made features.
Let’s take a look at downtown Boston — an area not known to be particularly hilly.
These bumps are the downtown skyscrapers — averaged out, since the resolution in this picture is 90 meters (300 feet). The small cluster in the lower left is the John Hancock tower. I added a hydrology layer to make it easier to see, but obviously radar does not know water from land.
Big holes in the ground
Looking at Chicago, I was worried when I first saw what looks like a big hole just outside of the city. Could it be a flaw in the data? Why would there be a 250-foot (~75 meters) deep hole at this location?
It is so large, in fact, that it’s going to be used to store runoff and sewage from the city. There’s one quarry you may not want to go swimming in.
Florida presented some special problems. We thought about not having a terrain layer at all, since the state is so flat (highest point: 345 feet/105 meters, on the border with Alabama). But in some ways, that makes smaller features that much more noticeable. For instance, I was puzzled by this strange hill southwest of Boca Raton (resolution 180 meters/600 feet):
Its top elevation is 177 feet/54 meters in the SRTM data, and that’s practically Everest in Florida. A look at the Google Maps view reveals what it is: a landfill.
In fact, it’s quite notorious. Dubbed Mount Trashmore by the locals, the Broward County Landfill has now reached a height of 225 feet/68 meters, and is the subject of much debate in the area. There is even talk of growing it to 280 feet. Why not take it all the way to 346 feet and make it the highest point in Florida? Perhaps our landfills will be the solution to rising sea levels. I have so many creative solutions like this, but no one will listen to me.
I hope to have given you a quick sense of the potential applications for the data from SRTM. It’s up for grabs. Wikipedia has quite a bit of information about it. What creative use will you make of it?