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You’re probably well aware that NASA has launched numerous spacecraft—some destined for orbit, others to land on distant planets, and some to initiate a galactic handshake beyond our solar system.
Many of these missions have corresponding 3D models. What’s more, NASA has made a number of these available to the public. From satellites and shuttles to rovers and crew modules, more than 300 objects are currently available to download.
Recently, I stumbled upon a NASA dataset containing the distance to the nearest coastline. The data are a rather straightforward calculation based on input from GSHHG—the Global Self-consistent, Hierarchical, High-resolution Geography Database.
Provided as a convenient GeoTIFF, the coastline distances are available in 0.04° and 0.01° resolutions. This makes it ideal for quick exploration. Or a dive down geographic rabbit holes.
One of my favorite places to see in imagery and maps is Glen Canyon National Recreation Area and The Rincon. Here, water meets stone as myriad canyons reach out from the serpentine courses of the Colorado and Escalante Rivers.
There’s something special about topographic maps. Each is different than the next, yet many reflect a canvas replete with smooth contours, pleasing colors, and a technical accuracy that can send both the mind and feet wandering.
Lately I have been challenging myself to read more fiction. The most recent book to be checked off my list is Stephen King’s Pet Sematary. A morbid and suffocatingly dark story, and one I had previously only known from seeing the 1989 film as a kid. (Yes, the book is better. By a long shot!)
Compelling cartography has never been easier or more abundant. We are inundated with new tools and technologies. All the while, one of the most powerful assets in the cartographer’s arsenal is being overlooked: the command line. Using keystrokes to create maps might sound like a task of yesteryear, but I am here to tell you it is a wormhole to the future. Whether you design maps for national parks or newsrooms, the terminal will enable you to supercharge your workflows with speed and elegance. This talk introduced some old tricks and new tools for designers on any deadline.
In Kong: Skull Island, we follow a crew of scientists and military specialists into the thick jungles of an uncharted Pacific island. Encounters with previously unknown creatures abound. Released in 2017, the film is set in 1973 and prominently features a fictional company—Landsat—whose work involves classified satellite data.
But is it all fiction?
A few years ago I made the move from Wordpress to static pages. The benefits were immediate, and it has been nice not worrying about plugins, security patches, or millions of updates since.
“I’m not bivariate, but I am curious.” That quip has been stuck in my mind ever since I overheard it at the 2013 NACIS conference in Greenville, SC. Not only was it perfectly timed after a talk about bivariate mapping, but it rang with a great deal of truth: a lot of folks aren’t creating bivariate maps, but they want to try. While it was just a joke and the person who made it can easily create bivariate maps, most people find them too difficult or mysterious.
That’s a real shame because bivariate choropleth maps are incredibly useful and very easy to make. So let’s go ahead and make one!
In some very real ways, polar sea ice is the backbone of our planet’s climate. When more ice is present, its bright surface tends to reflect sunlight, cooling things down. When there is less white, snow-covered ice, the ocean’s surface becomes a bit darker. A darker ocean surface absorbs more sunlight, causing it to warm. The relationships between climate and ice are much more complicated than that, as the thickness of the ice also influences a variety of subsurface feedback loops that have long-term effects.