Understanding Spatial Data
In this lesson we’ll focus on spatial data itself – it’s what makes maps possible. To be a fabulously awesome geographer you need to understand how spatial data is created, who makes it, and what its limitations are.
Where are we now?
It all begins with measuring location. Back when dragons prowled the oceans and headache relief was achieved by drilling a hole in your head, location was measured rather simply by taking angular measurements using the sun, moon, or stars. These methods are still taught and used by some today, but since this MOOC isn’t about sailing a Sloop to pick up spices in the Orient, I want to focus instead on how locations are measured today.
You’re probably thinking, “Yeah, I know, everything uses GPS to know where things are.” And if I asked you how GPS works, you’d say, “Yeah, Google invented it and there are Magic Laser Genies that send location beam particles to my iPhone.” And that would be incorrect.
The Global Positioning System (GPS) is no doubt one of the most important methods we have available today for measuring locations. GPS is the system designed by the United States starting in the 1970s, originally for military purposes, to provide location services around the world using satellites. GPS is one example of a Global Navigation Satellite System (GNSS). There are several others, like the Russian GLONASS (jeez, awkward acronym - comrades) system or the European Union’s Galileo system. Every GNSS works using the same general principle. You need a network of satellites in space to broadcast signals down to Earth that include position information about the location of each satellite as well as the exact time when the signal was sent. A GNSS receiver (like the GPS antenna on your fancy phone) can listen for these signals and compare the times/locations from multiple satellites to triangulate your exact location on Earth.
There’s much more to learn about GPS and GNSS if you’re so inclined. It’s quite a bit more complicated than my explanation might imply. For example, these systems only work when you have line-of-sight to a collection of satellites (which is why your Garmin is no good if you drive into a parking garage), and there’s an enormous amount of math going on to deal with signals that are constantly moving while you are moving yourself. You can also combine these satellite signals now with cell phone tower signals, wi-fi signals from routers, and other sources to improve accuracy and coverage.
The bottom line is that in the last decade it’s become much more likely for normal people to have access to handheld devices that use a GNSS to determine locations. The consumer-grade stuff you have in your phone or car can figure out where you are to within a few meters in some conditions, while in others you may be several hundred meters off target. Professional surveying equipment using big antennas and fancier computing hardware/software can be accurate to within several centimeters. If you’re trying to find the nearest curly fries while you’re sailing down the highway on a road trip, consumer-grade accuracy will do just fine. If you’re deciding exactly how much property tax someone should pay, you want to have the hardcore professional stuff.
If I use the GPS on my phone, I can see that I'm sitting at Latitude: 40.77004, Longitude: -77.896744 in my house writing this lesson. If I save that information I’ve effectively got a point location on Earth. If I walked around my house collecting multiple points, I could create a polygon by connecting multiple points. If I collected points in a row walking the shortest distance straight from my couch to the fridge (to retrieve delicious chocolate pie) I could connect them and have a line feature. These three location types (point, line, and polygon) comprise the spatial data foundations of modern Geographic Information Systems (GIS). They are considered vector data, because they can represent any kind of geometry. The other major data type is raster data which we’ll cover in the next section.