[MUSIC] Welcome to the lecture on projections. In this lecture, we'll cover what projections and coordinate systems are, some common projections and coordinate systems, the attributes of projections that effect when you would use them, and how you view projection information in Arc GIS. To start with, if I was to tell you the location of something as being 55 meters away in the x direction and 41 meters away in the y direction, where is this item located? It all depends on where those coordinates are relative to. Are they relative to me right now? Or are they relative to some standardized location on the earth? This distinction is very important. Packed into that description I just gave you are two important concepts about geographic data. Number one, I gave you a unit of measure for our coordinates in meters. Without units, distances are meaningless. And number two, we need to have a reference point with a known location in order to locate items with these coordinates. This reference point is often called a datum and it's effectively a model of the Earth's surface that coordinate systems can be built on. Together, these two concepts form the basis for a coordinate system. Not all data uses the same coordinate system. Far from it. And to be displayed on the same map, your data doesn't need to be stored in the same coordinate system. But the GIS software does need to convert your data to the same coordinate system behind the scenes. This will intuitively make sense because you have different reference points and different coordinates. How can you overlay them without some conversion to a common system. Building on coordinate systems is the concept of projections. The term projection is often used interchangeably with coordinate systems, and you may hear me make that mistake occasionally. But, in fact, they are different, and projections build on coordinate systems. So to start with, what is a projection? Projections help us display the earth on a flat surface like your screen or a sheet of paper. While it may not be intuitive at first, we can't just flatten the Earth easily to fit on your screen. To help illustrate this concept, let's try to imagine flattening a sphere. Just like we would have to do to display the Earth on your screen. Imagine an inflated spherical ball, just like a football, or a soccer ball for you Americans. Let's cut it down the side from top to bottom so that the interior hollow part is exposed. To make it even easier to visualize it we can cut it into completely into halves so that we can set the cut side on the ground. We now have half the ball sticking up off the ground but there's no easy way to completely flatten it so the skin of the ball is against the ground. If this ball was the Earth, we would need to stretch and distort it in order to get it completely flat to display on your screen or on paper. This set of stretches and distortions is what a projection is. When working on a two-dimensional surface like computer screen, we get some benefits out of working with projected data. First, lengths and angles can be constant across the two dimensions which we can't always say about our geographic coordinate system. Think about the lines of longitude and how they converge at the poles. The distance between the degree of longitude at the poles is very different than the distance between the same degrees at the equator. Projected coordinate systems have uniform distances and map units regardless of location, as well. This lets us identify locations by X, Y coordinates on a grid. To bring this all together, to build a geographic coordinate system we need an accurate model of the Earth's surface. From there, coordinate systems are built. And building on that are projected coordinate systems. Now, we don't get this translation of our data to a 2D surface for free, there are trade offs. When we project geospatial data, you end up creating distortions. Distortions can occur in the shape, the area, the distance, or the direction of the data. Different projections are created to optimize for these distortions so some projections are good at preserving local shape. These are called conformal projections. Others preserve the area of the features. These are called equal area projections and still others preserve distances between points on the map. These are called equidistant projections. In practice a projection must restore at least one attribute. Shape, area, distance, or direction. Different projections also optimize these attributes for different locations on the earth, and others do it for the entire earth. The result is a large number of projections optimizing for different attributes and different locations. Depending on the work that you're doing, you will find yourself needing different projections and coordinate systems. So now let's take a look at some projections. Before we do that, let's take a look at the earth on a sphere. We'll start by looking at Africa, and then we're going to compare it to the size of Greenland. Since Africa is near the equator, it's shown closer to its true size in this often undersized relative to the rest of the world on a world wide projection. In contrast, Greenland is oversized by virtue of being near the poles where more distortion occurs. But on this sphere, both are shown at their correct relative size. So keep these size differences in mind as we look at the following map projections. The first projection here is the equirectangular projection. It results from simply taking the angular coordinates of the globe and plotting them as if they are linear coordinates on a sheet of paper. So as you get closer to the poles, you have more distortion as the meridians, your lines of longitude, stay the same with the part on the sheet of paper instead of converging as they do on the globe. It's a common choice in GIS software for displaying data stored in a geographic coordinate system. I want you to note right here the size of Greenland relative to Africa as well. Next up is the Mercator projection. You've probably seen quite a bit of this projection as it's very common on the Internet. A variant of the Mercator projection is used to most mapping applications online. Note that in this projection, Greenland is about as big as Africa, much, much larger than it should be. The distortion is the result of this projection preserving angles in order to aid a navigation and sacrificing sizes as a result. It's an instance of a conformal projection. Now, take a look at the Mollweide projection. It is an equal area projection, which means that area is preserved within the map. Note that Greenland is it's appropriate size relative to Africa, but we've distorted the shape of all of these locations in order to get the appropriate areas. So far the projections we've looked at have been very simple and optimized for displaying things around the world. As a result the distortions that we have in our maps are greater, the Universal Transverse Mercator or UTM for short, projection, tries to account for this by creating a series of nearly identical projections that optimize for each area of the planet. If you want to understand more details of exactly how it does this, you'll need to take the rest of the courses in the specialization, but for now we'll show you enough to use it. The UTM projection divides the earth into 120 zones, 60 in the north and 60 in the south. Each of these zones is 6 degrees of longitude wide. Since this is just a rotated Mercator projection, we're minimizing distortion by effectively making each location have the properties that exist near the equator in the standard Mercator projection. In doing this, we minimize the distortion of area that occurs in the Mercator projection while getting the benefit of preserving angles. You can still display locations that are outside of each zone, but they become more distorted as they do in a Mercator map. This projection is very useful, and I encourage you to look up the zone that you are in as it could become a common part of your mapping. The last thing we're going to do in this lecture is take a quick look at how projections are used in Arc GIS. Remember that maps themselves have their own projections and coordinate systems that they use, and you'll learn how to set that when we talk about data frames in a later lecture. In the meantime, if you are wondering what coordinate systems data set uses, you can find out by going to the source tab of the layer properties pallet, and scrolling through the information. There, you'll see information about the projected coordinate system, if the data has one, as well as the geographic coordinate system that is built on. And one final thing I want to mention is that it's possible to change the projection of the underlying data and transform the coordinates from one coordinate system to another. Arc GIS has tools for this. But you don't need to know how to use them yet. Just keep in mind that it's possible using tools and GIS software. That's it for this lecture on projections. In this lecture, you learned what projections and coordinate systems are, some ways to distinguish them, some common projections, and how to view that projection information in Arc GIS. See you next time.