Let’s talk about Coordinate Reference Systems (CRSs) again. We’ve touched on this briefly before, but haven’t discussed what it means practically. The CRS that all the data as well as the map itself are in right now is called WGS84. This is a very common Geographic Coordinate System (GCS) for representing data. But there’s a problem, as we will see. Notice the scale changing? That’s because you’re moving away from the one point that you zoomed into at 1:5000000, which was at the center of your screen. All around that point, the scale is different. To understand why, think about a globe of the Earth. It has lines running along it from North to South. These longitude lines are far apart at the equator, but they meet at the poles. In a GCS, you’re working on this sphere, but your screen is flat. When you try to represent the sphere on a flat surface, distortion occurs, similar to what would happen if you cut open a tennis ball and tried to flatten it out. What this means on a map is that the longitude lines stay equally far apart from each other, even at the poles (where they are supposed to meet). This means that, as you travel away from the equator on your map, the scale of the objects that you see gets larger and larger. What this means for us, practically, is that there is no constant scale on our map! To solve this, let’s use a Projected Coordinate System (PCS) instead. A PCS “projects” or converts the data in a way that makes allowance for the scale change and corrects it. Therefore, to keep the scale constant, we should reproject our data to use a PCS. QGIS allows you to reproject data “on the fly”. What this means is that even if the data itself is in another CRS, QGIS can project it as if it were in a CRS of your choice. It turns out that we can zoom between these two layers, but we can’t ever see them at the same time. That’s because their Coordinate Reference Systems are so different. The continents dataset is in degrees, but the RSA dataset is in meters. So, let’s say that a given point in Cape Town in the RSA dataset is about 4 100 000 meters away from the equator. But in the continents dataset, that same point is about 33.9 degrees away from the equator. This is the same distance – but QGIS doesn’t know that! You haven’t told it to reproject the data. So as far as it’s concerned, the version of South Africa that we see in the RSA dataset has Cape Town at the correct distance of 4 100 000 meters from the equator. But in the continents dataset, Cape Town is only 33.9 meters away from the equator! You can see why this is a problem. QGIS doesn’t know where Cape Town is supposed to be – that’s what the data should be telling it. If the data tells QGIS that Cape Town is 34 meters away from the equator and that South Africa is only about 12 meters from north to south, then that is what QGIS will draw. When combining data from different sources, it’s important to remember that they might not be in the same CRS. “On the fly” reprojection helps you to display them together. Remember when you calculated areas for the farms in the Classification lesson? You did it so that you could classify the farms according to area. Notice how the areas are all very small, basically zero. This is because these areas are given in degrees – the data isn’t in a Projected Coordinate System. In order to calculate the area for the farms in square meters, the data has to be in square meters as well. So, we’ll need to reproject it. But it won’t help to just use “on the fly” reprojection. “On the fly” does what it says – it doesn’t change the data, it just reprojects the layers as they appear on the map. To truly reproject the data itself, you need to export it to a new file using a new projection. Look at the new values in your attribute table. This is much more useful, as people actually quote property areas in hectares, not in degrees. And projecting the data in an appropriate projection before calculating the area will actually give you the area in hectares. This is why it’s a good idea to reproject your data, if necessary, before calculating areas, distances, and other values that are dependent on the spatial properties of the layer. There are many more projections than just those included in QGIS by default. You can also create your own projections. This projection represents the Earth on a circular field instead of a rectangular one, as most other projections do. Different projections are useful for different purposes. By choosing the correct projection, you can ensure that the features on your map are being represented accurately. In the next lesson you’ll learn how to analyze vector data using QGIS’ various vector analysis tools. Source.