What is the process that we go through when we try to take part of the real world and turn it into a map? So, this section I've called mapping the real world because literally we're going to talk about the process of taking something that exists in the real world around you, that you want to identify or extract, if you will, and put that on a regular map and, what is the thinking that goes on behind that? How does that work? Let's just talk about that a little bit. So, here we have, let's say this is the real worlds as though we were floating above it, this is from a satellite image, but imagine that you are able to somehow levitate above the ground. This is the town of Hilo on the big island of Hawaii. It's a beautiful spot if you ever have a chance to go there. It's amazing, but wherever you are and whatever in the world you're trying to map, it's really kind of the same thinking process. You're looking down, you're looking around you and saying "What is it that I want to have on my map and what is it that I don't want to have a mind map?" That's going to vary from one person to another depending on the purpose of that map and what it is that they're trying to do. So, if we look down at this image, we can see that there's some areas that are water, there's some areas that are buildings, we have some roads along here, we even have an airport over here, so these are the runways. There's some boats in the harbor, and really what this is, what I'm trying to kind of get you to think about a bit is really there's an infinite amount of complexity that you potentially could put on your mouth. So, not to be too ridiculous, but are you really going to try and map every blade of grass, every grain of sand? What is it that's too much? What's the amount of detail that's appropriate or useful for you and how much is too much? Maybe you don't even need all the buildings. Maybe you just need to know that that's an area that's built up, and you could just have a gray area that says "That's residential," or something like that. Or maybe you do want to have every building, and do you want to have them as just squares that say, "There's a building here," or do you want to actually have the full outline of the footprint of every building? So, which objects, which things do you want to have on your map, and how much detail do you want to have on your map? These are the kinds of things that, now you as a mapmaker or a cartographer, someone who's collecting data, identifying objects, you have to go through this process and think about what I want to put on there. So, a map is a simplified version of reality. We have to decide what we want to include, what we want to exclude so that we can study an area, model it in some way, and ideally understand it. So, here's our simplified version of reality. This is the same location. So, as you probably can see, we've got water here. That's pretty easy to see. This is actually Hilo Bay, but you'll notice on this particular version of a map, this is not what I created, this was made by Esri. There are no buildings on this map. They decided for this particular purpose that that wasn't necessary for what they wanted to do, but they have color-coded areas that have vegetation. So, you can see vegetation there. You can see roads, and they've got different types of roads with different colors. So, that's all there. They have included the runways. So, they made choices about what they wanted to include in their simplified version of reality and what they wanted to exclude. It's important, I will say this many times, is that when you look at any map like this, you should be thinking about it critically, like, "What is missing from this map? What did they do that I might do differently? What is it you like about this map?" Those are the kinds of things you have to kind of go through instead of just accepting it and saying, "Well, it's a map." You have to kind of look beyond that and look at it a little more critically. It's more fun that way actually, I think. So, we're conceptualizing the real world. We're comparing, in this case, on the left reality to the right the simplified version of that reality. So, if you're a city planner, you might have one concept of what a city is while someone in urban forestry might have a very different concept of that same location, but they might make a different map. So, on one map, there might be no trees, like on this one here on the right, there's no trees, but if you're an urban forester maybe having trees in that map would be incredibly important. So, different decisions will be made by different people. So, now, if we think about this idea of simplifying reality, we have to think about what is it in reality that we're trying to include on our map and how do we show those things. How do we literally depict them graphically in a way that other people will be able to identify them and understand them. So, here, we have what I would call a continuous phenomenon, in this case, elevation. Hopefully, this kind of color scheme and way of showing things will be familiar to you, is that we have areas that are at low elevations in blue, that's actually beneath the sea level, then green, then moving up through the color scheme through yellow to red to the top; and they've included on this map as well some shaded relief. So, you kind of get that shadowing effect. It kind of enhance that idea of elevation, but the main point I'm trying to get across here at this point is that elevation is something that exists everywhere on the surface of the Earth. Every location has some kind of elevation associated with it, whether it's high, or low, or above sea level, or below sea level. So, how is it that we go about showing that elevation. So, we're going to talk about that and think about that. Here's the same location. This is Hawaii again, but now we're looking at things that can be depicted as discrete objects. So, we have continuous phenomena and discrete objects. So, here, if we look at the legend for this, we have emergency shelters. So, these are what we would call point symbols. So, you can see there's some here and here and here. We have volcanoes being shown as point symbols, and that's interesting in itself because the last slide when I was showing elevation, you can clearly see that the volcano does not exist at one discrete point, it actually exists over a much larger area; but how do you define, say the bottom of a volcano? Where is the bottom of it? Whereas the top of it? But in this version of reality, the people that made this map decided to identify that strictly based on the-, I'm assuming, the top or the crater caldera of the volcano, and so we have one here, one here, one here. So, they've taken that continuous phenomenon, which is really just a different type of elevation that we're choosing to identify its volcano, and they've condensed that down to one point. Points here actually don't even have any dimensions, they just exist at an infinitely small point, and then you have this symbol that's used to identify it. Then, we have highways, these are lines here, and then we have lava, flow hazard zones, which are areas. The main things I want you to get out of this at this point is that, we now have two different ways of showing things: one is where things are very continuously over space, or things like elevation. Another good example is air temperature, which exists everywhere, so you don't look out at the sky and say to your friend, "Hey, look, there's a 34 degrees." You can't see it. It's not there. It's just something that varies continuously, but then you have things that are discrete objects that do have finite boundaries to them. So, the sides of a building or the edges of a road, that kind of thing, are discrete objects. Again, you have to think about how would these things define. So, these hazard zones for example, they have these very crisp clear boundaries on the edge of the zones. Do you think that's actually indicative of reality? Do you think that if you walked out into that area that you'd be able to see this perfect demarcation on the ground where, "Oh, this is a high risk area and this is a low risk area"? Probably not. Someone had to make that choice about where do we think that risk zone boundary is? How are we going to define it? Then we can draw a boundary and a map that will help people understand those different areas and risks. So, we have continuous phenomena and discrete objects; points, lines and polygons as we will call them. So, here's our discrete objects. It's things like buildings, roads and our continuous phenomena; things like elevation and temperature. So, how can these be shown on a digital map? That's really what I'm getting at here, is how do we translate these from the real world to a map? How can we store data about them? So, it's not just how do we show them on a map, but we want to be able to have a database of information or data associated with that, and how we do that is we use models. So, what is a model? A model is just a simplified version of reality. So, here, a model car, is a simplified version of a real car, right? So, that's exactly what we're talking about is a simplified version of reality through all kinds of things you're going to learn about GIS, you'll hear different modifiers used to explain models. So, there's physical models, and logical models, conceptual models, but the basic starting point from that is it's all just a way of simplifying reality in a way that's easier for us to understand and work with. So, a model might be something like a car or a building, it might be a region, like an urban center, it may be a system, like the hydrologic cycle. There's lots of different ways that models get used, but this is really what we're starting from. So, that's what a model is. What's a data model? So, already, we're talking about something more specific than just a model. Now we're talking about a data model. So, instead of using pieces of metal or plastic to create our model car, we're going to use data points to create our model of the real world. So, for example, we can store the coordinates, let's say the longitude and latitude for each road intersection for a place and connect those intersections with lines, and that becomes a simplified model of the road network for a particular location. So, a data model is a way of organizing and representing data, that are a simplified version of reality. So, as a starting point, and this is just a guideline, is that at least for now a good way of thinking about this is that we can use a vector data model for discrete objects, we'll talk about this more; but a vector data model is essentially this idea of using points, lines, and polygons to to model objects. A raster data model, which is a grid of squares, is better or more suitable for modeling continuous phenomena. So, this is strictly just a starting point. It's very possible and sometimes advantageous depending on what you're doing, to use a vector model to model continuous phenomena, and you can use a raster model to show discrete objects. So, you can mix and match and use these things whichever way you want, but just for now I think it's a good starting point to kind of think of these as typically a good way to start is that vector is good for discrete, raster is good for continuous. Just to finish this section off, I've mentioned thinking about geographic themes as layers, so I just wanted to kind of show you this is that, you can think of, for example here, elevation as one geographic theme or layer. So, this is a continuous phenomenon. We can have a satellite image. Again, this would be a continuous phenomenon, which is the fact that we're looking at an image of part of the surface of the Earth, but really this type of imagery exists for the entire planet. We can have discrete objects. In this case, these would be census units for the City of Toronto, and we can show more discrete objects. These are vector points for something like grocery stores, that we could then map as well. The great thing about GIS is that we can co-locate these in space. So, in other words, we can spatially reference them, or geo-reference them so that we know where each of those layers is on the surface of the earth, and then compare them, put them together and use them together as a model to answer a question that we might be interested in. That's the real fun part of course, is not just making them out but then using it to answer questions.
