When we obtain a remotely sensed image from wherever, there are different ways that we can extract information from it and the most obvious one is to do it visually. So, if we imagine ourselves floating above the Earth looking down as we would if we were the sensor, we can see the Earth there with land cover and we can see that it's been divided up into individual cells that the sensor senses one at a time. So, each one of those has a value based on the amount of light that's been reflected off of the ground and hit a sensor, and that's converted into numbers which are in this case converted into grayscale values so we can visualize it. But really what does that cell represent? All we really know is that it has a number and then we can assign a grayscale or color to that number, but then what do we do with it? How do we actually turn that into something that we can use? So, is this a field with grass in it? Is it a building? Is it a tree? Is it a field full of a crop? What is that a crop? Is it a beach? So, that's really what we're talking about here is, how do we go through the process of visually extracting information? So, what does that cell number represent? All we know is that the remote sensor measures light reflected from a square on the ground, it doesn't tell you what that square is. So, we have to somehow turn that data into information and that can be done manually, in other words, using our eyes and our brain and we can interpret things, or it can be done automatically, or semi-automatically, or quantitatively using something called classification. So, interpretation is this manual process where we use visual pattern recognition. Your brain can recognize things like clumps of trees, but then you would actually have to manually trace out that clump of trees if you wanted to use that in your map. So, if you were to turn that into a feature in your GIS, for example using let's say the vector data model, you would actually have to digitize the outline of those trees and say that I am looking at this, I see trees, here is the outline of those trees and digitize that or trace it, and turn that into data that you can then do something with. So, to do that is fine, but it's very tedious and time intensive. With classification, we try to automate that process or semi-automate it depending on the message that's being used using math and software. So, what we try to do is get the software to recognize patterns in the numbers, are there a bunch of cells that have similar values? Are those cells near each other for example? We try to use those patterns or combinations of numbers to do that interpretation for us so that we can extract information in a more an automated way. So, it's a little more complicated but it saves us a lot of time and might give us even better results sometimes than we would get if we were trying to do it manually. For this section, we're going to just focus on the manual interpretation aspect. So, here we have a satellite image this is from the Icono satellite for part of High Park in Toronto. And we're looking at visual interpretation here. So, when you look at this, you're actually looking down at the ground and you're automatically identifying things. I'm sure it's not like you have to think about this a lot. You can say, "Well, of course I can see some trees, and a road, and a park, and so on", but what I want to do in this section is just try to break it down a little bit. So, what is it that your brain is actually looking at? Or how does it a break apart the identification process in order to be able to understand what it is that it's looking at? One of the most obvious things to look at is the shape of something, that's the form of the object. So, if you see something that has a straight edge, more than likely, it's going to be anthropogenic, in other words, made by people. So, it could be something that's urban or agricultural, whereas if you see an irregular edge, then it's more likely that it's something more natural, so this might be the edge of a forest, or the shoreline along a coast, something like that. So, when we see something like that here, what does that shape mean to you? Well, more than likely even if you've never been to High Park before, you could probably guess that that's a baseball diamond just based on that kind of unique shape, and there's another one here. Okay. So, sometimes shapes can give you a really good clue as to what that object is, and you have to remember that it's not always going to be so obvious. That's why, part of the reason why I'm going through this. Size is also a very important way of being able to interpret something. So, that could be the actual size, so, how many meters is it across or whatever, but it can also be the relative size of different types of objects. So, the fact that we have a large object here, we have another one here, we have a lot of smaller objects around it, I'm sure you can guess what these are, but the fact is that, yes there are buildings, but if we have a really large building, well, then that might tell us something about its purpose or its use. In this case, because it looks like it's in a residential area, maybe that's an apartment building or condominium, if it was in a more commercial area, then it might be an office building. But that alone, the size of that object tells us something about what it might be. Tone is just the amount of brightness or color that's in an image or a part of an image, and this of course is fundamental to distinguishing different types of features. It helps us in terms of our perceptions of shape, texture, pattern. So, for example, here we have a very bright tone, that's, for this is our baseball diamond than you can imagine. It's probably a really fine gravel, that's a very light color so that's going to come out as being really bright on our image. Then we have these dark patches over here and this part of the field. What would cause this difference in tone? What might that tell us about the conditions or the cover of that particular area? Now, I wasn't there on that particular day that this was taken, but just by looking at the shape of that and the tone together, I'm taking a guess that that's probably an area that's wetter than the area around it which may mean that it's an a depression, maybe it rained recently. So, that gives me some way of being able to interpret what I'm seeing there just based on tone and that in combination with things like shape. Texture is the arrangement in frequency of tonal variation. So, if we have a rough texture, what that really means is we have a modeled tone. So, we might have grey levels that are changing abruptly over a small area. So, that could be something like forest canopy like we have here. We have differences in tone over a very small area that comes across as this model look or what we would perceive as a rough texture. As opposed to a smooth texture, in other words, we have little tonal variation like we have in this field here. So that might tell us different things, for example, this is probably all the same type of land cover and in combination with other things that were interpreting, this pretty good guess that it's probably grass, it's smooth, it's all the same height, so, we have a similar or the same tone and texture across that area that tells us that it's probably a very uniform type of land cover. When we have a mottled texture here or rough texture, that might tell us about a different type of land cover such as a forest canopy. This is another example of texture based on water. So, we can see that we have a very rough texture on Lake Ontario here and we have a very smooth texture here. They're both Lake Ontario, they're both water. So, why are we getting different textures? I'm sure you can probably guess that the clue is that we have this brick wall here and that's stopping the waves from crashing onto the shore, and so this part of the lake is quite wavy, and then behind the brick wall, there are virtually no waves and so we have a much calmer, smoother surface and a different texture. So, again I wasn't there that day, I can't say 100 percent for sure that that's what I'm seeing, but from my experience with visual interpretation, I'm guessing that we have one area that was wavy and one area that was calm. Pattern is important. That's the spatial arrangement of objects. So, if we have a repetition of tones, or textures, or shapes, this is what produces a pattern. So, for example, you can see this pattern here, and here, and here being repeated over and over again and I'm sure you can probably guess that those are the roofs of houses, or this would be a residential area, and so the fact that we're seeing that pattern tells us something about how we can interpret that particular type of land cover, what are those objects that we're seeing there? Shadows can be really helpful. So, that can help to determine the height of a building, or the shape, or the profile of that building relative to the height. So, where we have here, for example, this is a tall building. How do I know it's a tall building? Because it has a long shadow. So, because it has a long shadow, it's tall, but the problem is that because we have this shadow, so yes that shadow is helping me in terms of understanding that that's a tall building, but it also means that I don't know anything about what's going on in that shadow. So, all of these dark areas are basically a lack of information about what the land cover is at those locations. So, shadows are a good thing and a bad thing. They can help us interpret what we're seeing in terms of that building itself, but not what exists in that shadow. Lastly, we have association and that just means the proximity of recognizable features. So, for example, what I'm highlighting here is this area and we can interpret what this is based on it's really a combination of things, shape, pattern, association, but the fact that we have a road here, and we have this smooth surface here, is probably a parking lot. We have this grouping of things with a similar pattern. So, that's probably a parking lot and those are probably cars. Not only that but if we have cars parked in a parking lot in a park and we happen to have a building over here behind that arrow, maybe you can't see it that well there, is there, maybe it's a restaurant, in fact I know that it is because I've been there but even if I hadn't, then maybe that's why people are parking there. So, there's associations or ways of being able to say if I see this type of pattern or this type of object associated with something nearby, that might tell me more about what it is that actually is there, what those objects are and what they might be used for. So, that's our section on visual interpretation. I hope that helps you to kind of get a sense of when you're looking at an image especially for an area that you haven't been to before, how you can go about in a more systematic way interpreting the information that you might be able to get out of that image just by looking at it.
