In the previous subunit I talked about the fractal dimension of various objects such as coastlines. But I haven't yet told you how these real world fractal dimensions were computed. It was possible for us to compute fractal dimension from the Koch curve and the Sierpinski triangle because these are perfect mathematical fractals, not real world objects. But there's a lot of interest in computing approximate fractal dimension in the real world because it can often reveal insights about natural or human created systems. There are a lot of different methods for analyzing fractals and whole books devoted to this subject. Here I'm going to show you one commonly used method for estimating fractal dimension, the box counting method. The box counting method is closely related to this idea that as you change the size of the ruler that you measure a fractal by, you get a different length as you go further and further into smaller and smaller length scales. So here's what the box counting method consists of. You take a particular object. Here I have a picture of the British coastline. So what we do is overlay this figure by a grid of boxes. Each box has a certain length of its side, which is the scale at which we're measuring this figure. And what we do is count the number of boxes in which part of the black outline of the coast appears. For example, it does not appear in this box, even though this is in the middle of Great Britain, so we don't count it. So if we follow that procedure and count the number of boxes containing part of this black outline, I got 36. The length of the side was 10 units for each box. Now I go to the next step and I increase the size of the boxes. So I'm now calculating the number of boxes, but at a different scale. Here because the length of the side of the box was larger, I got fewer boxes that contained part of this figure. Then I would go up again. Here the size of the box is larger again, 12. And I got 27 boxes that contained part of the figure. So you keep doing this, accumulating this list of numbers. Let's look at the relationship between Hausdorff dimension, which we already learned about, and box-counting dimension. If you recall, for the Hausdorff dimension we had a relationship that is the number of copies of a figure from a previous level. If we take the log of that, that was equal to the dimension times the log of the reduction factor from the previous level. It can be shown that if you do this box-counting method, this can be approximated by looking at the log of the number of boxes and that's equal to the dimension times the log of 1 over the length of the side. D is called the box-counting dimension and if you want to see the derivation of this and other details about the relationship between these dimensions, take a look at Chapter 4 of the Fractal Explorer which is a website about fractals. And there's a link from our Course Materials page on this. Now the question is, how do we actually get this D from our values from numbers of boxes and lengths of sides. Well if you're up on your algebra you might have noticed that this equation is actually the equation of a straight line. If we plot it on a graph where the axes are here, the log of one over the length of the side, this x value, and the y axis is log of the number of boxes. And D would be the slope of that straight line. So what we can do is we can take the measurements that we made at each level for the box counting and we can plot it, each measurement, on this graph. So here's some hypothetical measurements that we might have gotten, where the number of boxes goes down as the length of the side goes up. Notice this is 1 over the length of the side, so as length of the side goes up, this goes down. You can see that if this is actually true these should form a straight line whose slope is the dimension. So we can estimate the dimension by plotting these points, doing our measurements for the boxes and then plotting these points. Drawing a straight line through them, figuring out what the slope of that line is, and that's our measured dimension. And that's roughly what people did to calculate things like the fractal dimension of coastlines.