23 Mercator
The Mercator projection is the classic map
One means of building Mercator’s map is to begin with Archimedes’, and and perform some modifications. We will follow this, and will attempt to change as little from the previous map as possible: indeed we will attempt to construct this new map also by first projecting the sphere onto its bounding cylinder, and then unrolling that cylinder onto the plane.
The only choice we made in the above derivation of Archimedes’s map was that the projection was horizontal, or that the height
Definition 23.1 (A General Cylindrical Projection) Let
There are all sorts of maps you can make by choosing different functions
Here was his idea: we know how much the circle starting at height
Thus its circumference is
But the vertical direction involves two stretches: first we need to think about the effect of horizontal projection onto the cylinder, and then second, we need to tack on the vertical stretch induced by
The first of these is something we can already compute using our knowledge of Archimedes map! At a point
Where we found the vector as the second column of
This means a vector of Euclidean Length 1 on the map gets sent to a vector of length
Exercise 23.1 Check all this!
Now we’re ready to think about the stretch
That is, our function
This is a differential equation for our function
Definition 23.2 (Mercator’s Map) Let
Exercise 23.2 Find the parameterization for the mercator map. Hint: first calculate the inverse function of
Now we know the
Exercise 23.3 Show that if the point
Putting these two exercises together, we have successfully computed the parameterization to the Mercator projection!
Theorem 23.1 The parameterization for the mercator projection is the map
Where in the second line I have written these combinations of exponentials in their equivalent form using hyperbolic trigonometric functions. We will meet these functions in a different context very soon!
The fact that Mercator’s map sends preserves angles is a huge advantage not only for navigation, but also for calculation. Since it sends infinitesimal squares to infinitesimal squares, it scales all lengths by the same scaling factor, which we can find by
Exercise 23.4 Show that at any point
Hint: since all vectors are scaled the same, can you find the map length of
Being able to measure the infinitesimal length of any vector lets us write down the map-disks for the mercator projection, and also lets us compute the infinitesimal area element:
Exercise 23.5 Explain why the map-area is can be calculated by
Hint: think about what it does to an infinitesimal unit square
Exercise 23.6 At a point
23.0.1 Application: Geodesics
There is one important result about the sphere that has eluded us this entire time. In the plane, we saw that there were three different notions of line that defined the same curves: distance minimizing, straight, and fixed by isometries. For the sphere, we wrote down the same three conditions, and said we would prove them equivalent here as well. But what did we actually do?
We first discovered great circles as they were fixed by isometries, and then we proved that these curves were also straight, using the correct definition of acceleration on the sphere. Ever since, we’ve been using them to define our distance - but we never actually proved they are distance minimizing! I promised we would do that at a future time (in a non-circular way) when we had developed more tools to help us, so we could avoid some nasty integrals in 3D space.
And now is that time! One of the superpowers of using maps is it lets us take the sphere which was originally a curved surface in three dimensions, and accurately represent it by regions in the 2-dimensional plane. And calculus on the plane is much easier than calculus on a surface in three dimensions. This lets us mimic quite closely the original proof we gave in Euclidean geometry that lines were distance-minimizing (Theorem 12.1).
Here using the Mercator map, we will focus on a line of longitude, which is a vertical line on the map. We know these great circles are both straight and fixed by symmetries, so our goal now is to show they are length minimizing (at least, when they go less than half way around the sphere)
Theorem 23.2 Let
Proof. Let
PICTURE
First, let’s write down the infinitesimal length of
The integral of these infinitesimal lengths gives the overall length:
Now lets do the same for
And so its total length is
Remembering that
And this is clearly true! Since
The same equality remains true after taking the square root, and after dividing by
Integrating this we see that
so
The careful reader will notice that this proof is not quite technically complete: we showed that the great circle is the shortest of all curves of the form
Exercise 23.7 The careful reader will notice that this proof is not quite technically complete: we showed that the great circle is the shortest of all curves of the form
Hint: look back at the Euclidean proof where we did this: Theorem 12.1. Can you prove that
This finishes off the final fact we needed to complete our study of the geometry of the sphere. Congratulations!
Exercise 23.8 Show that
Hint: write
23.1 The Mapmaker’s Dilemma
We’ve now gotten rather comfortable computing true quantities about spherical geometry using a map and calculus. Since all of our maps have distorted the sphere in some pretty serious ways, its pretty important to have these abilities as you cant just trust your eyes!
Of course some maps did better than others: orthographic projection messed up basically every quantity we could think of, whereas Archimedes map managed to accurately portray area and Mercator’s accurately represented angles. But none of our maps accurately represented both area and angle at the same time.
Indeed - while we did not check it, all the maps in the Cartography chapter have this property: some of them preserve area, some of them preserve angle, but none of them do so simultaneously. But this doesn’t mean its impossible to make such a map - there’s an infinite variety of things that we haven’t tried (and an infinite number of possible maps that no human has ever drawn) - perhaps one of them is able to preserve two quantities of the sphere at once? After all, some of the maps we did see in the previous chapter did a pretty good job of approximately preserving both (and shifting some of the complexity to the shape of the mapping region
Math, that’s who says this will never happen.
Theorem 23.3 (The Mapmaker’s Dilemma) It is impossible to make a map which simultaneously accurately represents both angles and areas.
Proof. Assume for the sake of contradiction that there is such a map
This means that our map must preserve all infinitesimal lengths! Choose any point
But a map that preserves infinitesimal distances is an isometry - and this is going to spell trouble. In particular, we know that isometries send geodesics to geodesics, circles to circles, and preserve the length of all curves. Because of this, as we saw in the chapter on curvature, isometries preserve the value of all the terms showing up in the limit that defines curvature: and any two points related by an isometry must have the same curvature.
But
During the proof of this we noticed another, easier dilemma: its impossible to make a map that preserves distances!
Theorem 23.4 (The Mapmaker’s Dilemma, Distance) It is impossible to make a map which accurately shows the distance between any pair of points on the sphere.
Proof. Such a map would then preserve infinitesimal distances, and thus be an isometry. But this would again preserve the curvature, which implies a contradiction: that the sphere and the plane have the same curvature!
This is a pretty amazing result: proving nonexistence theorems are hard, as you have to somehow rule out all of the possible examples, even the ones you can’t imagine. Proving such a theorem often requires finding some deep mathematical property that can tell things apart, some sort of invariant. And for us, that invariant is curvature.
You can see the mapmaker’s dilemma as in some sense a capstone of this entire section of the course: if you dig deep enough almost everything we have done since the introduction of calculus goes into its proof in some way or another.
From one perspective, it essentially finishes off the entire theory of mapmaking, answering the fundamental question. But from another, it tells us useful pragmatic information about how to move on: don’t worry about making your map look accurate, our theorem warns us you don’t need to look at it to compute, anyway! That’s what calculus is for. Just make it easy to work with. There’s no best map, but there may be a good map for your specific desires or purpose, just build that one.
And build such a map, we will!