To start with, if I was to tell you the location of something

as being 55 meters away in the x direction and

41 meters away in the y direction, where is this item located?

It all depends on where those coordinates are relative to.

Are they relative to me right now?

Or are they relative to some standardized location on the earth?

This distinction is very important.

Packed into that description I just gave you are two important concepts about

geographic data.

Number one, I gave you a unit of measure for our coordinates in meters.

Without units, distances are meaningless.

And number two, we need to have a reference point with a known location in

order to locate items with these coordinates.

This reference point is often called a datum and it's effectively a model

of the Earth's surface that coordinate systems can be built on.

Together, these two concepts form the basis for a coordinate system.

Not all data uses the same coordinate system.

Far from it.

And to be displayed on the same map,

your data doesn't need to be stored in the same coordinate system.

But the GIS software does need to convert your data

to the same coordinate system behind the scenes.

This will intuitively make sense because you have different reference points and

different coordinates.

How can you overlay them without some conversion to a common system.

Building on coordinate systems is the concept of projections.

The term projection is often used interchangeably with coordinate systems,

and you may hear me make that mistake occasionally.

But, in fact, they are different, and projections build on coordinate systems.

So to start with, what is a projection?

Projections help us display the earth on a flat surface like your screen or

a sheet of paper.

While it may not be intuitive at first,

we can't just flatten the Earth easily to fit on your screen.

To help illustrate this concept, let's try to imagine flattening a sphere.

Just like we would have to do to display the Earth on your screen.

Imagine an inflated spherical ball, just like a football, or a soccer ball for

you Americans.

Let's cut it down the side from top to bottom so

that the interior hollow part is exposed.

To make it even easier to visualize it we can cut it into completely into halves so

that we can set the cut side on the ground.

We now have half the ball sticking up off the ground but there's no

easy way to completely flatten it so the skin of the ball is against the ground.

If this ball was the Earth, we would need to stretch and distort it

in order to get it completely flat to display on your screen or on paper.

This set of stretches and distortions is what a projection is.

When working on a two-dimensional surface like computer screen,

we get some benefits out of working with projected data.

First, lengths and angles can be constant across the two dimensions

which we can't always say about our geographic coordinate system.

Think about the lines of longitude and how they converge at the poles.

The distance between the degree of longitude at the poles is very

different than the distance between the same degrees at the equator.

Projected coordinate systems have uniform distances and

map units regardless of location, as well.

This lets us identify locations by X, Y coordinates on a grid.

To bring this all together, to build a geographic coordinate system we

need an accurate model of the Earth's surface.

From there, coordinate systems are built.

And building on that are projected coordinate systems.

Now, we don't get this translation of our data to a 2D surface for

free, there are trade offs.

When we project geospatial data, you end up creating distortions.

Distortions can occur in the shape, the area, the distance, or

the direction of the data.

Different projections are created to optimize for

these distortions so some projections are good at preserving local shape.

These are called conformal projections.

Others preserve the area of the features.

These are called equal area projections and

still others preserve distances between points on the map.

These are called equidistant projections.

In practice a projection must restore at least one attribute.

Shape, area, distance, or direction.

Different projections also optimize these attributes for

different locations on the earth, and others do it for the entire earth.

The result is a large number of projections optimizing for

different attributes and different locations.

Depending on the work that you're doing,

you will find yourself needing different projections and coordinate systems.

So now let's take a look at some projections.

Before we do that, let's take a look at the earth on a sphere.

We'll start by looking at Africa, and

then we're going to compare it to the size of Greenland.

Since Africa is near the equator, it's shown closer to its true size in this

often undersized relative to the rest of the world on a world wide projection.

In contrast, Greenland is oversized by virtue of being

near the poles where more distortion occurs.