All language subtitles for 08_multivariate-maps.en

Multivariate maps are just a way
of combining different types of

quantitative maps.

To be able to compare, or
show in some way, more than one variable,

so we have multivariate.

More than one variable,
put them together on a map, and

the idea is to try and
make it interesting and useful.

Without it kind of being too much, or too
complicated, you just want to kind of show

a relationship between two or
maybe three variables.

In a way that relates to
the geography of that location, and

it helps people understand what
it is you're trying to show them.

So here we have a map that's
showing two different variables,

what I have is a choropleth map
of population density here.

And I've purposefully made it
just this simple gray scale,

from light gray to dark gray,
showing the population density.

And I'm relating that to
the graduated symbol map.

Which has to do with the NO2 stack
emissions from point sources

of pollution in the City of Toronto.

And so the relationship, of course,
between these two variables is.

Where are there more people, in terms of,
what's the higher population density.

And where is more NO2 being
released from these point sources?

And so you can see that we have
a lot of people living downtown.

So the choropleth is showing
a high population density, but

it also happens to be the location
of a lot of NO2 emissions.

So NO2 isn't something you really want to
have a lot of around, if you can avoid it.

So this is just a way of being
able to show these two things.

So, in terms of map design,
I tried to show it in a way where we

have some semi-transparency
happening with the symbols.

So that you can see
the choropleth underneath,

I tried to increase
the contrast between the two.

By having a gray scale choropleth
with red symbols on top, so

that they kind of show
up well between the two.

So I think this works relatively well,

I think it's useful to be able to show the
relationship between these two variables.

They're something that people may be
interested in, in terms of pollutants and

population density.

And try to show it in a way where
the two variables compliment each other,

in terms of map design.

If we zoom in a little bit here,
here's the legend again.

So you can see, actually,

that the University of Toronto happens to
be the third largest emitter in the city.

In the year that this data was taken,
this is from 2010, and

notice that when I zoomed
in on the map in ArcMap.

It actually scaled the symbols to
match the change in scale of the map.

So you'll notice the size
of the symbols here,

compared to downtown versus in the
previous map where they're much larger.

So that has to do with the way that
the scaling is set up in the software,

there's different options for that.

But this is what I chose
to show them here.