Sunday 28 November 2021

World Population by Latitude

If you search online for 'world population by latitude' you'll quickly find quite a few results, including the great analysis by Bill Rankin on his Radical Cartography blog from 2008, which uses population from 2000, and also includes population by longitude. There's also a nice interactive version on Engaging Data, plus similar things on my One Degree of Population piece on here a couple of years ago and my global population density spike maps. In this post I look at world population by single degree of latitude using data from 2020. There are maps and stats below, but let's begin by looking at what appears to be some kind of alien eyeball but is in fact world population by single degree of latitude, where redder areas = more people at that latitude and bluer areas = less people. I used 2020 WorldPop data to do the calculations and all the maps were done in QGIS, as usual.

Weird alien eyeball? Or population map?

It's better viewed as a flat map, obviously, so I've posted that below. I've labelled quite a few places across the world and of course there are places at some highly populated latitudes that have very few people (notably the Sahara Desert) but you get the idea here: redder = more people at a given latitude.


Note the numbers on the left - including population data

If you view this image in full size you should be able to read the population numbers for each single degree of latitude - I've posted a zoomed in extract of this below. The most highly populated single degrees of latitude, according to my analysis? Here are the top 10 that I get:

  1. 25-26° North: 278.6 million people
  2. 26-27° North: 271.7m
  3. 23-24° North: 244.5m
  4. 24-25° North: 237.4m
  5. 22-23° North: 235.3m
  6. 30-31° North: 234.8m
  7. 31-32° North: 226.2m
  8. 34-35° North: 215.8m
  9. 35-36° North: 214.6m
  10. 27-28° North: 198.3m
And then down in 28th place we have the first entry in the southern hemisphere with 6-7° South having a population of 117.5 million people, according to my calculations. 


These are numbers I calculated myself

It's difficult to do anything with this colour scale these days without bringing to mind Ed Hawkins' warming stripes, but I think it's useful to use the red/blue colour ramp here because the most highly populated places are generally the warmer ones and the colder latitudes on the whole have fewer people. But of course there's another factor here, and that is about where all the land is. So first let's look at land vs population and then we can look at a density version of the above map - i.e. population density by latitude that presents the stripes based on the population density of land at all the different latitudes.


This is what I get for land by latitude


And population by latitude - people don't like living in the sea

You can do a little crossfaded gif to get the comparison between these two different elements, so that's what I did below. You can see it in the still images above, and in the gif below I have highlighted the single degree of latitude with most people and most land. 


Finally, we have a population/land by latitude gif

Let's hit pause on the gif, mid-fade, and then add some labels so we can make a bit more sense of what's going on. That's what I've done below - click to enlarge in order to read the labels.



Here's another globe-style view of the population data but this time from a different perspective.


Some surprises here perhaps

Okay, so the next three images are similar to the 'world population by latitude' image above but this time they are actually population density by latitude. That is, the redder latitudes are the most densely populated. I did this so that it only takes into account land, which is kind of where people like to live for some reason. You'll note in particular here there is a dark red stripe in the southern hemisphere that cuts across Santiago, Buenos Aires, Cape Town and Sydney, among other places. Note that I experimented by dimming and then removing the latitude colours over the sea in the second and third images because it kind of makes sense to do that.


Density makes a bit more sense

Dimmed the sea because people don't live there

Removed the sea latitudes, but I like this less


Other odds and ends

Once I'd done this I experimented with different map projections and views, hence the weird population latitude eyeball at the top of the piece. I also experimented with views from above and from below, so you can see them below in the first two images. The first one in particular looks like a bloodshot eyeball to me.


Where do most people live? Just eyeball it

Antarctica is pretty big

What else? Well, I did a few other versions, including just coloured lines of latitude, then adding only land, adding a chart and that kind of thing so I've posted them below too. These are more experimental versions - some I like more than others but the one with just colours and land I think is quite interesting.


Population stripes, with land

Just the population stripes

I took away only the land here

In this one I just added a chart of population by latitude

This is the original, as above, but without a white border

Does the final result on all this depend upon what dataset you use? Do you get a different result by using, say GHSL data vs WorldPop data? Or what about NASA's GPWv4, or even another source? Well, probably a bit, but the difference between GHSL and WorldPop wasn't huge and WorldPop is also available for 2020 and GHSL isn't so I used WorldPop. But you can see the difference between GHSL and WorldPop below anyway.


GHSL

WorldPop

GHSL WorldPop GHSL WorldPop GHSL WorldP

This all basically makes sense and is not particularly surprising but then again it's nice to be able to put some numbers to all this and make some maps of it. Plus it's interesting for training data and for working on map methods and techniques in QGIS.

People live here

Here's a screenshot of what this looked like in QGIS before I exported some of the final images. The font is Righteous, by the way.


Print Layout on left, map view on right


So there we have it. 

Thursday 11 November 2021

A few QGIS geometry, label and style tips

I haven't done a QGIS how-to blog post in a while, so it's time for another one because I'm working on a lot of training material right now. The end result is just a plaything, so it's more about the methods used. 'Learning by play' is a key concept in early years learning for a very good reason and I'm a big proponent of learning things this way, no matter how old we are. Okay, so what are we going to do? Well, see below for the end result and then we'll work it up step by step. This is for people already fairly familiar with QGIS, but you can probably follow it even if you're not. 

A stylised world cities and population map

The point of this exercise is mostly to demonstrate some methods, but first you need to grab some data from Natural Earth - just two layers are needed, plus one we'll make ourselves.

  1. Natural Earth populated places (simple version) .
  2. Natural Earth countries (without boundary lakes - this means we can see the Great Lakes on the map, and so on).
  3. A 10 degree grid layer, which we'll make in QGIS - it's very easy.

Step 1 - add the two layers

Add layers 1 and 2 above to QGIS, and make sure the places layer is on top - i.e. make sure the dots aren't under the land. 

Your colours may be different, it's not a problem


Step 2 - create a grid layer

Make a 10 degree global lat/long grid by going via Vector > Research Tools > Create Grid... and then entering the settings you see below. Make sure you create a polygon grid, as shown in my screenshot and then once it appears in QGIS, drag it underneath the other layers in the Layers panel. You'll notice that the grid extent in the screenshot below goes from -180 to 180 in longitude and -90 to 90 in latitude. It doesn't matter if you see decimal places in the box, just be sure to use these numbers otherwise your grid won't cover the whole world.

I chose 10 degree grid spacing, but feel free to us what you like

Step 3 - duplicate the layers

Then we're going to want to duplicate the layers - as shown below - and then change the styles. We will have three copies of the places layer, two copies of the countries layer and two copies of the grid layer. I'll share the colour and style information below as well. Don't know how to duplicate a layer? Just right-click a layer on the left and hit Duplicate Layer. They won't look like what you see below (yet) with the colours and filters on them but we'll do that next.

Only three data layers here, duplicated

Step 4 - style the point layers

There are three copies of the points layer. One is filtered to only show major world cities, and is represented by a square marker 2.0 size, 0.4 stroke width) with an upper case label and a semi-transparent background, with rounded corners. One is represented as spikes, based on population. And one is represented as fake shadows for the spikes. The spike and shadow layers use the QGIS Geometry Generator to convert the original point data to line data. See below for a screenshot of each layer's symbology.

The label settings for the point layer (font size is 10)

The main symbol settings for the point layer

Label background settings: #333333 is the label background colour, I used 45.2% opacity (in the Opacity slider in the Background options, rather than the Opacity slider in the colour options, but it probably doesn't matter which way you do it. I like the slightly rounded corners, so that's why the 2.0 values are in the Radius X,Y boxes.

To display only the cities you want, an easy way is to right-click a layer and use a filter (right-click > Filter...) and then here's what I used below to filter it, but you can add any cities you want of course, so long as they are in the dataset. 

Note that I used two different rules here - the second one is a list of city names that are also recorded as having a 1 in the "worldcity" column in the attribute table for the layer, but then I also wanted to add a few more that weren't classified this way, so I added a few more using the first "name" IN rule. Note that I have sometimes put an x or a city name with XXX after it when I decide to hide a city that I previously wanted to be on the map. This is just to remind me of what I was doing. Confused? Then either take some time to understand it by looking closely at the text, OR, just copy and paste it in and then play around with adding and deleting places. 


"name" IN ('Karachi','Dakar','Kinshasa','Tehran','x') OR

"name" IN ('Shanghai','New York','Madrid','Beijing','Tokyo','Paris','Moscow','Auckland',

'Sydney','Brasilia','Mexico City','Los Angeles','São Paulo','Buenos AiresXXX','Lagos','Cape Town',

'Cairo','Jakarta','TorontoXXX','Istanbul','Manila','Tunis','Nairobi','Dakar','Melbourne','Lima','Bogota',

'Santiago','Berlin','Mecca','New Delhi','London','Seoul','Rome','Mumbai','Hong Kong','Singapore'

) AND "worldcity" = 1

 

The bits of text in the double quotes are columns from the layer's attribute table

Okay, but how do you turn a point layer into spikes, or fake shadows? You use the Geometry Generator options in QGIS to do this, as shown below.

Here's the text you need to input for the spikes (below), which are based on the "pop_max" variable in our Natural Earth populated places shapefile. This makes a line from the points and the length is set to the value of the population, divided by 1 million. Why? Well, because the map units here are in degrees, and because the Tokyo metro area has about 35 million people, that means the biggest spike will be set to 35 degrees - if your dataset was in metres this would be too small and you wouldn't see any spike! 

If you're unsure exactly where  to find the Geometry Generator option, just right-click a layer, go to Properties... > Symbology and then where it says Marker towards the top you should see Simple Marker below that. If you then select Simple Marker look below that to see Symbol layer type - which should say Simple Marker right now, and then change it to Geometry Generator. Then you'll be able to replicate the screenshot below and add the text you see in the bullet point.

  • make_line($geometry,make_point(x($geometry),y($geometry)+ ("pop_max"  /1000000)))

 

This is for the vertical spike layer

Symbology for the spikes: 0.15 line width, #333333 colour. 

I decided I'd quite like to have some fake shadows for the spikes on my map as well, so I used a similar approach to generate these - I just added an offset angle. Note that for the symbology on the shadows I made them 0.35 thick (compared to 0.15 for the actual spikes) and also 10% opacity, so they are quite faint and not too visually dominant. Here's the Geometry Generator text I used to create these, and note the screenshot of it below as well.

  • rotate( make_line($geometry,make_point(x($geometry),y($geometry)+ ( "pop_max"  /1000000) )),110, start_point( $geometry))

This is the same as above, but it has rotate at the start because I want it to be rotated to a certain angle (in this case 110 degrees) but it also has start_point because I want it to be rotated from the point itself rather than another axis which would mean the shadow wasn't cast from the base of the spike, as it is here.

This is the fake shadow layer

Symbology for the spikes: 0.35 line width, #333333 colour, 10% opacity.

Obviously, these are fake spikes and you may not even want them, though that's not the point here. The point is just to demonstrate some of the capabilities with QGIS in relation to turning a point into a line, or any of the other Geometry Generator things you can do (e.g. simplify polygons, buffer, etc etc). Also note that this spike/shadow hack is not going to work if you change to a different kind of projection - e.g. anyone where the lines of longitude are not vertical - see below for a bit of Winkel Tripel!

Thanks to Oswald Winkel for his projection

Okay, that's the points layers - these were the trickiest ones so now let's look at the countries layers.


Step 5 - style the countries layers

The use case I'm imagining here is where someone wants to produce a locator map, with some cities named and then a country highlighted. The spikes I added above is just a way to demonstrate how you can use the Geometry Generator options to do interesting things. For the countries, we have two layers, one of which is filtered to only show China (and this is China based on the definition of China in the Natural Earth dataset).

  • The top layer is just filtered using "NAME" = 'China' (remember, right-click the layer, then Filter...) then a fill colour of #ef452f with opacity set to 38%. Stroke colour is #c93a27, 0.46 width. Nothing fancy.
  • The lower countries layer is just colour #e6daa1 for both fill and stroke, with stroke width 0.26. The only extra thing here is the slight drop shadow I used, to continue with the fake 3D effect. This is done by using the Draw effects options, as in the screenshots below.
You can do all sorts of great things with Draw effects

You may prefer other colours but this is what I used


And that's how I styled the countries layers. Nothing very complicated at all, but the drop shadow just lifts the map off the page a little and adds to the 3D effect, for a bit of fun.


Step 6 - style the grid layer

I decided to make the grid serve as a kind of canvas, as well as a geographical reference point, and I wanted to give it a drop shadow too. You can do this using only one layer with Draw effects but I found it works better using the drop shadow on a separate layer, so here's what I did.

  • The top grid layer is #70c8df fill colour and #ffffff (pure white) line of width 0.1. This gets us a nice blue grid with white map markers every 10 degrees of lat/long on the map.
  • For the grid shadow layer, that was done via the Draw effects options and all I had turned on here was the drop shadow itself, as you can see from the screenshot below. The drop shadow colour is #000000 (black) with 75% opacity and you can see how this lifts it off the page for another bit of 3D effect.
Again, this isn't essential, but it can be quite nice to do


Okay, great - we should now have a nice grid layer, some countries, China highlighted, city spikes and shadows, plus a number of city labels. Just a few more things and we're ready to export the final map.


Step 7 - background and QGIS logo

I wanted the map background to be darker than the map canvas so I went to Project > Properties and on the General tab on the left I set the Background color to #5facbf. That's just a darker shade of blue.

To add the logo, which is an svg file, I went to View > Decorations > Image... and then added the logo that I downloaded from the QGIS website, although you can also just paste in the path or url into the Image path box (see below). You can add other image types but you'll probably find that svg gives the best output quality in your final map.

Add a logo to your map layout

After that, all I did was make sure I'd zoomed out enough so that there was a bit of dark blue map canvas surrounding my whole world map. See below for a closer look at that.


Step 8 - save your map as a high quality png file

We're not going to bother with the QGIS Print Layout here at all. Sometimes we don't need to and one of the great things that the QGIS team has done in recent years (among many, many things!) is add more options for exporting high quality images directly from the main map view. So, to export the final image you see below, I just went to Project > Import/Export > Export Map to Image... and then changed the Resolution to 300dpi and unticked the Append georeference information (embedded or via world file box because I don't need that file, but it's not a problem if you keep it ticked, it just generates a small extra file. Note you could just as easily copy and paste the map using the Copy to Clipboard button.

And there we have it - one version of our world


Final notes

Obviously I haven't included every single little click, but there should be more than enough detail to replicate these methods if you have a basic familiarity with QGIS already. If you are left scratching your head though, please feel free to get in touch.

Don't like the cities I used? That's fine, they are not particularly well thought through - the idea here is more about showing how to pick your own ones.

Don't like the boundaries I used? Again, this is for demonstration purposes but of course that is something we still need to be aware of. 

Don't like the spikes? That's fine, they may be too much for this map but they can be useful in other situations and it's more about understanding what the QGIS Geometry Generator tools can do.