Lesson video

Hello, my name is Mr. Conway.

I'm very pleased to have this opportunity to guide you through today's geography lesson.

The emphasis is gonna be very much on GIS or Geographical Information Systems. So let's get started.

This lesson is part of a unit called Global Pattern of Resources.

By the end of today's lesson, intention is that you'll be able to use GIS desire lines to visualise, analyse food miles.

You'll be learning to use these GIS techniques which can be applied to lots of spatial data that we use in geography, and some of the learning may be new, but I'll be here to support you along the way.

To help us achieve the outcome we need to learn or remind ourselves about certain keywords.

These are the keywords for today's lesson.

Food miles, desire lines, great circles and pop-up.

Let's look at the definitions for each of these keywords.

Food miles is the term used to refer to the distance food items travel from the point where they're produced, that's where it's created or harvested in the first place to the point of consumption, not necessarily measured in miles, but obviously we can use other measures such as kilometres.

Desire lines is a graphical technique using lines on a map to show the simple direction of movement from one place to another.

Great circles are straight line routes, which appear curved on 2D maps because they account for the curvature of the earth.

And finally, pop-up is something we use a lot in GIS, which is a read-only display of information about attributes and things like text, images and charts often linked to a particular location.

There are two learning cycles for this lesson looking at how we use GIS desire lines to visualise and analyse food miles.

So we're gonna look at the first of these learning cycles now using desire lines to visualise food miles.

Much of the UK's food is imported from overseas from other countries.

Nearly all food imports travel by ship usually in containers.

All of this transportation creates a carbon footprint because most of that transportation requires the consumption of fossil fuels.

So a key question for us as geographers is where are the places that that food is travelling from? And to help us investigate this question, how can we use GIS to visualise the sources of our food? How can we use GIS to calculate our food miles? Here's a world map showing trade as a share of each country's GDP.

This is sometimes called the trade openness index.

Now GIS can be used to visualise this trade such as food and imports, and you'll notice that what's happened here is that GIS is actually used the choropleth map.

We might ask ourselves, how effectively does this choropleth map show international trade? Perhaps it shows the share of trade quite well, but not really the movement of that trade.

How can we visualise that better? What other GIS techniques can we use to visualise and analyse food trade? At an international global scale, such as this world map or any large scale map, desire lines are more useful than flow lines to visualise food imports or exports between source and destination countries.

Desire lines can convey a lot of information, particularly if they are GIS desire lines.

The width of the desire lines can visualise attributes such as the quantity of food.

The length of a desire line can visualise the food miles themselves, and then pop-ups can provide further details such as the actual distances for the food miles.

GIS shows desire lines as great circles.

Great circles are straight line routes which appear curved because they take the curvature of the earth into consideration.

How can we create and configure desire lines using GIS? Well, one useful way to do this is to consider food miles for a popular meal.

So talking of popular meals, chicken korma is one of the most popular meals in the UK.

What are the ingredients that go into that meal? Where do we get those ingredients from? Let's find out if we can map the sources of the ingredients and calculate the food miles for all those ingredients.

What are the ingredients of chicken korma? Well, here they are, quite a long list.

Take a quick read through these.

You'll see there's quite a variety of ingredients and they're sourced from many countries, including the UK, it must be said.

Several of the ingredients are sourced from more than one country.

So how can we use desire lines to visualise food miles? Let's find out.

Here's a guide showing you how that's done.

This video guide shows how we can create GIS desire lines and then configure them to visualise food miles.

Open the ready made map called food miles and then click on the layers panel on the left and you'll see one layer appears already, which is UK as a food destination, the red dot just here.

And we're going to make the other layer visible by clicking the visibility icon here.

And you'll see that the various source countries for the ingredients of chicken korma appear.

That's why this layer is called food miles, CK standing for chicken korma.

It's abbreviated so that we can make the attribute titles a bit shorter later on.

In order to create the desire lines, what we need to do is to tell the map which destination we're going to use and also to tell it what the sources are of those ingredients.

So we go to the food destination, we click the small three dots here to open the properties.

Three dots stands for the options, and we're gonna go to the analysis tool, which is shown by this icon here in the right panel.

We click that and we then see some options for tools.

So we click tools and then we scroll down to see the used proximity dropdown.

So we click that and then we'll see one of these tools is called calculate travel cost, and in spite of its name, that is the one that will create desire lines.

So we click that and open to panel inviting us to tell the tool where do you want the layers to come from and to.

So we want the information to come from the ingredients, which is the food miles chicken korma layer represented by the orange dots on the map.

So we select that one for from, and then we say we want it to go to, obviously to the UK.

So we click layer and then we can see the UK food destination.

We select that one for the to layer.

Our next step you have to scroll down a little bit more for this one is just to select the measurement type.

Now in our case, we want to select something called line distance.

The default is for driving time, but if you click the drop down here, you'll see the last option is the one we want, which is line distance, so we select that.

So as long as that says line distance, we are going well, then we need to give our output layer a name.

This is the output for the desire lines.

So I'm gonna click on that and type food miles UK, keep the name fairly simple so that that will make life easier later on for attribute names, et cetera.

Then we click run and it will start to generate the desire lines.

You can check the view status by clicking this blue button here and it gives you a rough idea of the progress that's being made.

The process of creating the desire lines can take a little while depending on internet speed.

So a successful result, our desire lines have been created and we want to save that work.

So we click save and save our map.

You can give it a different name if you want to.

For example, you call it food miles one or food miles with your initials.

And then we've saved our work and we can move on to configure the lines.

Now, configuring our food miles desire lines means making use of the data that they're carrying.

If we click on any of them, we see in the pop-ups that there's an awful lot of data that they have and some of that data could be quite useful.

So to make use of that data, we find the food miles layer, just check that it's the correct layer by switching the visibility on and off, making sure we leave it on.

Go to the options for finding, where we find show properties and then we find properties.

We go to the symbology panel just here and click edit layer style.

And the first option choose attributes in this section, it's by default showing destination ID.

We don't really want that, so we're going to click the X to delete that, but we're going to click field instead to make a selection of fields we do want to show.

So we click field and then scroll down to select two of the attributes.

And the ones that we want are about the number of ingredients.

So we see one there quite near to the bottom number of ingredients, and we click that.

And then the next one we want is going to be to do with the country that we are sourcing ingredients from.

And there's one there called source country.

So we click that one and then we click add to make sure the lines reflect those and the lines will change.

And straight away we see an improvement with the temporary legend here.

So we have colour coding for the countries, the source countries, and further down we have proportionalized the desire lines to show the number of ingredients that different countries supply.

So what we have here are default options, but we can refine those further if we click in this section pick a style, types and size and click style options.

And then find the panel that says counts and amounts, size, and once again, click style options for that and we're going to change the size range, but before we do, so just untick this one that says adjust size automatically.

And we're not gonna change the size that much, so I'm gonna untick that and we're gonna change the pixels for the lower end to two.

And you can see the smaller contributors have gone up to make them a little bit more visible.

And then we can make the larger one larger gonna suggest we go up to 18 and then we click done.

Now we could leave it at that, but there is another option before we carry on.

You can go to the types and styles section here and click style options where you have the option to change the symbol style, you click the pen and it will give you different colour ramps that you can choose.

I'm not gonna do that, but that is something you could do.

So when we got to that stage, we clicked done, three times and we have our map showing the configured desire lines to show food miles from different countries providing the ingredients to the UK for chicken korma.

One last thing you might want to try to make the visualisation a little bit more effective is by changing the base map.

So I'm gonna click the base map gallery and select dark grey canvas because that shows up the desire lines a lot better.

So once I've done that, I'm gonna shut the base map gallery and then click legend so we can interpret the symbols using the food mile colours for the source countries and the variations in their widths in proportion to number of ingredients the countries supply.

And then we can save our map as we have done before.

Soon you'll have the opportunity to create and configure GIS desire lines for yourself.

But let's just check up on a couple of points from the video demonstration first.

For our first check, when desire lines appear as great circles, what 3D shape are they trying to take into consideration? You may wish to pause the video here and restart it when you've selected your answer.

Well done if you selected sphere, yes, the world is round, a sphere, so when we see straight line route over any distance on a 2D map, they will tend to appear curved, especially over long distances.

Now for a second check, when using the calculate travel cost tool to create desire lines, which icon represents the layers that we need to link? You may wish to pause the video here while you think about that.

Okay, so the correct answer is A, well done if you got that right.

Now for a third check, when using map viewer analysis tools to create desire lines, in which section is the calculate travel cost tool found? Again, you may wish to pause the video here while you have a think.

The correct answer is B, the sequence which opens the tools menu, and then we use the use proximity tool.

Now for some tasks which are gonna help you create, configure GIS design lines yourself.

For these tasks, you're gonna need to open the link provided, which takes you to a ready-made web map in ArcGIS Online called food miles.

In task one, you're going to create GIS desire lines.

Then task two, guides you through the steps for configuring those desire lines.

So pause the video now to take some time to undertake those tasks, and when you're ready, press play again to obtain some feedback on these tasks.

Hopefully you were able to undertake those tasks effectively.

For task one, your web map desire line should look something like this.

For task two, your configured desire line should look something like this.

And you might notice the legend has been switched on and the base map dark grey canvas has been used to enhance the visualisation contrast.

If your answers were very different or you recognise some errors, take another look at the video demonstration.

In our second learning cycle, we're going to learn how to use our GIS desire lines to analyse food miles.

When GIS desire lines are created, the GIS doesn't just visualise the food miles.

Other useful data are generated in the background.

So how can we extract this data, this useful data about food miles? Well, the pop-up for each desire line can show the food miles distance for each ingredient.

And yes, Alex have some patience, we're going to see how we can configure the pop-ups to show food miles.

We can also extract the data to a spreadsheet for analysis.

Fair question Aisha, "How do we download this food miles data?" We'll see how to do these things shortly, but it will be useful to provide a little explanation first because there are a few steps involved.

in your ArcGIS Online account in content, which looks like this items such as desire lines are saved as what called feature layers, for example, food miles UK.

Then in item details, you can find the overview menu.

You need to click the button that says export data, and in the dropdown button that appears, click export to CSV file.

The next step is to click the three dots to download the newly created CSV file and select a suitable location on your device for that download and remember where it is.

The first four columns of your downloaded CSV file entitled routes, should look like this.

Column C shows desire line distances in miles.

Column D shows desire line distances in kilometres.

Then we can add a formula for calculating the total distances.

In each cell, under distances, we use an automatic calculation formula such as auto sum or similar, to calculate the sum of the distances.

We're now going to follow a second demonstration clip so that we can see how to use GIS desire lines to analyse food miles.

So we've created our food miles desire lines, we've configured the lines themselves.

How can we now configure the pop-ups so that they're more useful to show data about the food miles? And furthermore, can we actually download the food miles data to analyse that information? So let's start by configuring the pop-ups.

We need to go to the layers panel and we need to go to our food miles layer, which is of course the layers of the desire lines.

You can see them there switching 'em on and off.

Make sure that we leave them on.

We then click the three dots to make sure the properties panel opens up.

And then we can work through this by going to the icon for pop-ups and we can see that here.

We click pop-ups and then we can move on to configure the pop-ups and you'll see a progress panel opens up so we can see what happens as we go along, which is useful.

The first thing we're going to manage is the title of the pop-up because the default is not actually very useful.

It doesn't really mean anything.

So we can see where we can configure that in here, which says title, and we're going to remove what is said there already, completely delete that and replace it with a pop-up title that's going to say source colon.

And then pick up the data from source country in the spreadsheet underneath.

So for every pop-up, it will then say source colon, and it will give the name of the country and keep it nice and simple like that.

Then we're going to need to manage the rest of the pop-up, which you can see contains an awful lot of information, some of which is useful, but some of which isn't, and it's not terribly easy to visualise.

So what we can do is keep the panel open so we can check our progress.

First of all, we're going to go to the fields list where we manage that information, that text, and we're going to delete what's there.

You'll see it all disappear.

Then we're going to add some content and we add that as text.

So we're going to customise effectively what we show in the pop-up.

We're gonna right click and paste some text into here, a formula of words and click okay, I'll explain this in just a moment.

So we can see that we've picked up by writing number of ingredients equals the number of ingredients and the actual ingredients from each source.

Then we've got the food miles equals, and we've picked up that data there and we've got the food kilometres as well, which as you'd expect is a higher number.

Now if we go back to edit text, we can see how that works.

We've picked up these things in curly brackets and they're shown in this list here.

So we literally picked them up from there, but I've made that a little bit easier for you by giving you the formula of words in advance.

But you can create your own formula of words as well.

The setup or layout of the words can also be improved.

So where you've got semicolons here, if we just delete them and put return or enter, it should mean that the layout in the pop-up is a little bit more amenable.

So if we do that and click, we see that we've got them set out like that.

So this is clearer to see, and we can check that by clicking any of the other desire lines and we see the number ingredients, which ingredients they are, and of course the food miles or food kilometres.

So what we're gonna do next is just have a look and see if we can enhance that pop-up a little bit further.

We're going to click add content again, and this time we're going to add an image.

So we click image and we look for the URL.

We don't need to fill up any of these details here.

We just look for the URL and we're going to search for the URL, which shows the flag of each country.

And you can see one here that says from flag URL, we click that click done.

And you can see it also provides us with the image of the flag for each country.

So if I click around again, you can see each country's flag appears as well as the pop-up details.

So we've got some good looking pop-ups there.

So let's just shut the layers panel and the properties panel and we can look at our work and see that we have improved things.

It looks much the same as before, but we've of course have improved the pop-ups for all of the desire lines.

So let's make sure we look after this good work and click save.

So we've seen the data generated by the desire lines, especially in the pop-ups.

How can we do something a little bit more with that data? In order to do so, we need to move away from the map, in fact.

So we're gonna go to a new window and if you open up just the line again, if you need to, and from the homepage we then go to content and hopefully you will find a food miles layer that looks like this, and it will probably say feature layer, hosted after it.

If it says feature layer, hosted, that's gonna enable us to use it to analyse the data.

So we click the three dots at the end of this and we're going to view the details.

You can double click on the layer as well to do this.

So we're gonna view the details of the desire lines layer, and among other things, it gives us the option here to export the data.

So if I click that and you can see one of the options is to export the data as a CSV file, export to CSV file.

So if we click that, it then invites us to give the file a name.

So I'm going to just make sure we don't muddle it up with other ones by just putting CSV at the end of it.

That's a Comma Separated Values file.

It's a type of very simple spreadsheet, very versatile.

And click the export button and the CSV file appears as another item and we can click download to download the data from it.

So I click download and it asks us to download to somewhere on our device.

So we're going to click that.

So we've downloaded that data.

Then we go to the place where we have saved the data, and it's a zipped file.

So we use whatever means your device uses to extract data, and we're gonna extract the data and keep it in the same place.

And we see that the data is already opened as a file called routes underscore zero.

That's the default name for the data from the desire lines.

And when we open the data, we see the CSV file content, the single sheeted spreadsheet, and it shows a whole load of data that we can use.

What we're particularly interested in are these two columns here that shows the straight line distance in miles, and this one shows the straight line distance in kilometres.

So once the data's in the spreadsheet, we can use a fairly simple auto sum by clicking the bottom of one of those columns.

This is, remember, it's the straight line distance in miles.

So if we click there and add the sum of the total distances above that and press enter, we get the total for the total number of miles.

And we could do the same thing for the kilometres.

We're just gonna add an auto sum in there, and we can also find the total for that one by clicking enter.

So we have the two totals for those.

Then in much the same way, we can calculate the average number of food miles for the ingredients.

We click on the cell at the base of the column for straight line distances in miles.

This time we choose an auto sum for average, we click enter and we see that the average or mean is to the nearest mile 3,274 miles, and we could do the same thing for the kilometres.

So we find the average or mean of those and we find out the answer to that is 5,269 kilometres, the nearest.

Soon you'll have the opportunity to use the desire lines to configure their pop-ups and to calculate food miles.

But first, let's just check on some points in the video demonstration.

Firstly, is it true or false to say that food miles must always be measured in miles? Just pause the video here and restart it when you've selected your answer.

The correct choice here is false.

Why is it false? Once again, pause the video to decide why it is false.

This statement is false because any units of measurement can be used, including food miles or kilometres.

Food miles is what we might call a generic term used to refer to the concept of distance travelled by food and drink items. Here's your second check, which menu in ArcGIS Online is the place to find and download data contained in desire lines? You may wish to pause the video here and restart it when you've selected your answer.

In this case, the correct choice is content, a menu in ArcGIS Online.

Now for the tasks which will help you to use the desire lines to configure their pop-ups and calculate food miles.

As for the tasks in learning cycle one, you will need to access the same map about food miles on the link provided.

In task one, you're going to configure the pop-ups for the desire lines.

And in task two, you're going to use those desire lines to calculate the food miles.

So pause the video now to take some time to undertake those tasks.

And when you're ready, press play to obtain some feedback.

We'll see you on the other side of these tasks.

Hopefully you were able to undertake the tasks effectively.

For task one, your configured desire lines pop-up should look something like this, visualising details such as the source, country name, range of ingredients, and the country flags.

For task two, your calculation of food miles should have gone something like this.

The total food miles in miles should be something in the region of 78,575 miles, which would create an average or mean of 3,274 miles.

If we choose metric measures, which is fine, the total food miles in kilometres is 126,454 kilometres, and that produces an average or mean of 5,269 kilometres, and those answers are to the nearest kilometre or mile.

As an option, you may have generated column charts as well to compare countries using the desire lines data.

The first chart here compares the distances of food miles, and we find that the top three countries for food miles are Indonesia, Chile, and Vietnam, in that order.

But that data might be misleading because we also need to consider how many ingredients each country provides.

For some countries, they might only provide one or two ingredients, whereas others may provide quite a few.

So the second chart here compares the countries by the number of ingredients that they provide, and we find that the top three countries for ingredients are India, Netherlands, and Spain, in that order.

Let's round up our findings.

In answer to the question, to what extent are these results close to expectations? We all thought, similar to Aisha, who says, "It was amazing that the ingredients for just one meal could be sourced from so many different countries.

It would be interesting to compare the results with other popular meals." Agreed it would.

And Alex suggests that, "The distances are really surprising.

I had no idea that food ingredients travelled so far.

The carbon footprint of imported food must be significant." And finally, how effectively do desire lines help us to analyse food miles? Izzy commented that, "Desire lines are useful to show great circle routes from ingredient source countries and their locations relative to the destination country." Laura points out that, "Proportional desire lines help us to compare food miles from source countries.

Pop-ups visualised details such as the source country name, range, ingredients and flags." And Sophia concluded that, "Downloaded desire lines can be analysed such as distances to calculate food miles and then compare sources.

And it's useful to calculate the carbon footprint of the ingredients and meal." So well done.

What we've been doing in this lesson is learning some GIS skills, which can be applied in different situations, and it's this kind of deliberate practise that can help to make these GIS capabilities fluent.

So let's just summarise our learning in this lesson.

First of all, we can say that GIS desire lines can be created using GIS to visualise food miles.

They're actually straight lines, but they follow great circles, so they may appear to be curved, particularly on 2D maps.

We can configure desire lines with pop-ups to improve visualisations.

And these can be used to analyse food miles for ingredients or source countries.

So we found out how to create and configure desire lines to enhance our learning about the food miles and therefore one of the great resources of the world.

This is great work, which has maybe made you hungry for food or maybe hungry to find out more about GIS in geography.

So it's been a real pleasure to take this learning journey with you and hope to see you again soon.

So bye for now.