ONE UN - Future urbanisation, how will your city change over the next decades (WUF13)

Welcome.
Thank you for coming.
We're delighted to have you here, and we wanted to talk to you a little bit about the future of urbanization, how cities are going to be changing.
And we're going to have some joint work presented here.
We'll have Cheryl Sawyer.
She is the chief of the Population Trans and Analysis branch at the UN Population Division in New York.
Then I'll be presenting some of the city focused analysis.
I'm Lewis Dextra.
I work for the Joint Research Center of the European Commission.
And afterwards, we'll have a panel session to discuss these results and how they can be used by researchers, by cities, by policymakers, and that will be moderated by Ruger Iron from the OECD.
So without too much further ado, I would like to pass the floor to Cheryl and she'll be kicking off with the first presentation.
Thank you very much.
Good morning.
Can you hear me okay? Great.
Thank you.
This morning, I'll be presenting the results of the UN's World Urbanization Prospects 2025, which was released last November.
The presentation is titled A New Lens on the Global Settlement Continuum.
We chosen to title it this way because as you'll see coming up in this revision, we made a major change to the publication adding the Degree of Urbanization Technology, which Luis will describe for you in detail.
But also keeping our previous methods of organization estimates and projections based on national definitions.
This gives us a completely new look at global settlement patterns.
Okay.
Before I start, let me introduce for those who may not know the population division of the UN.
We are in the UN Secretariat in New York as part of the Department of Economic and Social Affairs.
The population Division was established in 1947, for the demography out there, it's the same age as my parents as the Secretariat to what was then called the Population Commission, now the Commission on Population and Development, which is a subsidiary body of the Economic and Social Council, which is one of the main bodies under the General Assembly.
So we're the Secretariat to the Commission on Population Development, and it's for them that we produce the analyses that we produce.
I thought I took this animation out, but let me just through.
So there are three parts of our work under our mandate, and they're interrelated.
The product I'll be talking about today is part of our analytical work.
And here you see our analytical work, which covers population estimates and projections, and the best known product of ours is the World Population prospects, which you see our Assistant Secretary-General holding up here.
We also look at the components of population change, so fertility and relatedly family planning, mortality and international migration.
We do studies of population age structure and aging, and what I'll be talking about today, urban and rural population change, relationships between population and sustainable development and population policies.
And then the other components of our work are intergovernmental or normatives or support to intergovernmental bodies at the UN, and we also do capacity development on population topics.
Okay.
So what is World Urbanization Prospects 2025? The Population Division has a more than 60 year legacy of analytical work on urbanization.
We've been producing the World Urbanization Prospects since 1963, and the 2025 revision is the 22nd edition.
It covers 237 countries or areas of the world.
The numbers we publish in this publication are estimates for 1950 to 2025 and projections for 2026 through 2050.
The new version includes more than 12,000 cities with greater than 50,000 inhabitants.
In comparison, the most recent revision in 2018 covered only 1,900 urban agglomerations with 300,000 or more.
The estimates are consistent with the world population prospects 2024 medium variant, and as I will say already and several more times, the 2025 revision presents a dual approach, official national statistics as well as harmonized geospatial methods.
So let's talk about the urban definition challenge.
Since the beginning of world urbanization prospects, the population division has faced this definition challenge.
Historically, countries use diverse criteria to define urban.
This may be based on one or a combination of the factors listed here, administrative status, population size, density thresholds, economic functions, or urban characteristics.
Some examples of these are Japan where an urban defines a contiguous area with 50,000 or more inhabitants.
Then we have Norway and some of the other Nordic countries where it's a locality with at least 200 inhabitants.
For India, we get one of the more complex definitions.
It's statutory towns plus areas with 5,000 or more people, a density of 400 people per square kilometer, and 75% of the workforce in non agricultural work.
As you can probably understand from those different definitions, did I get the micropho? Is better.
Okay.
Um, So it was not possible to make meaningful international comparisons between countries, and that figure that we published of 58% urban in 2025, it's very difficult to define across the world what that actually means.
In the SDG era, it's also challenging to track progress on SDG 11 when all of the countries have different urban definitions.
There have been earlier attempts at harmonization, including by the UN and others, but up till now, there was no method that was able to provide a globally consistent and replicable definition that could generate a long time series for international comparisons.
There's also growing demand from end users for access to more geospatially disaggregated data.
Nevertheless, we retained a track with the national definitions to reflect the specific contexts and priorities of each country.
I think this is actually the previous version of the presentation.
It's okay.
This brings us to the degree of urbanization methodology.
I won't go into detail here because Lewis, I'm sure will tell us much more about it since it was developed by the European Commission RC, with a consortium of international organizations that includes FIO, UN Habitat, ILO, the OECD, and the World Bank.
This method consistently classifies the entire territory of a country along the urban rural continuum based on population density, contiguity, and population size thresholds applied to 1 square kilometer grid cells.
It gives us a harmonized definition of urban and rural areas across countries, enabling more accurate international comparisons of urbanization levels.
In 2020, the UN Statistical Commission endorsed the methodology for delineation of cities and urban and rural areas for international and regional statistical comparisons, but emphasized that the methodology is not intended to replace national definitions of urban and rural areas, but to complement them.
This is a schematic just to orient you for the graphs I'll be showing next.
So when looking at the contiguous clusters, if it has a density greater than 1,500 inhabitants per square kilometer and a contiguous cluster population more than 50,000, it's defined as a city.
So you'll see those in red in the charts.
The next level down is towns and semi dense areas, density greater than 300 inhabitants and a contiguous cluster population of greater than 5,000.
And below that is rural areas, less than 300 inhabitants per square kilometer or not part of a cluster.
Now, the degree of urbanization methodology has actually a finer grain of classifications, but for presentation purposes, we condense them to three categories.
Again, just to review the innovations in WUP 25, full integration of the degree of urbanization methodology alongside national definitions, collaboration with the EC Joint Research Center, who actually produced the geospatial estimates on which the WP is based, harmonized classification across urban rural continuum, expanded spatial coverage and resolution.
We also have new analyses of built up area land use per capita and urban compactness.
Updated methods for projections of the national definitions on the other track, and also expanded datasets and online data portal.
Now let's get to the results.
The key findings from the WUP 2025.
First, we have a little quiz.
In what year did cities become the most common settlement type? I think for a second.
1996.
I hope you can see the lines, the graphics from my colleagues, the types a little bit small, so I'll try to talk through them.
Sorry.
Okay.
So we have the growth of cities, towns, and rural areas 1950-2050, and the dotted line in the middle shows the split between the estimates and projections.
So 1950-2025, the cities in red, grew from 20% of the population to 45% of the global population as the total population grew from 2.5 to 8.2 billion.
Towns went from about 40% to 36% of the population, and the rural population from 40% to 20% of the global population.
From now to 2050, we expect that two thirds of further population growth will occur in cities and towns will absorb most of the rest.
The rural population is projected to peak around the 2040s before starting to decline.
So that gives you the overview of the degree of urbanization and how it shows us the past and future along this urban rural continuum.
Okay.
Your next quiz.
According to this new methodology, what was the most populous city in 2025? Jakarta.
In the past it was always Tokyo, now, Jakarta.
I'll just do a couple of slides on cities since Lewis will be presenting more on this, but the number of mega cities grew from eight in 1975 to 33 in 2025 with 37 projected by 2050.
The majority of these mega cities are in Asia and the top five largest were Jakarta, Dhaka, Tokyo, Cairo, and Delhi.
However, more people live in small and medium sized cities than in mega cities, of the 12,000 cities worldwide that were defined by the De Gerba methods, 96% have less than 1 million inhabitants, and 81% have less than 250,000.
Most of the city population growth occurs within existing cities.
So in this slide, we have the blue is the growth in existing cities over these different time periods, and yellow is newly emerging cities.
The future growth of the world city population will be concentrated in just seven countries.
Looking at the projected change during 2025 to 2050, and I apologize again, the type is quite small.
Half of the future projected change, so about 500 million new city residents will occur in India, Nigeria, Pakistan, Egypt, Democratic Republic of the Congo, Bangladesh, and Ethiopia.
You can see that the future town growth is similarly clustered in a few countries and projected rural population growth is nearly nonexistent.
Okay.
This is your last quiz.
So while cities hold the largest number of the world's population, they're not the dominant settlement type in every country.
So in two of these countries, towns are actually the most common settlement type.
China.
China.
India and the US.
Hopefully these maps on the next slide are big enough for you to find your country.
They're a little small.
But this is showing what is the most common settlement types? Where do the most population live in each country? In 104 countries in 2025, this was cities, but towns dominated in 71 countries and rural settlements are most common in 62 countries.
What I found personally, one of the most interesting findings was that in several European countries, actually the most population is in rural settlements.
Okay.
And I apologize for the crowdedness of this graph.
So this is where we get to the two track approach.
So this graph and let's look at the left most bar first.
So this is the world, and the black bar is based on national definitions, we get 58% of the world being urban.
And then the red, yellow, and green are the same colors you saw before, so that's 45% cities, 36% towns, and 19% rural.
So compared to the degree of urbanization, national definitions on average are under counting or under classifying, uh uh, denser settlements of an urban nature, and the world is more urbanized than national statistics suggest.
Um So again, I'm not sure how well you could read from the floor, but if you go over to the third region over is Central and Southern Asia, and we see there that, in fact, a lot of what Da Gurba captures as cities are classified as rural under the national definition.
But remember that included 75% of the male workforce not in agriculture.
So there's probably a lot of issues contributing to this.
And then also in Sub Saharan Africa, you have quite a few of the sub regions there with urban definitions that mainly are only capturing cities and not towns.
Okay, this one might be a little easier to see.
So this is showing you over time how this gives us a new view.
So the top left square is the world, and the black line is the national definitions.
So you can see that national definitions went from 29% urban in 1950 to 58% in 2025.
And so we're missing it's 67% projected by 2050, whereas degree of urbanization, cities go 20-45 to 48%.
So we got the same general trend in urbanization, but at a somewhat different scale.
And you can also see clearly here.
So if you go down to the bottom left square that is Central and Southern Asia, where the national definitions very closely track cities and are not including towns and semi dense areas.
And the same for sub Saharan Africa.
This is just showing one of the other new results we have, so I won't spend as much time on this, but if you're interested, there's a bit on it in the report, and I think it will definitely be an interesting area to study.
Catch up with my notes here.
So these graphs are comparing the expansion of built up areas to population growth, and we have the built up areas in gray and population growth in purple, and on the left is the total global and on the right is cities only.
So globally, built up area per capita has grown 43-63 meters squared per capita, so it's grown twice as fast as population 1975-2025.
And on the right side, we have the cities.
So we get two messages here.
I So built up area and population have grown about the same pace, so compared to towns semi dense and rural, cities are growing more efficiently.
I think this again will be an area for more study.
At the population division, we are not land use experts or geographers, so I hope that some experts will take up these data and do some more exploration with it.
Okay.
So lastly, just a few key recommendations that are coming out of the WUPops I had added a new bullet just once again, that's not here to come back again to this notion of shifting our perspective or our lens from an urban rural dichotomy, so a boundary between urban and rural to this urban rural continuum from the degree of urbanization.
In fact, in the report, it is world urbanization prospects, but we had to work pretty hard to make this message very clear and really not using the word urban very much at all.
So we don't actually publish a percentage urban, in the new report.
So you can add up the cities and towns and get something urban, but it's not really equivalent, and probably Lewis can talk some more about how we should understand this.
Then some of the findings that came out so we uh, concur with adopting the De Gerba method for international monitoring, but maintaining these estimates and projections of national definitions since these do still have some domestic use for policies, and it's also interesting to see how countries are defining this.
Um, We may wish to focus on the rapidly growing smaller cities, which would need planning support.
One thing I did not present in here, but we note in the report is divergent trajectories.
So even in countries that have populations still growing, you have cities, some cities shrinking and vice versa.
So you have countries where the population is stable or shrinking, but they have cities that are growing.
Um, towns are another area of focus, not to get lost in between the urban and the rural, so we need to strengthen town planning and for balanced development.
We stress the need to invest in data infrastructure, such as censuses and geospatial integration.
And then we have these new findings on land efficiency.
So it's important to use geospatial data to track land use, built up area per person, and compactness, which can hopefully contribute to better policy and curbing sprawl.
Okay, so that's all that I have.
Up here, we have the links to our website and data on plots.
But I put a QR code because I know everyone is on phone.
So that will take you to the launch page for World Urbanization prospects, where you can link to the reports and the datasets.
And then we also have links to the European Commission datasets, which are also very rich and fun to play with and look at your own city.
And I'm sure Lewis will tell you more about this.
So and then we have two publications.
I'm showing here we have the summary of results, and then we also have a data booklet that focuses on the cities, so the world cities in 2025.
So thank you very much.
Okay.
And I'll be happy to take questions after the presentations.
Let me hand over to Oh, okay.
So my name is Cheryl Sawyer.
I'm from the Population Division in the UN Department of Economic and Social Affairs in New York.
Okay.
No.
Thank you very much, Cheryl.
Very happy to present to you a bit more of the city focused work.
I do encourage you to check out all the data visualizations done by the UN POP division.
So really nice work there and also the data booklet, really useful to try and understand how this is changing our perception of the world.
So I'm going to zoom in a little bit on individual cities because really this time is the first time that we weren't just able to cover 12,000 cities.
We were able to cover every single city in the world.
So if you live in a city, it should be in here.
So but before I jump into the detail, let me back up a little bit because we are asking you to take a new lens, to take a different approach, to look at urbanization from a different angle, right? And this is the degree of urbanization.
This is not brand new.
It's something we started developing ten years ago.
We started off at the, um, Habitat three conference ten years ago in Ecuador and Quito, where we committed together with the OECD and the World Bank to develop this definition.
Then we were joined by the FAO, ILO, and UN Habitat.
And so for four years, we really did a lot of work to kind of change it, improve it, consult it, and really make sure that we were had a result that people liked, that people recognized, right? And so you and habitat helped us tremendously.
They did lots of consultation workshops.
In Europe, it was a methodology that we were already familiar with that we had developed, but we wanted to enrich it and make it more suitable for global application.
And these regional workshops gave us a lot of feedback.
So I think this is one of the most heavily consulted methodologies out there, and I'm very proud of that.
I want to thank you and Habitat for their support on this front.
So in what in statistical terms is record time.
We got this endorsed within four years of saying that we were going to try and do this.
And, you know, statisticians are very reliable, but also a little bit of conservative group, so they don't jump, you know, it's not because you think it's a good idea that they're going to agree, but this was something that they were willing to endorse, not to replace, but to complement national definitions.
So what's this definition? Cheryl already hinted at it.
There's two levels.
There's one level one where we have three classes, and it all depends on what you find in little squares of one by 1 kilometer.
First, we classify the squares by density, and you can see those on the vertical axis.
Then we glue the cells together, the ones that touch the contiguous cells, and we add up the population.
So you have enough cells together of 1,500 density, together, 50,000 people, you have what is a city.
And then towns and semi dense areas, it's over 305,000 inhabitants and the remainder is rural.
But rural doesn't cover a large part of the population, but it covers almost the entire globe.
When we worked with FAO, they were like, Well, we should have some differentiation here as well.
We introduced villages and dispersed and very dispersed rural areas.
Towns and semi dense, the name suggested, it's not one thing, it's two things.
We also split that into dense towns, semi dense towns, and suburban or para urban areas.
Again, purely based on these density and size thresholds.
Now, here are a couple of examples from the World Urbanization perspect.
You can see some towns and a high income or a low middle income country.
On the left, you can see Berlin and Dhaka, and you can see some towns in Poland and in Colombia and some more rural and village settings on the right.
Now, since 2020, we have been working very hard to help countries implement this because, yes, the UN Statistical Commission endorsed this work, but it said, you need to make sure that this is not just a theoretical piece of work, but it's applied and that countries know how to use this and produce data using these definitions.
So together with UNFPA, UN Habitat, UN Statistics Division, UNICEF, World Pop, World Bank, OECD, we've been helping lots of countries develop the skill to apply this methodology.
It takes a little bit of work, but it's not super complicated.
And we'll hear later from Azerbaijan, who's participated in some of those workshops and has applied that definition as well.
So here you can see that over 100 countries know how to apply this country this methodology already, and that means more than half of the countries in the world, right? Not all of them are producing data with it yet, but they have applied it once, or they understand how to apply it compare to their national definition and given us feedback on those results.
So this is level two.
So we can see changes in population by the degree of urbanization level two, in red, you get the cities, and you see this big increase since 1950 in the share and the total population in cities.
But as the global population growth starts to slow down, you can also see that urbanization is starting to slow down.
So yes, we'll see more people living in cities in the future, but that growth rate is slowing down, and a certain point it's likely to plateau.
Because a lot of our urbanization is driven by natural growth.
It's not just by migration, but actually it's often by natural change, a village growing into a town, a town growing into a city, and over time, you see that share change.
You can also see here, as Cheryl mentioned, that the rural share dropped by half since 1950, and it continues to shrink, and it will even shrink absolutely, but more slowly, right? And we see a little bit of suburbanization, that yellow, those are the semi dense or pa urban suburban areas.
They've grown a bit, and then the towns are relatively stable, although they have also shrunk in share.
This is the same picture that Cheryl presented, but here, instead of showing three classes, I wanted to show also the towns and the villages to emphasize that depending on the country or the region you're in, some countries have cities as their primary goal of their national definitions, but some countries have added towns, right? And sometimes they also add suburbs or even villages to it.
So for example, in Latin America and the Caribbean, it includes cities, towns, and suburbs.
In Europe, North America, Australia, New Zealand, it even includes some of the villages because actually their national definitions are, how shall I put it, very generous, very broad, right? Any kind of clustered settlement is considered urban.
Whereas in say, Central and Southern Asia, sub Saharan Africa, in the past, it was really only cities.
In Sub Saharan Africa, you see slowly the towns also being considered urban.
One additional challenge when using national definitions is that they're not necessarily stable over time.
So if you look at the population share and nationally defined urban area and you see a big zigzag line, it means that they've changed the definition multiple times over time, that makes it really difficult to create a time series.
And here, because we apply this to a consistent time series, same method every time, we get a very consistent result.
Now, let's see.
This is a little animation, and I hope it'll work.
It's a Baku, and we're starting in 1975.
On the left, you can see these little grid cells, degree of urbanization level two.
And on the right hand side, you see the population in this square and how it evolves over time.
I hope if I click now that it'll start moving.
Try again.
Nope.
Can somebody on the computer and see if you can somehow there is a button on the presentation to allow it to move? Yes, there at the bottom.
You see the play button? Lower? Yes, there.
Drats.
I have good news for you.
We have over 1,000 of these little movies available online.
You can watch all of them.
Right now, unfortunately, I will have to skip them.
But here, for example, in Baku, you can see the population peaking around 2060 and then starting to decline on the right.
Here we've got Das Salam in Tanzania and you can see just radically rapid population growth.
If the movie would work, then you would actually see that urban center, that city expanding significantly over time.
So I wanted to just give you a very high level idea of how this data was created.
We started in the middle with data that was observed using data on population and data on buildings to create a population grid, and this is the global human settlement layer.
It's kind of the workhorse of this time series.
Then following suggestions from the UN Pop division, we found a relationship between how the population in national and urban area defined areas changed with the changes in the degree of urbanization.
So we backcast to 1950.
That's why we can start so far back in time.
We've only done that for population, not for land and built up area, and we don't have boundaries going back in time, but we have estimates of total population.
And then we have built a model to really take into account where more buildings are likely to show up, where more population is likely to live, and to allow that to change over time up to 2,100.
UN only published up to 21 50, but for the climate change community in particular, I thought the 2,100 data would also be useful.
And so we tweaked the model by World region to take into account where people tend to live in Africa or Asia or Europe.
And so, but the results, I can't check if we're right.
Can't fly to 2,100 and see if our projections were real, but they do produce very plausible results.
And so that's a reassuring thing.
We are trying to do a validation by starting earlier in time and to project the situation today, and we should publish those results later this year.
So I think this is very unique, and it's innovative.
In the past, not all cities were included in this database.
Now, we also allow cities to be born.
A town can grow into a city, and it happens during this period, but a city can also die.
It can shrink, so it's no longer 50,000 inhabitants, and then it becomes a town.
So you have cities entering and exiting from this dataset as time goes on.
We've published a boundary of every single city, so you don't have to wonder where these places are or where the city stops.
We show it for every single point in time.
We connect these boundaries across time, so you can allow you know you can follow them, see how they grow or shrink or shift.
And this is something quite new.
I mean, we've had city datasets before, but they assume that the number of cities is fixed, that their boundaries are fixed, and nothing changes across time.
And that really limits what you can do in terms of analysis, especially over long periods of time.
Now, think of a large city today, imagining analyzing it with the borders of 2000 or 1980 and assuming that nothing would change.
That doesn't work.
And so we've added other indicators.
I wanted to give you a couple let's a couple of examples.
But before that, let me just try and explain what we did because we had a bit of a challenge.
So we apply the degree of urbanization every year, and then you find 10,000 cities in one year and 11,000 cities in another year.
And then you hope that you can connect them.
But it doesn't always work because sometimes two cities become one or one city becomes two.
So what we've created is a very simple system where we don't allow cities that have been born or existed in 2025 to split or merge.
So it means in the past or in the future, we'll keep split cities together or we'll keep merge cities apart.
It's a bit technical, but it's just to allow you to understand that it's necessary to make these connections between these cities to allow for a meaningful analysis.
So here, again, the animation doesn't work, but you can see a rapid increase of the population in Cairo.
Here you see the situation in 1975, and if the animation worked, you would see Cairo spread, but you would also see those cities in the north grow, and in the end, they would touch but not merge.
So we kept them apart to allow you to continue to follow Banha or those other cities across time.
Whoo.
Look.
Thank you.
So this is what I wanted to show you here and see, all those cities now are contiguous and in principle, anything that's contiguous is part of the same city.
But here, we've kept them apart to make sure that you can also follow those cities over time, and you wouldn't get sudden jumps in those cities as one died and was absorbed by the other.
It's a technical little thing, but it helps us understand how cities grow in a smoother way.
And this is what we needed to do because especially large cities, typically consisted of many different parts in the past.
Jakarta is a very large city today, but if you go back to 1975, it actually consisted of more than ten individual cities.
And so we kept those together in the past, and you see these massive growth patterns here.
But for me, the interesting thing is, yes, in the past, say, 30 years, you see big increases in the population of these large cities.
But then for many of them, they flatten and most of them actually start to decline.
You know, if you look at the two Chinese cities, Shanghai, Guangzhou, rapid growth rates, then they start to plateau and they come back down.
Also Kolkota and Delhi, big growth rates flatten, and then a little bit later they start to calm down.
Also, Dhaka and Jakarta, you see that as population starts to shrink towards the end of the century, you see less increases.
But Dhaka is, you know, projected to become over 60 million, so really a massively large city.
Obviously, with projection time frames like this, there's a lot of uncertainty.
Nevertheless, I do think it's interesting to see the big contrast between the rapid increases in the past and then the slower growth in the future.
So what can we learn from 150 years of urbanization? Let's take a look.
So I mentioned that cities can be born or cities can die, right? So on the left hand side, and I hope you can read it, we show the number of cities by year of birth 1950-2025.
Now, I work for the European Union, and it struck me that of all the cities that we have today in Europe, 60% were already there in 1950.
So we haven't added a lot of cities, and most of the cities in Europe are actually around for at least 75 years, right? Whereas if you compare that, for example, to Africa, of all their cities today, only 6% was already a city in 1950, that's really a radical difference and half of their cities were only added in the last 25 years.
You see Europe, which from an urban point of view, a city demographic point of view is a very slow moving region, and then Africa being very, very dynamic, doubling its cities over the last 25 years.
Then if you look at the future, Africa, largely because a lot of natural growth, we'll see a massive increase in its number of cities over the next 75 years.
It may even these are additional cities, right? So if it says 200%, it means we triple the number of cities in Africa.
So in terms of experience, you know, there's going to be a lot of efforts needed to make sure that those cities are attractive, sustainable, resilient places, right? In Europe, actually, the number of cities is going to shrink.
Population is going to shrink, but actually a lot of cities aren't going to shrink into towns over the coming decades.
That's why it's so important to not just plan for growth, not just plan for expansion, but also acknowledge that in many parts of the world, we are increasingly going to have to plan for reductions of the number of cities and also the physical contraction of those cities.
Here we show cumulatively the population by city size and the top one is that class over 5 million and you can see that really growing substantially over time.
On the right hand side, you can see it as a share of population, and so only 10% of the population lived in cities of that size in 1950.
But today, that share has more than doubled.
But the key point that Cheryl made earlier remains more people live in small cities than in these mega cities.
These mega cities get all the media attention, but actually more city dwellers live in cities of less than a quarter million.
So we shouldn't overemphasize these mega cities.
They are known by name, but actually they're not representative of the experience of the vast majority of city dwellers.
Here you get the different population changes by world region.
You can see Africa, rapid increase in city population in all size groups.
In Asia, you can see a rapid increase, but then it starts to plateau and all those lines start to go flat.
In Latin America, you can even see it more.
There's clearly a hump and a bigger reduction.
Europe, we've peaked and we're slowly seeing a reduction of our city population.
Northern America still growing, but less quickly.
Oceania, you see some shifts there between the different sizes, but still quite rapid growth, but obviously from a much smaller base.
For us, we try to define cities as something very simple, a concentration of people in space.
So what does that mean? It means density, right? Higher density.
And we find those higher densities in cities, but it also differs by size.
The bigger the city is, the higher the population density is because people tend to live in taller buildings and also often in smaller dwellings.
And you can see that pattern across the regions, but you can also see big differences between the patterns, right? In Africa cities, even small cities are denser than the biggest cities in Northern America.
So those are kind of the two extremes, but typically the largest cities are much, much denser.
What for me is also interesting is to track the changes in density over time.
And there's all this worry about sprawling and expansion.
But actually, we see that over the past decades, city densities have either stayed flat or have increased.
So actually, we've added more people than space to the cities.
Now, these cities don't include the suburbs, so it's just the denser part of the city, right? We're working on agglomeration, so it might be a different story there.
But here, you can clearly see that city densities have either remained stable or gone up over time, and there is this clear distinction with the smallest cities being the least dense and the largest ones being the most dense.
Here you can see it by World region, and I kept the vertical axis identical.
And here, for example, you can very clearly see the difference between Asia on the top left with the largest cities of density over 8,000 inhabitants per square kilometer, and then Northern America where everything is around 4,000 or less, really big differences in scale there between the two extremes.
Latin American Caribbean still quite dense, but starting to shrink towards the end of the century, Europe, most of them shrinking except the large ones.
Large ones are also quite dense, 8,000 inhabitants per square kilometer.
Africa, which I don't show here, is similar to Asia in the sense that it has very, very high densities.
Now, here I want to address something that is, I think important for this community, and it's about these changes in population and changes in built up area, right? We have SDG 113.1 where we want to compare changes in built up compare it to changes in population.
And so what we show here is the evolution of built up area per capita by city size 1975-2075.
You can see, especially towards the future that the smaller the city, the higher its built up area per capita is, and you see a general increase of the built up barrier per capita.
So if I were very worried about land being covered by asphalt and by buildings, this would be my smoking gun.
Look at how bad cities are for the environment.
Now, hold that thought and look at this.
This is the same data, but I added rural areas and towns in semi dense areas and you can see a straight line going up, much more so than in cities.
If we're worried about land being covered by infrastructure, worried about fertile land being covered by buildings, We shouldn't be worrying about the cities.
We should be worrying about what happens outside the cities and not just just next to cities or in the suburbs, but also in the rural areas because that's where we're seeing a lot of construction, a lot of buildings, and increasing at a very high rate.
So I think it's an important perspective, and that's the benefit of having a classification that covers the entire territory.
We shouldn't think about cities in isolation.
We should think about them in relationship to the rest of the country.
So trying to wrap up and get ready for our panel.
I'm less diplomatic than the UN.
I do apologize.
But I said for international comparisons, national definitions aren't designed to deliver that.
That's not their fault.
It's not wrong.
None of those national definitions are wrong, but they are all different.
And they are sometimes very, very different, not just across space, but also across time.
If you want to come up with a robust comparable conclusion, you can't start from national definition.
And this is the first one that was endorsed by the UN and which was heavily consulted and really seems to work quite well.
Of course, I'm biased, but no, please take a look at yourself and see if you believe it.
We do see a growing share of global population in those cities, but both the growth absolute and relative is slowing down.
So the period of massive shifts of population into cities is already behind us.
We see more mega cities, but also the number of new mega cities is shrinking and more people live in small cities.
So that's much more representative of what people are experiencing.
City densities actually, both for the past and the projections for the futures are quite stable, so I'm expecting those to remain quite high.
Cities are expanding.
They are adding more built up, but the growth of built up per capita per resident is much higher outside cities.
So I don't think that cities are really the one we need to worry about if we want to conserve land.
So just a few more things, and then I'm going to close, We were very happy with this cooperation with the UN Pop division and a lot of fruitful exchanges and useful suggestions.
So this was one step.
We got the world urbanization prospects out of the way.
We're also planning to create a time series of urban agglomerations because I want to connect those cities and towns to their own suburbs, so we can see the expansion, not just at the city center or the town center, but also the surrounding suburbs.
And that one, we will create a time series starting in 1975, all the way in the future.
And I think that will be a useful complement to the analysis that we've already seen.
We also have a definition of a functional urban area.
In a nutshell, it's a city plus it's commuting zone.
That's a bit more difficult to apply over time because we'd have to guess where the roads are going to be in the future, which I haven't figured out how to do yet.
So we're just going to estimate functional urban areas for one point in time for 2025, and again, we'll publish those and especially for economic analysis, some housing markets, labor markets, specialization, economic growth.
Functional urban areas or metropolitan areas can be extremely useful.
And again, we'll put all this stuff out in the public domain for free.
And then finally, I also do a lot of rural analysis, and we wanted to create a more functional concept for rural areas.
So, in addition to the functional urban areas, we've created functional rural areas around market towns to allow, again, to understand where people sell their wares, go to school, go to healthcare, go to the bank, go shopping.
And again, we'll do that both for Europe and globally, and we'll publish these at the same time as the functional or shortly after the functional urban areas.
Okay, that was it for me.
Thank you for listening to me.
Sorry for being a bit long.
And then I suggest we switch to the panel discussion, and I'll pass the floor to Ruger.
But if there's a quick question, feel free.
Okay? Yes.
First of all, thank you for your presentation.
I'm from Slovakia.
My name is Yuri, and we work with local municipalities.
My question is about national standards and definitions.
Yes, on national level, I agree with you, they are designed for the different thing, but on local level, we have this data.
Municipalities have this data, at least in Europe, not the case for Africa.
For example, in Ethiopia, we don't have it.
But still, we can use the international definition with per square kilometer residential density and we can do that.
We can actually bypass national definitions, and we can just take it over on local level and then just rise it up and argument with earth observation.
Here, I see the challenge, but I don't see blind spots, so we definitely can do it.
Thank you.
Yeah, just a quick comment on that.
So I've shown you the grid degree of urbanization, but it also can be used to classify municipalities.
So if your majority of your municipality lives in a city, then it's a city, same for rural.
And so you can actually have a classification of each municipality by degree of urbanization.
And all the data that's available, geospatial data at grid level can also be aggregated up to the municipal data level and can be combined with any data that you have for municipality.
So this is something that standard practice in the European Union, but you need boundaries for the municipalities, which globally, I'm still struggling to find.
Okay.
I propose one last question and then we'll move on to the panel.
Hello.
I would like to ask you a question.
No.
One, two, three, sound check.
There is a projection that certain larger cities will simply merge with small cities and there are ongoing talks on the AI will replace certain jobs or professions if UN or other international organizations have vision how the agriculture will progress further and what will happen with employment in the future.
Spatial distribution of population and employment.
Hard to answer in the short term.
But I'll give you two thoughts.
I think in terms of agriculture, in many countries, we've already gone to a situation where agriculture requires very, very little manpower, and a lot of it has become larger in scale and more mechanized.
I do think that will continue to happen in large parts of the world.
So if I had to make a guess in 30 years, we'll see far fewer people needing to work in agriculture and also needing to work in the countryside.
When it comes to employment and the AI, I think it's very difficult to say what's going to happen, but in many ways, I think what AI cannot do is innovation and bringing things that are new.
And one of the key things that are required for innovation are exactly those face to face contacts, those dense social networks.
If anything, I actually think AI if it's going to have a major impact on the spatial distribution of employment and population, which is not given, I would argue it's probably going to help cities.
Also, after COVID, we saw a lot of speculation.
Oh, the city is going to die.
We've heard this many times before.
Cities are quite resilient and it's because we like them and it's because they give us things that we enjoy, not just culture, but also they allow us to be more connected and more creative and more innovative.
With that one, I really need to pass on to the panel, but thank you very much for your question.
Ortger over to you.
May I ask the panelists to come up here.
So we are very pleased to have with us Monica Kufa, Carl, again, and then also Dennis Maniki and Asu Tgwaya from different organizations.
Have they been introduced? Shall I introduce them or do you introduce yourself? Maybe you quickly introduce yourself.
Maybe start next to Loose.
Let's see if the micro works.
Good afternoon.
Thanks for being with us during lunch break.
My name is Monica Kufer, University of Tanta ITC.
I'm working with informality, urban data, hazards, et cetera.
Urbanization is an important base layer.
Okay.
Good afternoon.
Hi everyone.
My name is A Takeva.
I work at the State Statistical Committee of the Republic of Azerbaijan at the Sustainable Development Statistics Department.
Hello, good afternoon.
My name is Dennis Wonk.
I'm a Spatial data expert.
I work at UNABitat and I'm also lucky to have been part of the entire implementation process for the degree Organization since 2018.
Nice to see everyone.
Thank you all for being here.
If that's okay, I'll be asking you some questions trying to make it a little bit more interactive and I will, which is maybe it implite, but then nonetheless, I'll start with you, Dennis.
How was the degree of ariz been developed? Thank you, Roa.
I might want to start with a question to the audience because Louis and Gerry already say something.
Which year was the degree of Orbanization endorsed by the UNSco Commission? 19 1986, 1986.
I'll give you options.
2010, 2018, 2020? At least one person got 2020 right.
The history of the work on the implementation of deglobanization, is not very old, but the method itself, I think has been already operational in Europe for a while.
In 2016, when we were negotiating the work on the Narban agenda, Arbit three during to is when what we call the global voluntary commitment was made, which included different institutions, the European Commission, ILO, UN Arbit at the World Bank.
And the idea was to work together to assess whether it's possible to create a globally harmonized definition for cities and human settlements, and also rural areas for use for stats score comparisons.
The process that followed that is what is more important for at least for us from Mian habitat, because the idea for it was to be a very consultative process where you talk to countries, you talk to stats systems, talk to people responsible for planning and urban development, and you ask Is it possible to create a method that can help us to compare our data, or statistics using the same metrics? If this is possible, then what are the key considerations? 2018-1919, we led several regional discussions.
We talked to more than 85 countries across the developing regions mostly and we were presenting with our colleagues from the European Commission, the degree of organization is the potential method to do this comparison.
For me, the big The question is what we were asking them.
What do you think about this method? Are the results really relating to your local context? If you actually are not seeing the relation, what do you think can be brought in this process? Through this discussions is what led to the endorsement by the Stsco Commission in 2020 because countries actually realize the value of this method, how it was complementing the national processes.
The key ask as already has been said by Luis and Sherril is that this method was not supposed to replace the national definition, it's supposed to complement those processes and this is consistent with what the message you are trying to pass.
And countries also ask us to help them to actually implement this method using their own data because a lot of the work that Louis has shown here is implemented using data produced by the Joint Research Center, the European Commission, but countries actually ask us that they want to use their national data to implement this and they see how the results look like.
This is the process we've been implementing since 2021 as Vienabitat together with UNSD, UNICEF, and the UNAPA and the feedback has been really good.
Countries in many ways are actually owning the process as opposed to being a driven process externally by European Commission, UN abit the UN agencies.
Countries are actually not taking the leadership more to implement the process and take it forward.
This is just a short history.
And also to mention as part of this transition and the negotiation, there have been a few changes.
Luis did not mention them.
There have been a few changes to the core methodology that was originally proposed with very small adjustments to the Goober class level two.
To respond to what actually we are finding from implementation in countries and that actually adds value to the method itself because it's something that is negotiated the core development of the process.
Great.
Now that we know basically where the degree of rbanization is coming from and how it emerged, I think it would be interesting to hear a bit how it's been applied and I would be asking you if you could tell us how you've been implementing the degree of Urbanization in Azerbaijan and also have been using it for the SDGs.
Thank you for your question.
We implement the degree of Urbanization approach in contribution Human Habitat and European Commission.
It helps us to strengthen statistical ability, ECG monitoring and urban statistics.
It's very useful for us.
Of course, it's also hard for us Thank you for Denis.
Denis helped us a lot.
Thank you for this action.
And we can calculate two indicators SCG indicators, which this is the access transportation SG indicator 11.2 0.1 and 11.7 0.1 access to special areas.
It's very useful.
It's new approach for us, of course.
It also a and help us make the interagency collaboration.
Of course, we calculate these indicators with the helping the other institutions in our country.
For example, we calculate the access to transportation.
We use the Ministerial of a digital ministry and data.
We get the transport stops and then we integrate this data on the map.
Then we calculate using the sat globan and also we calculate the axis of the proportion of the population which access to the open space.
This is also very useful for us.
Every year report these indicators to the human habitat.
And it's very useful.
We hope we can continue this collaboration.
Thank you.
Thank you very much, Au, for this very interesting description of how you've been working with the degree of urbanization.
Now, somebody once said, I don't remember who it was that a model is never true and false, is either useful or useless.
And when it comes to the definition, it's always the same thing.
Definition by default is not perfect.
It's either bringing value to the table or not, and so it has strengths and weaknesses.
That's why I thought we can have Monica tell us a bit about the strengths and the weaknesses of this degree of rbnization.
Yes, it.
Let me start with some examples.
I've still memorized the time trying to make comparative statistics before we had this layout.
If you take, for example, simple questions like how much green spaces has a city and you take the administrative area and you take just two very iconic cities like London and Paris.
And you compare them because Paris, the administrative boundaries is very tiny and it's really basically the core city where London is huge and contains a lot of the non buildup area.
You get total garbage comparison, just to be very transparent.
If you use administrative statistics for comparison of open spaces, green area, The same, I'm working a lot with informal settlements.
If you compare city A and city B about how much percentage, how much area is covered by an informal settlement and you take different cities and they're not comparable.
You get total nonsense comparison statistics.
This was the layer.
I remember still an early meeting, I think in 2009, where I was very excited going there and we're talking the first time about how to make the global human settlement layer, how to map global settlement in a consistent way.
I think it's for researchers, it was working with urban analysis.
It was, wow, we now finally have a layer we can use as a base layer to say, if we do global urban analysis, that's the layer to go.
And there are many applications like in all kinds of SDG indicators.
I'm working also with hazards.
So how much percent of the city is exposed to flats, to urban heat, and these are all, let's say, we always have a boundary.
And this boundary, we need to make comparative statistics that are senseful.
Um, the bats, let's say, and that's something I've been debating a lot is coming with this 1 kilometer grid.
I don't know if you've seen the maps, and they don't make me entirely happy and very transparent.
Because if you do an urban analysis, this 1 kilometer grid, they're not really following nicely the urban morphology.
They are great and they're big blocks.
They are great for global analysis.
But if you do more like palling city level statistics and you show, for example, a very modern, I have to promote something.
I didn't say that I'm from the Netherlands.
There's a new cool planting standard for green spaces.
I don't know who has ever heard 3,300 in the room.
There are few people know, so you should see from your window at least three trees.
Your surrounding of your house should have around 30% green coverage and you should be within 300 meters to a park.
So all these kind of statistics, they have a boundary and you say, how much of the population, half this sort of conveniently half the street, 3,300.
Then if you make a boundary which is very blocky, which is not very nicely looking for platters, so I think we really need to move to, uh, like, um, smaller grid sizes.
Like my wish was 100, but I was told off that 100 is maybe two, too tiny, maybe something like 250 or something in between, because often also with the city I know very well there is alarm, you don't see the nice expansion areas which are following along the roads, which are basically huge buffer zone development along the road infrastructure.
That would be at the scale.
We have all the data now, we have the satellite images which are used as an input like sentinel images which are available ten meter resolution.
It's easily doable.
I think we have to go there.
I stop here, I have maybe some more lists but maybe in the second round.
Well, thanks a lot, Monica.
I now wanted to ask Luis, it's nice to have a definition, but it also somehow needs to be translated into concrete actions, policies basically.
Maybe you can say something about how this division can help with the SEDs, for example.
Maybe I also quickly react to Monica because the 100 meter version is also a wish list and my to do list.
I acknowledge that if you want a concrete more closely fitting boundary, 100 meter would work a lot better.
For the policy translation, we're really trying to make sure that all these blocky grid level concepts and data can be translated into information that mayors and local politicians can understand.
We take that information, those SDGs, access to public transport, access to green, built up area per capita, and we translate that into the municipal level so that a local policy can maker can say, okay, I'm living in a city of size X and all the other cities of this size in Europe are doing way better than I am.
What am I doing wrong? How can I fix it? Also, we're now preparing a State of European cities report, which we'll publish at the end of the year.
We've done some analysis using also that 330300 rule and we have a number of SDG indicators.
Really where I think we add the most value is that a mayor can say, and I want to compare my city to a city another city in the same country or in another country and understand where my city does better and where my city does worse.
When I do worse, I want to understand, okay, what have the cities that do well on this done differently? How can I fix that? Just the fact that you can say, okay, show me the best performing city in terms of access to public transport or which city in Europe gives me the best access to urban green? You can answer those questions and you can go to those places and you can talk to the mayor and say, Okay, what have you done and what should we change? For me, that being able to compare yourself across borders, cities of the same size using harmonized data and getting inspiration from local practices is how you turn it into policy.
Back to you, Ruger.
Well, thanks a lot Luis.
Also, we had previously mentioned the road rzation prospects and I was thinking, Cheryl, you could say something about the advantage of using the degree of rzation in these prospects.
Thank you.
Could I ask the IT service to put my presentation back on and I have one extra slide at the end to help illustrate this question.
We've said this many times through two presentations.
Yes, if you could go to the next slide, there it is.
Okay.
Sorry about that.
I wanted to show the comparison of China and India because that really is driving what we say about urbanization for the world as a whole.
And actually, I can kind of show it This isn't working, but when the comparisons for East Asia and Southern Asia, for China, it's very driven by the definition changing over time.
So from the 1950s through 70s or so, you can see that it tracks cities.
And then what looks like a huge burst of urbanization in China, from the national definition is really a, um, more of a change in the definition while India tracks the cities the whole way.
But then if you look at them at the cities, towns, and rural areas, the overall trends actually are not that different.
Just India starting from somewhat more rural.
Really, again, this international comparability comes through and changes really how we view urbanization in some of the world's biggest countries.
Thank you.
It's okay.
Sorry.
Thank you.
Thanks a lot, Cheryl.
We are running out of time.
I have a second run of questions for you but would ask you to really very quickly answer that question so we have at least a minimum for Q and I afterwards.
Maybe if you could try to basically answer in a minute or absolute maximum too, but a minute would be better.
Denise do you think this population projections and this built up or projection that we saw that they can be actually useful for national policy and city policies? Yeah.
The straight answer is yes, very useful for national urban policies, but also local development.
One of the biggest challenges we have in understanding the impact of policies is actually trying to relate them with what we've achieved with them.
Many of the policies we developed because the political processes, but they are not really responding to what is likely to happen.
With these projections, we can actually understand where growth is likely to happen, but then put in place structures to ensure that it's not happening in the wrong place that has adverse effects on development.
The other thing that I see critical Luis mentioned it, a lot of urban growth is happening in smaller towns and growing cities, and our policies are still largely based on issues to do with mega cities and big cities and unless we actually use this kind of data to understand this major transition in urbanization, we keep developing their own policies.
So in my view, yes, I find this information will be very, very useful and very critical to how we plan.
We are to we already considering application and applying some of these data for national urban policies, helping countries to know how to design specially reference national urban policies.
Thank you, Dennis, Monica, I mean, why are a why are changing boundaries so important when you're doing research and if you're looking at time series and projections? Changing boundaries are basically essential because if you think about a city looking at a static picture, and you want to create all kinds of information about environmental quality living conditions.
The change will basically tell you whether the newly built up areas are they better off or worse off.
In terms of living condition, livability, environmental condition, hazards.
It's a fundamental question.
We had many studies looking typically on the new built areas.
They are often very functionable, they are very car dependent, so all this information is so essential when we talk about sustainability challenges to understand the dynamics of the expansion of our cities.
I stop here, maybe out of time.
I could talk more about this.
Thanks, Monica.
Asu you had your presentation, I was wondering, is Aan going to produce more grid data and are you going to keep on using the degree of ization? Yes.
Thank you.
We want to continue use this methodology.
That's why after this session, we want a brief discussion with Dennis how we can apply this degree of urban methodology for showing the inadequate city legal settlements.
It's the major challenge for our countries that make the statistics of the illegal settlements.
Thank you.
Yeah, I mean, I just in the session of the global coalition before and this question of informal settlements is a huge problem and not only in Afghan Azerbaijan when you're looking at these issues.
I mean, that's a very good question, actually, but I don't think we have a good answer yet, but we're working on that.
Then Louis, you're always coming up with new stuff.
I mean, I guess you have some other new stuff that you're thinking about.
What will it be? I should stop making new spatial concepts, but they keep asking for more.
So basically, we've got the agglomeration, we've got the functional urban areas, but we really want to create these functional rural areas.
I really think it can help understand population change, access to services, and create units that are meaningful for people's daily lives, but also for policy making.
So understanding where is a good place to put a doctor, a hospital, a school, where to concentrate public and private services to make sure that you can service a wider community.
So me, I think with those, I should be done.
But it was something that we had proposed to the UN Statistical Commission earlier this year and they endorsed us developing those two new additional concepts.
I'm looking forward to sharing that and consulting that also with the partners that we have around the table here to make sure that it responds to both people's perceptions and lives and the policy needs.
T Luis was just talking about the UN.
The other UN publications that you're planning where you're going to use the degree of Oiation? So next year when we do the world population prospects to be released July 11th of next year, we plan to do breakdowns by age and sex of both according to the national definitions of urban and rural areas, I think also DG.
And then I'll just mention one other thing we're working on, which, as Luis had showed with the built up area or building up of rural areas, our team was also very intrigued by that.
So we're working on a policy brief Looking at how that build up in different areas is divided between residential and non residential.
We should have that coming out hopefully in a couple of months, the first look at that.
We would now have 8 minutes for question and answers.
If there is anybody in the audience who would like to ask anything to anybody on the panel here, Let me be an icebreaker.
My question is to all the panelists, local sustainable development goals indicators.
Why won't we account that for rural areas, for the smaller villages, we have access.
In Europe for sure.
But I don't know, probably you correct me, but it's not being accounted.
It's not carpeted with local SDDGs and why? Could you please explain to us what is the challenge, what blocks us from that.
Data is available.
Thank you.
Who would like to have the question? Luis? I can start, but I'm hoping Dennis will jump in there.
Okay.
I think there's a There's a challenge there in a way because yes, the data is available, but it's not necessarily something that you would evaluate with the same expectations.
For example, I used to live in Brussels and lived fairly close to the center and I had a metro station at the end of my street.
I felt like that was totally normal and that was a good thing to do.
I have.
Now I've moved to Italy, Northern Italy and I live at the end of a gravel road in the middle of a forest.
Obviously, I don't have a metro station next to my house.
I also think that's totally normal.
This anecdote is just to highlight that I think it is very useful to analyze the entire territory and not just large cities, but also small cities, towns, villages, rural areas.
But we have to change our expectation and we might also need to change what is important.
I Being close I don't live close to a park, but I live in the middle of the forest.
Do I have a problem? I think the important thing is when we analyze the entire territory that we change what we focus on and we change what we think should be our aspirations.
But with that philosophical remark, I'll pass the floor to Dennis maybe.
Okay.
Very good question, Lori.
The straight answer to you is there's no reason why we should not focus on rural areas.
It's only that the big focus has been on cities because this is also where we have the bigger problems.
Actually, we say if today you solve the issues you have in our cities and urban areas, regarding sustainability, we'll actually have solved almost 80 to 90% of the global challenges on sustainability because the cities are the one eating the villages, they are the one taking up all the sensitive areas.
But From a localization perspective, yes.
Within the CCG frameworks, we have indicators and specific issues that focus on rural areas and those are small villages because like you talk maybe the issues that Lewis says transport, I look at from a rural perspective, I look at issue like access to healthcare.
When I'm staying in that village, I want to have understanding on where can I get the nearest healthcare it could be a dispensary, it could be a hospital.
For that, the measure plan will be different.
For example, we're seeing how far can you access all road from your house to go maybe to a school or to go to a hospital.
These aspects are actually in the SDG.
There may be not just shown in this for the other applications, we also at least with the world bank applying on the issue of SDG 9.1 looks at the issues I'm mentioning about access to all weather roads because they are very important for rural markets and the implementation.
It's just maybe the scale of the data presentation here is more vibrant or more visible for cities, but at the village level, I think it is also something that is happening, maybe has not been presented here, but there are quite a number of things happening in that land.
Just to reflect a wonderful presentation which was presented, I think at the Wolf in Abu Dhabi, a joint work of your inhabitant and UNICEF looking into deprivation of African cities and comparing.
One of this really striking outcome was there that the secondary cities in terms of all kinds of health outcomes, school attendance, particularly the focus on children, was the worst of inhabitants living in secondary cities in Africa.
So people in rural areas were better off and in primary cities were better off.
And that's, I really like another reflection which reminds me a lot about nationality wise German.
It's a very old planning tradition in Germany which looks into, you could translate it as Evic equivalent living condition, which goes back to the central place theory of 1930 Germany.
Saying that rural areas, they will never have the same types of services, infrastructure, but there should be a minimum and there should be acceptable minimum of how long it takes from a rural rural settlement to reach a certain service and there are planning standards, and I think it's very interesting to look into this.
They will not be the same as cities, but they should have a minimum.
That's very interesting analysis with this new layer to be produced.
So, stopping.
Okay.
Do we have any other question? We have still time for one last question, I guess, if there is one.
While you're getting the mic, I can do a little publicity stunt, which is basically a use case for the degree of Urbanization.
We've been doing a lot of data on that in the OCD, having some events on that.
If you're interested, I'll put some business cards out to give you information about those events.
Question, please.
Yes.
I'm from Brazil Brazilian Stat Institute for Angiography.
I forgot the name now.
Yeah, I We are creating now the Guba for Brazil.
We have already finished.
Some data was very interesting because we have an increase in the human small increase, but the decrease in the density.
When we look for the data, the decrease looking for the census before was 3.3 persons perhaps, now it's 2.78.
And it was a decrease of 0.83% and the Gouba decrease of density was 0.85%.
You see a very good relation statistic with the DeGuba.
Now we are looking for the Gooble to put some other datas like social datas, economic datas, We still had a problem with the secrecy of the data.
You can't put it by one by 1 square kilometer, but we are looking to put them by type like towns, the difference.
We are beginning this study.
I would like to know if you already had some thinking of that, how can we put these other data, especially from census, but you had a monthly census for call housing census, a small one.
How are you thinking to use this data inside the group, is there any? So when we have data which is exhaustive and covers the entire population and it's not confidential, then obviously it's easy.
But it becomes more interesting and we can use more data, right? So Eurostat currently publishes more than 200 indicators by degree of urbanization, and they're all based on surveys.
So it could be the Labor Force survey, household budget surveys, the income and living conditions survey.
And there, indeed, they tend to produce it by aggregate.
So they don't produce it for each individual city, but they'll group cities together.
They won't publish the micro data, but they will publish it aggregated.
And really, the key thing there is sometimes you can you have to aggregate it necessarily at the national level, but you could see whether the privacy and confidentiality is still protected if you aggregate it by state, for example.
I think Brazil is a federal country, so you could do by state and by degree of urbanization, and then you could still publish quite a bit of results.
I think the key there is not to try and publish it at the grid cell level, but aggregate it either per city or by degree of urbanization and by state or by country to allow you to still monitor those changes over time in a reliable manner without sacrificing confidentiality.
That's it for me.
Interesting and of course, very nice Philippe to hear about Brazil.
We are supporting Brazil.
What I've seen also in some of the other countries and a good case is Bolivia.
They are actually going the opposite and saying, we want to do the more higher resolution, they make the grid level to be their base for all the data and that grids become permanent.
They say for all the data on planning on access to services, everything is analyzed at the grid level.
For example, in the last time they were presenting, they were showing like access to improved water at the grid level.
They're actually seeing the correlation between people who don't have access to improved water and sanitation and location of the river and they can actually start having a conversation at the planning level people very close to the rivers, for example, don't have access to improve sanitation and a lot of the air is into these rivers.
In my view, I still find that 1 kilometer is okay for privacy issues related to your data because you aggregate.
But even as you can start from that and build up into the small towns then to the major towns.
In Brazil, a lot of the data is also, I think you have a national grid, so I think it's a good complement to also consider at these two levels.
The provincial is is but also at a much higher resolution at the lower level.
Anybody else wants to add to this question? Well, then we're already 2 minutes over the time.
I would like to thank everybody.
I think that was a really great session.
I mean, I mean, first the speakers and the panelists, but also you in the audience and the questions.
Everybody deserves a really nice applause