Demographic factors of change in urbanisation processes : dynamics of national urban and rural population determining the degree of urbanisation.
Date: 2019-10-15
Institutions: Joint Research Centre
Subjects: demographic analysis, habitat, research report, rural population, urban population, urbanisation

Demographic Factors of Change in 
Urbanisation Processes 

Dynamics of national urban 
and rural population 
determining the Degree of 
Urbanisation 

Melchiorri Michele, Schiavina Marcello, Florczyk J. 
Aneta, Freire Sergio, Kemper Thomas, and 
Pesaresi Martino 

2019 

EUR 29861 

 
 
This publication is a Technical report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It 
aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a 
policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is 
responsible for the use that might be made of this publication. 

Contact information  
Name: Thomas Kemper 
Address: Via Fermi, 2749 21027 ISPRA (VA) - Italy - TP 267 
European Commission, Joint Research Centre (JRC), Ispra 
Email: Thomas.kemper@ec.europa.eu 
Tel.: +39 0332 785576 

JRC Science Hub 
https://ec.europa.eu/jrc 

JRC118028 

EUR 29861 

PDF 

ISBN 978-92-76-11306-5 

ISSN 1831-9424 

doi:10.2760/127903 

Luxembourg: Publications Office of the European Union, 2019 

© European Union, 2019 

Reuse is authorised provided the source is acknowledged. The reuse policy of European Commission documents is regulated by Decision 
2011/833/EU (OJ L 330, 14.12.2011, p. 39). 

For any use or reproduction of photos or other material that is not under the EU copyright, permission must be sought directly from the 
copyright holders. 

How to cite this report: Melchiorri M., Schiavina M., Florczyk J. A., Freire S., Kemper T., Pesaresi M., Demographic Factors of Change in 
Urbanisation Processes, EUR 29861, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-76-11306-5, 
doi:10.2760/127903, JRC118028 

All images © European Union 2019 

i 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Authors ..................................................................................................................................................................................................................................... 3 

Abstract ................................................................................................................................................................................................................................... 4 

1  Introduction ................................................................................................................................................................................................................... 5 

1.1  Overview.............................................................................................................................................................................................................. 5 

1.2  Rationale ............................................................................................................................................................................................................. 5 

2  Data description ......................................................................................................................................................................................................... 7 

2.1  Population .......................................................................................................................................................................................................... 7 

2.2  Settlement Model .......................................................................................................................................................................................... 7 

2.3  Spatial Units of Analysis ........................................................................................................................................................................... 7 

3  Methodology and Implementation ................................................................................................................................................................. 8 

3.1  Cases of national and urban population change ....................................................................................................................... 9 

3.1.1  Degree of urbanisation variations.................................................................................................................................... 10 

3.1.2  Net national population changes ...................................................................................................................................... 10 

3.1.3  Net urban population changes ........................................................................................................................................... 11 

3.2  Urban and rural population dynamics as proxies for degree of urbanisation variations ............................. 11 

3.2.1 

Rural driven de-urbanisation and demographic growth ..................................................................................... 12 

3.2.2 

Urban driven urbanisation and demographic growth .......................................................................................... 12 

3.2.3 

Urban polarised urbanisation and demographic growth ................................................................................... 12 

3.2.4 

Urban resilient urbanisation and demographic decline ...................................................................................... 12 

3.2.5 

Urban driven de-urbanisation and demographic decline ................................................................................... 13 

3.2.6 

Rural driven urbanisation and demographic decline ............................................................................................ 13 

3.2.7 

Rural resilient de-urbanisation and demographic decline ................................................................................ 13 

3.2.8 

Rural polarised de-urbanisation and demographic growth .............................................................................. 13 

3.2.9 

Stable or pure shift cases ..................................................................................................................................................... 13 

4  Application .................................................................................................................................................................................................................. 13 

4.1  Occurrence and geographical distribution of degree of urbanisation change cases....................................... 14 

4.2  Demographic changes across degree of urbanisation change cases ....................................................................... 16 

5  Conclusions................................................................................................................................................................................................................. 18 

References .......................................................................................................................................................................................................................... 19 

List of abbreviations and definitions ................................................................................................................................................................. 21 

Annex ..................................................................................................................................................................................................................................... 22 

List of figures ................................................................................................................................................................................................................... 24 

List of tables ..................................................................................................................................................................................................................... 25 

ii 

 
Authors 

Melchiorri Micheleb, Schiavina Marcelloa, Florczyk Anetaa J., Freire Sergioa, Pesaresi Martinoa, Thomas Kempera, 

a European Commission, Joint Research Centre (JRC), Ispra, Italy 
b Engineering S.p.a, Roma, Italy 

3 

 
Abstract 

Information, theory and policy response to the process of urbanisation are growing as scientific evidences and 
global  statistics  on  urban  population  refine.  The  Global  Human  Settlement  Layer  (GHSL)  provides  baseline 
data to determine the share of population living in urban areas using the GHSL Settlement Model Grid (GHS-
SMOD).  The  SMOD  ports  the  Degree  of  Urbanisation  (Dijkstra  and Poelman  2014)  in  the  GHSL environment 
and applies it globally. The degree of urbanisation refers to the share of the total population living in urban 
areas.  

The information on population distribution contained in the GHSL population layer (GHS-POP) and settlement 
typology  from  GHS-SMOD are  available  for  four epochs:  1975-1990-2000-2015.  GHS-POP  and  GHS-SMOD 
applied to urbanisation analysis are mainly used to estimate the shares of urban population per country in the 
different  epochs,  and  to  calculate  the  changes  in  the  degree  of  urbanisation  over  time.  This  information  is 
particularly  relevant  in  support  to  policymaking  as  it  quantifies  the  patterns  of  urbanisation,  rural-urban 
transitions and population shifts. The sole relative change of the degree of urbanisation per spatial unit, is not 
a comprehensive indication of the  demographic and spatial transformations taking place in that spatial unit 
(e.g. a country). The classification schema is also useful to develop and apply analytical methods and tools for 
better  understanding  of  current  and  future  urbanisation  trends  to  inform  development  and  cooperation 
actions.  

In  this  technical  report,  we  present  a  formalised  application  of  the  “Demographic  Factors  of  Change  in 
Urbanisation Processes” model to monitor variations in the degree of urbanisation at country level, analysing 
its demographic determinants (urban, rural and total population). The report proposes a formalised abstract 
classification  of  the  cases  of  degree  of  urbanisation  variations.  The  classification  is  then  applied  to  the 
countries in the Region “Europe” as per the  2018 Revision of World Urbanization Prospects published by the 
United Nations Department for Economic and Social Affairs.  

4 

1 

Introduction 

1.1  Overview 

The GHSL serves urbanisation analyses providing globally-consistent, multi-temporal, open and free data on 
the distribution of built-up areas (GHS-BUILT), population (GHS-POP) and human settlement typologies (GHS-
SMOD)  on  Earth.  The  Degree  of  Urbanisation  (Dijkstra  and  Poelman  2014)  is  an  important  and  well-
established  measure/indicator  adopted  by  Eurostat  and  used  for  producing  statistics  and  indicators 
disaggregated by settlement typology but whose application outside Europe was until recently limited by data 
suitability and availability.  

The  GHSL  geospatial  data,  due  to  its  global  coverage  and  characteristics,  allows  porting  the  Degree  of 
Urbanisation to the global domain by enabling the worldwide classification of different settlement typologies 
(High Density Clusters (Urban Centres), Moderate Density Clusters (Urban Clusters), and Low Density Grid Cells 
(Rural  Grid  Cells))  and  quantify  for  each  type  the  amount  of  built-up  areas,  population  and  surface.  The 
availability  of  this  baseline  information  is  used  to  support  the  European  Commission-led  voluntary 
commitment  to  develop  a  global,  people-based  definition  of  cities  and  settlements1.  Additional  applications 
include  the  testing  of  the  Degree  of  Urbanisation  at  global  level  with  the  production  of  Country 
Summaries2.The GHSL Data Package 2019 (Florczyk et al. 2019) contains improved GHS-BUILT, GHS-POP, and 
GHS-SMOD baseline data. Based on the 2019 GHSL release (GHS P2019), the overall Degree of Urbanisation 
for the world reaches 76.4% and has increased by 3% since 1975. This information could be supplemented 
by  characterising  the  determinants  of  the  degree  of  urbanisation  change  to  characterise  the  urbanisation 
process in different areas of interest. This is carried out by analysing the urban and rural population dynamics. 

This technical report presents different ways in which the net changes in total national population, total urban 
and  rural  population  at  national  level  determine  the  variation  in  the  degree  of  urbanisation  between  two 
epochs.  The  method  is  particularly  relevant  to  characterise  cases  where  there  is  variation  in  the  degree  of 
urbanisation, to benchmark the net demographic performance of urban areas vis-á-vis the one in rural areas, 
and the overall change of the total national population. The ultimate goal is to define which demographic and 
territorial processes take place in territories that undergo similar changes in the degree of urbanisation, and 
so  to  help  identifying  policy  response  options  with  the  production  of  baseline  data  underpinning  a  better 
understanding and documentation of conditions and development trends. 

1.2  Rationale 

The classical demographic definition of urbanisation is based on: 

Where the share of urban population at a given time (Ut) is determined by the ratio between the population of 
a given  spatial  unit accounted in  urban areas (Pu), over the total population of the spatial unit (PT – that is 
composed  by  urban  population  Pu,  and  rural  population  Pr).  This  formalisation  dates  back  to  the  traditional 
studies  on  urbanisation  by  Davis  (Davis,  1955).The  degree  of  urbanisation  of  the  same  spatial  unit  at  a 
subsequent year (Ut+1) can be calculated with the same formula and the respective  Pu and PT obtained from 
the baseline population data at the corresponding  t+1 year. Having quantified Ut and Ut+1 it is of interest to 
calculate the change of the degree of urbanisation of the spatial unit (e.g. a country) between the two epochs:  

The change in the degree of urbanisation of the spatial unit can be positive or negative, depending on the net 
changes of the urban population (Pu) or the total one (PT) whereas: 

1 

2  

https://ec.europa.eu/commission/commissioners/2014-2019/cretu/blog/presenting-voluntary-commitments-eu-meet-new-urban-

agendas-objectives_en 
http://ghsl.jrc.ec.europa.eu/CFS.php 

5 

 
 
                                           
From the above concepts,  Table 1 simplifies the different  conditions for  degree of  urbanisation changes. In 
principle, the degree of urbanisation grows in four circumstances, determined by the combination of total and 
urban  population variations (growth and decline), and declines in  other three circumstances. To  characterise 
further  the  changes  in  the  degree  of  urbanisation  it  is  necessary  to  disaggregate  PT  in  its  Pu,  and  Pr 
components. Table 1 demonstrates that change in the degree of urbanisation indicator alone is not capable to 
characterise the process of urbanisation taking place in a given  area of interest. For example, the degree of 
urbanisation in a situation of positive change of  PT and  Pu can increase or decline;  similarly, it can increase 
even with a net loss of urban population.  

Table 1. Synthetic table of combinations of national and urban population dynamics between two epochs in a positive or 
negative domain of degree of urbanisation change 

Degree of urbanisation 
change 

National population change 
between 
 t1 and tt+1 

Urban population 
change between  
t1 and tt+1 

Discriminant 

+ 

+ 

+ 

+ 

- 

- 

- 

+ 

+ 

- 

- 

- 

- 

+ 

Pu and Pr disaggregation 

Pu and Pr disaggregation 

Pu and Pr disaggregation 

Pu and Pr disaggregation 

+ 

+ 

+ 

- 

- 

- 

+ 

Figure 1. Change in the degree of urbanisation between 1975 and 2015 per country, binary 

6 

 
 
 
 
 
 
 
 
 
 
 
 
2  Data description 

Demographic  analyses  on  urbanisation  require  two  main  pieces  of  information,  one  to  quantify  population 
distribution, the other to classify settlements and respective population into urban versus rural classes. 

The Global Human Settlement Layer (GHSL) is produced at the European Commission – Joint Research Centre 
and it is supported by the Directorate-General for Regional and Urban Policy. GHSL maps population density 
(GHS-POP)  and  settlement  typologies  (GHS-SMOD),  for  the  epochs  1975-1990-2000-2015.  An  additional 
layer (GHS-BUILT) mapping presence and density of built-up areas for the corresponding years is available. All 
GHSL layers are consistently produced to grant comparisons across time and regions of the world. 

In  this  technical  report,  data  are  sourced  from  the  GHS-POP  and  GHS-SMOD  contained  in  the  GHSL  Data 
Package 2019 (Florczyk et al. 2019), epoch layers 1975 and 2015. National population statistics for the test 
application  of  the  methodology  were  extracted  from  GHSL  in  combination  with  the  Database  of  Global 
Administrative  Areas  v2.8  (GADM3).  Territories  in  the  Region  “Europe”  were  identified  from  the  World 
Population Prospects: The 2018 Revision, Classification of Countries by Major Area and Region of the World 
(United Nations, Department of Economic and Social Affairs, Population Division 2018). 

2.1  Population 

GHS-POP (Schiavina, Freire, and McManus 2019) is a spatial raster dataset that depicts  the distribution and 
density of population, expressed as the number of people per cell. Residential population estimates for target 
years  1975,  1990,  2000  and  2015  provided  by  CIESIN  GPWv4.10  were  disaggregated  from  census  or 
administrative units to grid cells, informed by the distribution and density of built-up as mapped in the GHS-
BUILT global layer per corresponding epoch (Freire et al. 2016, 2018). 

2.2  Settlement Model 

The GHS-SMOD  raster dataset (Pesaresi et al.  2019) delineates and  classifies human  settlement typologies 
using  a  logic  of  population  size,  population  and  built-up  area  densities  as  a  refinement  of  the  ‘degree  of 
urbanisation’ method as described by EUROSTAT4 using the GHS-POP and GHS-BUILT as input. 

The GHS-SMOD at level 2 classifies each 1 km grid cell into one of the classes with a two digit code (30 – 23 
– 22 – 21 – 13 – 12 – 11 – 10). Classes 30 – 23 – 22 – 21 together form the “urban domain”, while classes 
13 – 12 – 11 – 10 form the “rural domain”. 

2.3  Spatial Units of Analysis 

In this report the areas of interest are selected using country extents. To generate urban and rural population 
statistics  per  country  we  used  a  spatial  layer  to  delineate  territories,  the  Global  Administrative  Map  layer 
(GADM),  and  a  statistical  dataset  to  name  and  assign  countries  to  major  regions  of  the  world  (with  the 
country  classification  adopted  by  UNDESA  for  the  2018  Revision  of  the  World  Urbanization  Prospects)5. 
Although for the purpose of this report the analysis is conducted at national level, this methodology could be 
applied to every user-defined extents (e.g. NUTS2 or 3 levels, UN Major Areas, custom areas, etc.). 

3 http://gadm.org/ 
4 https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Degree_of_urbanisation 
5 VAT has been excluded from the analysis 

7 

                                           
3  Methodology and Implementation 

The workflow was implemented in four main phases. The first one consisted in the selection of the temporal 
span of the analysis (1975 to 2015), and areas of interest to be analysed (spatial units of analysis  -SUAs, 
here selected as country extents as delineated in the GADM layer and the WUP 2018 country classification). In 
the  second  step,  the  GHSL  Data  Package  2019  layers  (GHS-SMOD  and  GHS-POP)  were  injected  in  the  GIS 
environment to extract zonal statistics over the selected SUAs (Territories in the Major Region Europe). From 
these first two steps, it was possible to generate a geospatial layer and a multi-temporal statistical dataset 
containing for the year 1975 and 2015 the following information: total national population, urban and rural 
population per country, and the degree of urbanisation. In the third step, the Demographic Factors of Change 
in  Urbanisation  Processes  model  was  applied  and  the  different  cases  of  degree  of  urbanisation  variation 
codified and labelled. The fourth phase was implemented with statistical analytics to apply the model to the 
SUAs. The fourth phase delivered a comprehensive classification of countries, formalised in (Table 4 p.17). 

Figure 2. Methodology workflow 

8 

 
3.1  Cases of national and urban population change 

The degree of urbanisation of a country varies to the extent in which absolute changes in the urban and total 
national  population  manifest.  In  practice,  to  characterise  a  positive  or  negative  change  of  the  degree  of 
urbanisation  it  is necessary  to  analyse  the  absolute  changes in  the  components  of  the  ratio, namely  urban 
and  national  (urban  and  rural)  population.  This  methodology  is  provided  to  make  explicit  the  differences 
between the demographic patterns that determine variations in the degree of urbanisation. In fact, countries 
where the degree of urbanisation changes in the same way may undergo opposite demographic trajectories. 
Table 2 presents a classification of these patterns.  

Table 2. Classification of positive and negative degree of urbanisation changes between epochs, national population and 
urban / rural population variables 

Degree of 
urbanisation 
change 

National 
population 
change 
between 
 t1 and tt+1 

Urban 
population 
change 
between  
t1 and tt+1 

Rural 
population 
change 
between  
t1 and tt+1 

Case 

Classificatio
n 

Determinant 

Name 

- 

+ 

+ 

+ 

- 

+ 

- 

- 

+ 

+ 

+ 

- 

- 

- 

- 

+ 

+ 

+ 

+ 

+ 

- 

- 

- 

- 

+ 

+ 

- 

- 

- 

- 

+ 

+ 

1a 

1b 

2 

3 

4a 

4b 

5 

6 

Rural driven  
de-urbanisation  
and demographic 
growth 

Urban driven 
urbanisation  
and demographic 
growth 

Urban polarised 
urbanisation  
and growth 

Urban resilient 
decline 

Urban driven 
demographic 
decline 

Rural driven 
urbanisation  
and demographic 
decline 

Rural resilient  
de-urbanisation  
and demographic 
decline 

Rural polarised  
de-urbanisation  
and demographic 
growth 

The  demographic growth or decline labels refer to changes of PT, urbanisation or de-urbanisation refer to 
the degree of urbanisation change, respectively positive and negative, whereas a settlement typology (U or R): 
(i) drives the change, if the P (U or R)is greater than the other, in a national change like effect; (ii) polarises 

9 

 
 
 
 
 
 
 
 
 
 
 
 
the change, if its dynamic is concurrent to the national one, in a mix like effect; (iii) is resilient to the change, 
if its dynamic is the opposite of the national one, in a competitive like effect. 

3.1.1  Degree of urbanisation variations 

Net national and urban population changes determine degree of urbanisation variations. Figure 3 displays the 
sectors  of  the  Pr  versus  Pu  scatter  plot  where  countries  with  increasing  and  decreasing  degree  of 
urbanisation  are  plotted.  The  degree  of  urbanisation  variations  model  includes  eight  possible  combinations, 
four respectively for positive and negative change. Figure 3 also shows the ranges of slopes, as a function of 
Ut  (between  0  and  1  that  correspond  to  a  completely  rural  or  urban  population  respectively),  splitting  the 
sectors. 

Figure 3. Sectors of positive and negative change of degree of urbanisation 

3.1.2  Net national population changes 

To  analyse  variations  in  the  degree  of  urbanisation,  the  first  differentiation  concerns  a  positive  or negative 
demographic  balance  at  national  level.  In  the  domain  of  growing  national  population  there  are  four  cases, 
where two are related to growth of degree of urbanisation (1b and 2), and  two to decline (1a and 6). In the 
instance of declining national population (four cases), two are related to positive variations of the  degree of 
urbanisation  (3  and  4b)  and  two  to  decline  (4a  and  5).  Figure  4  shows  the  sectors  of  a Pr Pu  chart  of 
positive and negative change of national population. 

10 

 
Figure 4. Sectors of positive and negative change of total population 

3.1.3  Net urban population changes 

The net growth of urban population is not the only determinant of growth in degree of urbanisation of a SUA. 
From Table 2 it emerges that the net growth of urban population is responsible for the positive change of the 
degree of urbanisation in three cases (1b, 2, 3), while in one (1a) net urban population growth does not result 
in  positive  degree  of  urbanisation  change.  Net  decline  of  urban  population  is  mostly  associated  with  a 
negative variation of the degree of urbanisation (cases 4a, 5 and, 6), and only in case 4b net urban population 
decline results in a growth of the degree of urbanisation. In graphical terms, SUAs that account for a positive 
net change of urban population are plotted in quadrants I and II of the Pr  Pu scatter plot (Figure 5). 

3.2  Urban  and  rural  population  dynamics  as  proxies  for  degree  of  urbanisation 

variations 

Table  2  makes  explicit  that  the  degree  of  urbanisation  variation  manifests  as  a  combination  of  urban  and 
rural  population  dynamics.  These  can  take  place  in  an  instance  of  positive  or  negative  national  population 
balance. The set of degree of urbanisation variations can be fully explained only taking into consideration: a) 
the  national  demographic  trend;  b)  the  net  change  of  urban  population  (Pu);  c)  the  net  change  of  rural 
population  (Pr).  The  interplay  between  the  urban  and  rural  population  variables  and  their  aggregate  (PT) 
determine the result of the U.  

Figure  5  (a  combination  of  Figure  4  and  Figure  3)  synthetizes  the  eight  cases  of  degree  of  urbanisation 
change, disaggregating changes in rural and urban population. Areas plotted in shades of red correspond to 
an increase in the degree of urbanisation, the ones in blue to a decline. The sectors intertwine U, Pr and Pu. 
The  “urbanisation  slope”  m  of  the  line  defining  the  spaces  with  increasing  and  decreasing  degree  of 
urbanisation  (i.e.  Pu=mPr,  the  “urbanisation  line”)  plays  a  key  role  in  determining  the  classification  by 
splitting  cases  1  and  4  in  their  “a”  and  “b”  alternatives.  Such  urbanisation  slope  is  determined  by  the  ratio 
between the degree of urbanisation at time t and one minus the degree of urbanisation at time t: 

This section describes the factors determining variations in the degree of urbanisation. 

11 

 
 
Figure 5. Plot sectors by degree of urbanisation change classification 

3.2.1  Rural driven de-urbanisation and demographic growth 

Case name 1a. The rural driven de-urbanisation and demographic growth areas are subject to an increase of 
total population, with both urban and rural population growth, but a decline of the degree of urbanisation. In 
such  case  the  population  growth  is  more  substantial  in  rural  areas  with  an  absolute  change  in  the  urban 
population that is smaller than the rural one times the urbanisation slope (i.e. Pu<mPr). 

3.2.2  Urban driven urbanisation and demographic growth 

Case name 1b. The urban driven urbanisation and demographic growth characterises areas with an increase 
of total population, with both urban and rural population growth, and a simultaneous growth of the degree of 
urbanisation. In contrast to the previous case, the net change of urban population is greater than the one in 
rural areas times the urbanisation slope (i.e. Pu>mPr). 

3.2.3  Urban polarised urbanisation and demographic growth 

Case name 2. In the case of urban polarised urbanisation and demographic growth, both the total population 
and the  degree of  urbanisation grow. The  growth of  total population is determined by  an increase in  urban 
population  that  is  greater  than  the  loss  of  rural  population.  A  specific  case  of  case  urban  polarised 
urbanisation  and  demographic  growth  takes  place  when  the  loss  of  rural  population  is  null  (i.e. Pr=0);  this 
situation represents the pure urban growth. 

3.2.4  Urban resilient urbanisation and demographic decline 

Case  name  3.  A  pattern  of  urban  resilient  urbanisation  and  demographic  decline  shows  a  loss  of  total 
population, with a growth of urban population and an increase of the degree of urbanisation. This pattern is a 
sign of the advantages of urban areas that are resilient to population decline and actually experience a trend 
opposite  to  the  overall  one.  A  specific  case  of  urban  resilient  urbanisation  and  demographic  decline  takes 
place when the growth of urban population is null (i.e. Pu=0), this situation represents the pure rural decline. 

12 

 
3.2.5  Urban driven de-urbanisation and demographic decline 

Case  name  4a.  The  urban  driven  de-urbanisation  and  demographic  decline  areas  are  subject  to  a  declining 
total population, with both urban and rural shrinking populations, and a decline of the degree of urbanisation. 
In  such  case  the  population  decline  is  more  substantial  in  urban  areas  with  an  absolute  change  in  urban 
population smaller than the rural one times the urbanisation slope (i.e. Pu<mPr). 

3.2.6  Rural driven urbanisation and demographic decline 

Case name 4b. The rural driven urbanisation and demographic decline is a condition of total population loss, 
with both urban and rural populations shrinking, but facing growth in the degree of urbanisation. In this case, 
the population decline is more sizable in rural areas with an absolute change in urban population greater than 
the rural one times the urbanisation slope (i.e. Pu>mPr). 

3.2.7  Rural resilient de-urbanisation and demographic decline 

Case name 5. In the case of rural resilient de-urbanisation and demographic decline, both the total population 
and  the  degree  of  urbanisation  decline.  The  decline  in  total  population  is  determined  by  a  rural  population 
increase greater than the loss of urban population. In this case, rural areas play a competitive-like effect and 
manifest an opposite trend compared to the  total one. A specific case of rural resilient  de-urbanisation and 
demographic decline occurs when Pr=0, this case is of pure urban decline. 

3.2.8  Rural polarised de-urbanisation and demographic growth 

Case name 6. In this last case, classified as rural polarised de-urbanisation and demographic growth, the total 
population grows but the degree of urbanisation declines. However, an opposite dynamic takes place in rural 
and urban settlements, with  population growing in the  former and declining in the latter.  A  specific case of 
rural  polarised  de-urbanisation  and  demographic  growth  occurs  when  the  loss  of  urban  population  is  null 
(Pu=0), with this situation representing pure rural growth. 

3.2.9  Stable or pure shift cases 

In  cases  of  Pu  and  Pr  lying  on  the  urbanisation  line,  there  are  situations  of  stable  urbanisation  and 
demographic  growth  (when  both  are  positive)  or  stable  urbanisation  and  demographic  decline  respectively 
(when both are negative).  

When such cases happen in  situations of Ut = 1, the stable urbanisation and  demographic growth coincides 
with  the  pure  urban  growth,  generating  the  pure  urban  growth  and  stable  urbanisation;  also  the  stable 
urbanisation  and  demographic  decline  coincides  with  the  pure  urban  decline,  generating  the  pure  urban 
decline  with  stable  urbanisation.  In  situations  of  Ut  =  0,  the  stable  urbanisation  and  demographic  growth 
coincides with the pure rural growth, generating the pure rural growth with stable urbanisation; also the stable 
urbanisation  and  decline  coincides  with  the  pure  rural  decline,  generating  the  pure  rural  decline  with  stable 
urbanisation. 

The cases where Pu and Pr are equal in module but have opposite sign are of pure shift. Rural to urban shift 
occurs  when  Pu<0,  and  Pr>0;  the  urban  to  rural  shift  occurs  when  Pu>0,  and  Pr<0.  Although  the 
mathematical formulation requires a strict definition, pure shift cases could be estimated with a tolerance (i.e. 
as a percentage difference in module). 

4  Application 

The methodology described in the previous sections has been tested in the sample of 51 countries forming 
the Major Region Europe in the World Urbanization Prospect 2018. The interest is to apply the  Demographic 
Factors of Change in  Urbanisation Processes  model to characterise the  degree of urbanisation variations of 
countries  in  the  European  Region  between  1975  and  2015.  The  test  is  made  at  national  level  using  GHSL 
(GHS-POP  and  SMOD),  to  exploit  the  full  set  of  countries  in  the  Region,  but  the  disaggregation  can  be 
repeated for other spatial units for which data is available (e.g. at NUTS2 and NUTS3 levels). 

13 

4.1  Occurrence  and  geographical  distribution  of  degree  of  urbanisation  change 

cases 

Overall, urban and rural population in the selected sample of countries changes by about 45 million people in 
urban  areas  (∆Pu),  and  about  16  in  rural  areas  (∆Pr).  In  32  countries  the  degree  of  urbanisation  increases 
between 1975 and 2015 (cases 1b, 2, and 4b), and in the other 19 it declines (1a, 4a, 5, and 6). The majority 
of territories (16 occurrences) where the degree of urbanisation increases suffer an urban driven urbanisation 
and demographic growth (1b) situation (examples include Belgium, Germany, Denmark, Spain, the Netherlands 
and the United Kingdom). Thirteen other countries account for urban polarised urbanisation and demographic 
growth (2) –including Austria, Italy and Portugal. Other 3 countries (Croatia, Romania and Serbia) develop with 
a  rural  driven  urbanisation  and  demographic  decline  pattern  (4b)  (territories  are  listed  in  Table  3).  Croatia, 
Romania  and  Serbia  are  the  only  countries  analysed  where  the  degree  of  urbanisation  increases  in 
conjunction  with  a  net  demographic  loss  (∆Pt<0).  Such  loss  exceeds  250  thousand,  2  million  and  720 
thousand people respectively, and in Croatia and Serbia the majority of population is lost in rural areas while 
rural  and  urban  population  loss  is  almost  equal  in  Romania.  In  the  situations  of  declining  degree  of 
urbanisation, the majority (8 cases) follows the rural driven de-urbanisation and demographic growth process 
(1a) –including France, Poland and Russia. The other occurrences are evenly distributed across the remaining 
change cases (four occurrences in cases 5 and 6; three occurrences in case 4a). 

Figure 6 Frequency distribution of cases of degree of urbanisation variation in Europe between 1975 and 2015 

Table 3 Classification of territories in Europe per case of degree of urbanisation change 

Case 
1a 

1b 

2 

4a 

4b 

5 

6 

Name 
Rural driven de-urbanisation and 
demographic growth 
Urban driven urbanisation and 
demographic growth 

Urban polarised urbanisation and 
demographic growth 
Urban driven de-urbanisation 
and demographic decline 
Rural driven urbanisation and 
demographic decline 
Rural resilient de-urbanisation 
and demographic decline 
Rural polarised de-urbanisation 
and demographic growth 

Count 

Territories (ISO A3) 

8  AND, IRL, FRA, MNE,POL, RUS, 

SMR, SVK 

16  ALA, BEL, DEU, DNK, ESP, FIN, 

GBR, GRC, IMN, LUX, MKD, NLD, 
NOR, SVN, SWE, XKO 

13  ALB, AUT, BLR, CHE, GGY, GIB, 

ISL, ITA, JEY, LIE, MCO, MLT, PRT 

3  BGR, HUN, UKR 

3  HRV, ROU, SRB 

4  BIH, EST, LTU, LVA 

4  CZE, FRO, MDA, SJM 

14 

 
Figure 7 Classification map of the region Europe according to the Demographic Factors of Change in National Degrees of 
Urbanisation model 

The degree of urbanisation change cases seem to have  specific geographical distribution (Figure 7). In most 
countries in Eastern Europe the degree of urbanisation declines, most often due to urban driven urbanisation 
and  demographic  decline  pattern,  whereas  both  urban  and  rural  population  shrink.  On  the  contrary,  urban 
driven urbanisation and demographic growth is widespread across Central and Western Europe implying net 
population  growth  in  both  urban  and  rural  areas  (excluding  France  and  Ireland,  showing  a  rural  driven  de-
urbanisation and demographic growth pattern). 

15 

 
4.2  Demographic changes across degree of urbanisation change cases  

Figure 8 plots the territorial patterns of Pr and Pu (from which also U can be derived) presented above. In 
comparative terms, the dynamics of urban and national population and of degree of urbanisation variations 
are rather different across the analysed area of interest.  

Figure 8. Cases of degree of urbanisation variation by changes of national and urban population in Europe 1975-2015 
(right); and Countries in the Major Area Europe per case of degree of urbanisation change 

Figure 9. Average of national and urban population and degree of urbanisation per case of change 

16 

 
 
Figure  9  shows  average  changes  in  total,  urban  and  rural  population,  and  the  related  average  degree  of 
urbanisation variation per class. The chart is built summarising the national-level changes of the countries in 
the class. Although the model is not formulated on the basis of relative changes of Pr, Pu and the degree of 
urbanisation, ex-post classification highlights that the intensities of change varies. In case 1b and case 2, both 
of positive U, the latter shows on average a higher relative change of the degree of urbanisation. This is due 
to  the  combination  of  positive  demographic  change  in  urban  areas  and  net  loss  in  rural  ones.  Table  4 
summarises for the countries of the Major Region Europe, the observed absolute changes of total population, 
urban and rural components, the degree of urbanisation at t (1975) and t+1 (2015), and the case of degree 
of urbanisation variation as per the classification with the presented model. 

Table 4. Dataset of the observed variables for countries in the European Major Region, 1975-2015 (P in thousands) 

ISO A3 
ALA 
ALB 
AND 
AUT 
BEL 
BGR 
BIH 
BLR 
CHE 
CZE 
DEU 
DNK 
ESP 
EST 
FIN 
FRA 
FRO 
GBR 
GGY 
GIB 
GRC 
HRV 
HUN 
IMN 
IRL 
ISL 
ITA 
JEY 
LIE 
LTU 
LUX 
LVA 
MCO 
MDA 
MKD 
MLT 
MNE 
NLD 
NOR 
POL 
PRT 
ROU 
RUS 
SJM 
SMR 
SRB 
SVK 
SVN 
SWE 
UKR 
XKO 

Pt 

             8.63      
         485.73      
           39.71      
         919.95      
       1,533.85      
-      1,561.49      
-        156.94      
         128.03      
       1,938.21      
         487.52      
       2,028.69      
         607.83      
     10,211.84      
-        112.49      
         785.13      
     11,382.88      
             7.67      
       8,534.65      
             4.86      
             6.22      
       1,925.17      
-        251.62      
-        684.98      
           26.84      
       1,508.90      
         111.47      
       4,535.13      
           32.41      
           13.82      
-        420.57      
         211.20      
-        485.85      
           12.42      
         224.33      
         275.25      
         111.07      
           71.95      
       3,305.43      
       1,203.08      
       4,443.61      
       1,163.50      
-      2,160.38      
       9,666.33      
             1.58      
           10.51      
-        720.96      
         679.76      
         318.59      
       1,585.34      
-      3,935.61      
       1,064.01      

Pu 

            4.60      
        545.44      
          24.81      
     1,040.71      
     1,406.01      
-     1,191.84  
-       301.08      
        205.07      
     2,009.27      
-           7.35      
     1,837.88      
        542.74      
     9,133.11      
-       547.11      
        599.79      
     5,360.50      
               0        
     8,146.69      
            5.21      
            6.22      
     1,479.91      
-         35.64      
-       678.19      
          22.52      
        762.88      
        124.53      
     5,932.07      
          34.34      
          15.88      
-       522.45      
        167.04      
-       523.13      
          12.42      
-           4.73      
        266.97      
        114.49      
          48.14      
     2,857.22      
        922.11      
     2,095.25      
     1,363.69      
-    1,084.32      
     3,464.45      
               0        
            8.57      
-       143.03      
        180.73      
        247.34      
     1,319.21      
-    3,144.97      
        782.50      

Pr 

            4.03      
-         59.72      
          14.90      
-       120.76      
        127.85      
-       369.65  
        144.14      
-         77.04      
-         71.06      
        494.87      
        190.82      
          65.09      
     1,078.73      
        434.63      
        185.35      
     6,022.39      
            7.67      
        387.96      
-           0.34      
               0        
        445.25      
-       215.97      
-           6.79      
            4.31      
        746.02      
-         13.07      
-    1,396.94      
-           1.93      
-           2.06      
        101.88      
          44.15      
          37.29      
                0       
        229.06      
            8.28      
-           3.42      
          23.81      
        448.21      
        280.97      
     2,348.36      
-       200.18      
-    1,076.05      
     6,201.88      
            1.58      
            1.95      
-       577.93      
        499.04      
          71.25      
        266.13      
-       790.63      
        281.50      

17 

Ut 
40% 
56% 
67% 
51% 
75% 
 
74% 
69% 
67% 
62% 
69% 
59% 
74% 
96% 
56% 
64% 
0% 
83% 
89% 
100% 
66% 
55% 
65% 
62% 
55% 
52% 
70% 
78% 
72% 
75% 
56% 
73% 
100% 
62% 
69% 
91% 
70% 
81% 
48% 
62% 
61% 
54% 
77% 
0% 
83% 
60% 
56% 
45% 
60% 
70% 
55% 

Ut+1 
44% 
66% 
64% 
58% 
78% 
56% 
69% 
70% 
76% 
59% 
70% 
62% 
77% 
63% 
59% 
61% 
0% 
85% 
91% 
100% 
68% 
57% 
62% 
69% 
54% 
72% 
74% 
87% 
88% 
67% 
65% 
65% 
100% 
58% 
72% 
95% 
69% 
82% 
54% 
60% 
67% 
55% 
74% 
0% 
82% 
64% 
52% 
50% 
64% 
69% 
65% 

case 
1b 
2 
1a 
2 
1b 
4a 
5 
2 
2 
6 
1b 
1b 
1b 
5 
1b 
1a 
6 
1b 
2 
2 
1b 
4b 
4a 
1b 
1a 
2 
2 
2 
2 
5 
1b 
5 
2 
6 
1b 
2 
1a 
1b 
1b 
1a 
2 
4b 
1a 
6 
1a 
4b 
1a 
1b 
1b 
4a 
1b 

5  Conclusions 

With  the  global  debate  increasingly  bound  to  urbanisation  figures  and  analysis,  it  is  key  to  inform 
policymaking  on  the  basis  of  reliable, accurate, updated  and consistent  data.  To  support  the  endeavours of 
the  European  Commission  and  its  institutional  partners  (OECD,  the  World  Bank  and  FAO)  committed  to 
developing a people-based global definition of cities and settlements, this technical report has introduced a 
methodology  to  analyse  the  changes  in  the  degree  of  urbanisation  considering  demographic  factors:  urban 
and rural population, and total national population. 

The mathematical formulation of the methodology  demonstrates that the degree of  urbanisation variations 
should  be  analysed  taking  into  consideration  the  dynamics  of  its  components,  namely  urban,  national  and 
rural population. In the abstraction of the change cases, it was highlighted that equal variations of the degree 
of  urbanisation  may  be  due  to  opposite  demographic  trends.  Therefore,  in  order  to  consider  the  degree  of 
urbanisation  as  indicator,  it  is  necessary  to  characterise  it  and  be  aware  of  the  different  drivers  of  its 
variation.  

The abstract classification proposed in Table 2 (Classification of positive and negative degree of urbanisation 
changes between epochs, national population and urban / rural population variables) has been tested in the 
51  countries  forming  region  Europe  as  per  the  classification  of  the  UNDESA  World  Urbanization  Prospects 
2018 Revision (the institutional and scientific reference in the domain). The application demonstrated that it is 
needed  to  differentiate  and  classify  national  cases  of  degree  of  urbanisation  variation  to  capture  actual 
demographic  dynamics  (absolute  changes)  and  shifts  (urban  rural  transitions,  and  vice  versa),  as  these 
dynamics require substantially different policy responses especially in the framework of the Future of Cities 
(European Commission Joint Research Centre 2019). 

The  presented methodology is capable  of supporting policy design and policy implementation monitoring at 
European level and at international one. In particular, the model could be applied to classify smaller territorial 
units  (i.e.  NUTS  or  regions).  In  particular  it  could  help  to  better  identify  the  territorial  and  demographic 
dynamics  determining  urbanisation  processes.  Such  information  is of  particular importance  to  conceive  and 
analyse  policies  addressing  the  specific  requirements  of  the  different  processes.  In  a  broader  context,  the 
classification  schema  is  also  useful  as  sampling  attribute  to  group  and  identify  specific  economic,  social, 
development and environmental indicators. For example the classification can be deployed to characterise the 
risk assessment  for  humanitarian  crises  and  disasters index  of  JRC  (INFORM)  (Marin  Ferrer,  Vernaccini, and 
Poljansek  2017),  and  to  inform  development  and  cooperation  actions,  that  could  underpin  the  assessment 
and  the  focus  of  disbursement  among  beneficiaries  in  DEVCO  intervention  (European  Commission  , 
Directorate-General for International Cooperation and Development 2018). 

18 

References 

Davis, Kingsley. 1955. ‘The Origin and Growth of Urbanization in the World’. American Journal of Sociology 60 

(5): 429–37. https://doi.org/10.1086/221602. 

Dijkstra, Lewis, and Hugo Poelman. 2014. ‘A Harmonised Definition of Cities and Rural Areas: The New Degree 

of Urbanisation’. Publications Office of the European Union. 

European  Commission  ,  Directorate-General  for  International  Cooperation  and  Development.  2018. 
Development and Cooperation Annual Report 2018 On the Implementation of the European Union’s 
Instruments for Financing External Actions in 2017. 2018th ed. Publications Office of the European 
Union. 10.2841/0373. 

European  Commission  Joint  Research  Centre.  2019.  The  Future  of  Cities:  Opportunities,  Challenges  and  the 

Way Forward. Luxembourg: Publications Office of the European Union. 10.2760/375209. 

Florczyk, A. J., C. Corbane, D. Ehrlich, S. Freire, T. Kemper, L. Maffenini, M. Melchiorri, et al. 2019. GHSL Data 

Package 2019. JRC117104. Publications Office of the European Union. 10.2760/729240. 

Freire, Sergio, Erin Doxsey-Whitfield, Kytt MacManus, Jane Mills, and Martino Pesaresi. 2016. ‘Development of 
New Open and Free Multi-Temporal Global Population Grids at 250 m Resolution’. In Proc. of the 19th 
AGILE Conference on Geographic Information Science. Vol. 250. Helsinki,  Finland. 

Freire, Sergio, Marcello Schiavina, Aneta J Florczyk, Kytt MacManus, Martino Pesaresi, Christina Corbane, Olena 
Borkovska, et al. 2018. ‘Enhanced Data and Methods for Improving Open and Free Global Population 
Grids: Putting “Leaving No One behind”into Practice’. International Journal of Digital Earth, 1–17. 

Marin  Ferrer,  M.,  Luca  Vernaccini,  and  Karmen  Poljansek.  2017.  ‘Index  for  Risk  Management  -  INFORM. 
Concept  and  Methodology  Version  2017’.  EUR  -  Scientific  and  Technical  Research  Reports. 
EN. 
Publications 
http://publications.jrc.ec.europa.eu/repository/handle/111111111/38453. 

JRC106949. 

European 

28655 

Union. 

Office 

EUR 

the 

of 

Pesaresi, M., A. J. Florczyk, M. Schiavina, M. Melchiorri, and L. Maffenini.  2019. ‘GHS Settlement Grid, Updated 
and  Refined  REGIO  Model  2014  in  Application  to  GHS-BUILT  R2018A  and  GHS-POP  R2019A, 
Multitemporal  (1975-1990-2000-2015),  R2019A’.  European  Commission,  Joint  Research  Centre 
(JRC). 10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218. 

Schiavina, M., S. Freire, and K. McManus. 2019. ‘GHS Population Grid Multitemporal (1975-1990-2000-2015), 
R2019A.’  European  Commission,  Joint  Research  Centre  (JRC).  10.2905/0C6B9751-  A71F-4062-
830B-43C9F432370F. 

United  Nations,  Department  of  Economic  and  Social  Affairs,  Population  Division.  2018.  ‘World  Urbanization 

Prospects: The 2018 Revision’. 

19 

 
List of abbreviations and definitions 

GHS-BUILT 

Global Human Settlement Layer Built-up grid 

GHS-POP   

Global Human Settlement Layer Population grid 

GHS-SMOD 

Global Human Settlement Layer Settlement Model grid 

21 

Annex 

Table 5 Colour coding  

Classification 

Name 

RGB 

1a 

1b 

2 

3 

4a 

4b 

5 

6 

Rural driven de-urbanisation and demographic growth 

176, 181, 201 

Urban driven urbanisation and demographic growth 

223, 172, 171 

Urban polarised urbanisation and demographic growth 

245, 176, 175 

Urban resilient urbanisation and demographic decline 

249, 208, 209 

Urban driven de-urbanisation and demographic decline 

233, 245, 253 

Rural driven urbanisation and demographic decline 

247, 234, 238 

Rural resilient de-urbanisation and demographic decline 

208, 225, 241 

Rural polarised de-urbanisation and demographic growth  164, 221, 247 

Table 6 Demographic Factors of Change in National Degrees of Urbanisation model nomenclatures and abbreviations, 
specific cases are reported in brackets 

Classification 

Name 

Abbreviation 

1a 

1b 

2 

3 

4a 

4b 

5 

6 

Rural driven de-urbanisation and demographic growth 

Urban driven urbanisation and demographic growth 

Urban polarised urbanisation and demographic growth 

(Pure urban growth) 

Urban resilient urbanisation and demographic decline 

(Pure rural decline) 

Urban driven de-urbanisation and demographic decline 

Rural driven urbanisation and demographic decline 

Rural resilient de-urbanisation and demographic decline 

(pure urban decline) 

Rural polarised de-urbanisation and demographic growth 

(Pure rural growth) 

RDG 

UDG 

UPG 

(PUG) 

URD 

(PRD) 

UDD 

RDD 

RRD 

(PUD) 

RPG 

(PRG) 

22 

 
 
Table 7 Demographic Factors of Change in National Degrees of Urbanisation model nomenclatures and abbreviations of 
special cases 

Name 

Abbreviation 

Rural to urban shift 

Urban to rural shift 

R2U 

U2R 

Stable urbanisation with demographic growth 

SUG 

Stable urbanisation with demographic decline 

SUD 

Disclaimer 
The  European  Commission  Joint  Research  Centre  has  taken  considerable  care  in  preparing  the  information 
presented in this report. The designations employed and the presentation of material on the map do not imply 
the expression of any opinion whatsoever on the part of  the European Union concerning the legal status of 
any country, territory or area or of its authorities, or concerning the delimitation of its frontiers or boundaries 
that if shown on the maps are only indicative. 
The  European  Commission  Joint  Research  Centre  produced  this  dataset  to  improve  public  access  to 
information.  However,  the  producer  accepts  no  responsibility  or  liability  whatsoever  with  regard  to  the 
information on this dataset. This information is of a general nature only and is not intended to address the 
specific  circumstances  of  any  particular  individual  or  entity;  it  is  not  necessarily  comprehensive,  complete, 
accurate or up-to-date; and it is sometimes  based on external datasets over which the Commission has no 
control and for which it assumes no responsibility. 

23 

List of figures 

Figure 1. Change in the degree of urbanisation between 1975 and 2015 per country, binary .....................................6 

Figure 2. Methodology workflow .............................................................................................................................................................................8 

Figure 3. Sectors of positive and negative change of degree of urbanisation ...................................................................... 10 

Figure 4. Sectors of positive and negative change of total population ..................................................................................... 11 

Figure 5. Plot sectors by degree of urbanisation change classification..................................................................................... 12 

Figure 6 Frequency distribution of cases of degree of urbanisation variation in Europe between 1975 and 
2015 ........................................................................................................................................................................................................................................ 14 

Figure 7 Classification map of the region Europe according to the Demographic Factors of Change in National 
Degrees of Urbanisation model.............................................................................................................................................................................. 15 

Figure 8. Cases of degree of urbanisation variation by changes of national and urban population in Europe 
1975-2015 (right); and Countries in the Major Area Europe per case of degree of urbanisation change ............ 16 

Figure 9. Average of national and urban population and degree of urbanisation per case of change ................. 16 

24 

List of tables 

Table 1. Synthetic table of combinations of national and urban population dynamics between two epochs in a 
positive or negative domain of degree of urbanisation change ...........................................................................................................6 

Table 2. Classification of positive and negative degree of urbanisation changes between epochs, national 
population and urban / rural population variables .........................................................................................................................................9 

Table 3 Classification of territories in Europe per case of degree of urbanisation change ........................................... 14 

Table 4. Dataset of the observed variables for countries in the European Major Region, 1975-2015 (P in 
thousands) ........................................................................................................................................................................................................................... 17 

Table 5 Colour coding ................................................................................................................................................................................................. 22 

Table 6 Demographic Factors of Change in National Degrees of Urbanisation model nomenclatures and 
abbreviations, specific cases are reported in brackets ........................................................................................................................... 22 

Table 7 Demographic Factors of Change in National Degrees of Urbanisation model nomenclatures and 
abbreviations of special cases ................................................................................................................................................................................ 23 

25 

 
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K
J
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N
A
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2
9
8
6
1
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27 

doi:10.2760/127903 

ISBN 978-92-76-11306-5