The average for 2021 based on 27 countries was 187 people per square km. The highest value was in Malta: 1620 people per square km and the lowest value was in Finland: 18 people per square km. The indicator is available from 1961 to 2021. Below is a chart for all countries where data are available.

In 2022, the population density in the European Union remained nearly unchanged at around 112.05 inhabitants per square kilometer. Nevertheless, 2022 still represents a peak in the population density in the European Union. Population density is calculated by dividing the total population by the total land area, to show the average number of people living there per square kilometer of land.

Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second smallest country, with an area of about two square kilometers, and its population only numbers around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer stands at about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase as well. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

Denmark has, by far, the highest population density of the Nordic countries. This is related to the fact that it is the smallest Nordic country in terms of land area. Meanwhile, Iceland, which has the smallest population of the five countries, also has the lowest population density. As the total population increased in all five countries over the past decade, the population density also increased.

Chart and table of Europe Central Asia Ibrd Only Countries population density from 1950 to 2025. United Nations projections are also included through the year 2100.

Key figures on the population of the Netherlands.

The following information is available: - Population by sex; - Population by marital status; - Population by age (groups); - Population by origin; - Private households; - Persons in institutional households; - Population growth; - Population density.

CBS is in transition towards a new classification of the population by origin. Greater emphasis is now placed on where a person was born, aside from where that person’s parents were born. The term ‘migration background’ is no longer used in this regard. The main categories western/non-western are being replaced by categories based on continents and a few countries that share a specific migration history with the Netherlands. The new classification is being implemented gradually in tables and publications on population by origin.

Data available from: 1950 Figures on population by origin are only available from 2022 at this moment. The periods 1996 through 2021 will be added to the table at a later time.

Status of the figures: All the figures are final.

Changes as of 17 July 2024: Final figures with regard to population growth for 2023 and final figures of the population on 1 January 2024 have been added.

Changes as of 26 April 2023: None, this is a new table. This table succeeds the table Population; key figures; 1950-2022. See section 3. The following changes have been implemented compared to the discontinued table: - The topic folder 'Population by migration background' has been replaced by 'Population by origin'; - The underlying topic folders regarding 'first and second generation migration background' have been replaced by 'Born in the Netherlands' and 'Born abroad'; - The origin countries Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan, Turkmenistan and Turkey have been assigned to the continent of Asia (previously Europe).

When will new figures be published? In the last quarter of 2025 final figures with regard to population growth for 2024 and final figures of the population on 1 January 2025 will be added.

In 2023, the population of the United Kingdom was around 68.3 million, with approximately 34.5 million women and 33.1 million men. Since 1953, the male population of the UK has grown by around 9.1 million, while the female population has increased by approximately 8.5 million. Throughout this provided time period, the female population of the UK has consistently outnumbered the male population. UK population one of the largest in Europe As of 2022, the population of the United Kingdom was the largest it has ever been, and with growth expected to continue, the forecasted population of the United Kingdom is expected to reach over 70 million by the 2030s. Despite the relatively small size of its territory, the UK has one of the largest populations among European countries, slightly larger than France but smaller than Russia and Germany. As of 2022, the population density of the UK was approximately 279 people per square kilometer, with London by far the most densely populated area, and Scotland the most sparsely populated. Dominance of London As seen in the data regarding population density, the population of the United Kingdom is not evenly distributed across the country. Within England, London has a population of almost nine million, making it significantly bigger than the next largest cities of Birmingham and Manchester. As of 2022, Scotland's largest city, Glasgow had a population of around 1.7 million, with the largest cities in Northern Ireland, and Wales being Belfast and Cardiff, which had populations of 643,000 and 488,000 respectively.

The European Copernicus Coastal Flood Awareness System (ECFAS) project will contribute to the evolution of the Copernicus Emergency Monitoring Service by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS will provide a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.

The ECFAS Proof-of-Concept development will run from January 2021-December 2022. The ECFAS project is a collaboration between Istituto Universitario di Studi Superiori IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and is funded by the European Commission H2020 Framework Programme within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services.

This project has received funding from the European Union’s Horizon 2020 programme

Description of the containing files inside the Dataset.

The dataset was divided at European country level, except the Adriatic area which was extracted as a region and not on a country level due to the small size of the countries. The buffer zone of each data was 10km inland in order to be correlated with the new Copernicus product Coastal Zone LU/LC.

Specifically, the dataset includes the new Coastal LU/LC product which was implemented by the EEA and became available at the end of 2020. Additional information collected in relation to the location and characteristics of transport (road and railway) and utility networks (power plants), population density and time variability. Furthermore, some of the publicly available datasets that were used in CEMS related to the abovementioned assets were gathered such as OpenStreetMap (building footprints, road and railway network infrastructures), GeoNames (populated places but also names of administrative units, rivers and lakes, forests, hills and mountains, parks and recreational areas, etc.), the Global Human Settlement Layer (GHS) and Global Human Settlement Population Grid (GHS-POP) generated by JRC. Also, the dataset contains 2 layers with statistics information regarding the population of Europe per sex and age divided in administrative units at NUTS level 3. The first layers includes information fro the whole Europe and the second layer has only the information regaridng the population at the Coastal area. Finally, the dataset includes the global database of Floods protection standars. Below there are tables which present the dataset.

Copernicus Land Monitoring Service	Resolution	Comment
Coastal LU/LC	1:10.000	A Copernicus hotspot product to monitor landscape dynamics in coastal zones
EU-Hydro - Coastline	1:30.000	EU-Hydro is a dataset for all European countries providing the coastline
Natura 2000	1: 100000	A Copernicus hotspot product to monitor important areas for nature conservation
European Settlement Map	10m	A spatial raster dataset that is mapping human settlements in Europe
Imperviousness Density	10m	The percentage of sealed area
Impervious Built-up	10m	The part of the sealed surfaces where buildings can be found
Grassland 2018	10m	A binary grassland/non-grassland product
Tree Cover Density 2018	10m	Level of tree cover density in a range from 0-100%

Joint Research Center	Resolution	Comment
Global Human Settlement Population Grid GHS-POP)	250m	Residential population estimates for target year 2015
GHS settlement model layer (GHS-SMOD)	1km	The GHS Settlement Model grid delineates and classify settlement typologies via a logic of population size, population and built-up area densities
GHS-BUILT	10m	Built-up grid derived from Sentinel-2 global image composite for reference year 2018
ENACT 2011 Population Grid (ENACT-POP R2020A)	1km	The ENACT is a population density for the European Union that take into account major daily and monthly population variations
JRC Open Power Plants Database (JRC-PPDB-OPEN)	-	Europe’s open power plant database
GHS functional urban areas (GHS-FUA R2019A)	1km	City and its commuting zone (area of influence of the city in terms of labour market flows)
GHS Urban Centre Database (GHS-UCDB R2019A)	1km	Urban Centres defined by specific cut-off values on resident population and built-up surface

Additional Data	Resolution	Comment
Open Street Map (OSM)	-	BF, Transportation Network, Utilities Network, Places of Interest
CEMS	-	Data from Rapid Mapping activations in Europe
GeoNames	-	Populated places, Adm. units, Hydrography, Forests, Hills/Mountains, Parks, etc.
Global Administrative Areas	-	Administrative areas of all countries, at all levels of sub-division
NUTS3 Population Age/Sex Group	-	Eurostat population by age ansd sex statistics interesected with the NUTS3 Units
FLOPROS		A global database of FLOod PROtection Standards, which comprises information in the form of the flood return period associated with protection measures, at different spatial scales

Disclaimer:

ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.

This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211

Between 2015 and 2022, Estonia had the highest density of “right to be forgotten” or “right to erasure” requests issued to Google and Microsoft Bing, among other European countries, with almost 59 appeals per 10 thousand inhabitants. Registering the highest number of requests during the analyzed period, France ranked second regarding request density, with 46.2 requests per 10 thousand inhabitants.

In 2019, Latvia had the highest rail network density in Europe, with around 11.6 kilometers of tracks per 10,000 inhabitants. It was followed closely by Estonia and Finland, at 10.82 and 10.73 kilometers per 10,000 inhabitants respectively.

The European System of Social Indicators provides a systematically selected collection of time-series data to measure and monitor individual and societal well-being and selected dimensions of general social change across European societies. Beyond the member states of the European Union, the indicator system also covers two additional European nations and – depending on data availability – the United States and Japan as two important non-European reference societies. Guided by a conceptual framework, the European System of Social Indicators has been developed around three basic concepts – quality of life, social cohesion, and sustainability. While the concept of quality of life is supposed to cover dimensions of individual well-being, the notions of social cohesion as well as sustainability are used to conceptualize major characteristics and dimensions of societal or collective well-being. The indicator system is structured into 13 life domains altogether. Time-series data are available for nine life domains, which have been fully implemented.

Time series start at the beginning of the 1980s at the earliest and mostly end by 2013. As far as data availability allows, empirical observations are presented yearly. Most of the indicator time-series are broken down by selected sociodemographic variables, such as gender, age groups, employment status, or territorial characteristics. Regional disaggregations are being provided at the NUTS-1 or similar levels as far as meaningful and data availability allows. The European System of Social Indicators is preferably based on harmonized data sources, ensuring the best possible level of comparability across countries and time. The data sources used include international aggregate official statistics, for example, provided by EUROSTAT and the OECD, as well as microdata from various official as well as science-based cross-national surveys, such as the European Union Statistics on Income and Living Conditions (EU-SILC), Eurobarometer Surveys, the World Value Surveys, or the European Social Survey.

The European System of Social Indicators results from research activities within the former Social Indicators Research Centre at GESIS. In its initial stage, this research was part of the EuReporting-Project (Towards a European System of Social Reporting and Welfare Measurement), funded by the European Commission within its 4th European Research Framework Programme from 1998 to 2001. For more detailed information on the European System of Social Indicators, see the methodological report under „other documents“.
The data on the area of life ´Population, households and families´ is made up as follows: Demographic and socio-economic structures of society: migration and foreign population, population and household structures, population density and agglomeration, population size and growth, family formation Subjective well-being: Subjective assessment of the quality of service offerings Objective living conditions: Social services for the family Inequalities and social exclusion: Equal opportunities between men and women (division of housework; support from household members) Social relationships and ties: Quality of relationships between household members, Social relationships between different households Human capital: provision of daily care for elderly household members, provision of regular support for household members, time spent on raising children Values and attitudes: Values and attitudes towards the family domain, Values and attitudes towards the partnership and marriage domain.

The population density of Spain maintained a steadily at a rate of over 92 inhabitants per square kilometers in the last decade, with the latest figures revealing a density of 95 people per square kilometer in 2022. Spain’s degree of urbanization is rather high, with levels reaching over 81 percent of urbanization in the country. Andalusia, with a total number of 8.6 million inhabitants, ranked first on the list of most populous autonomous communities in Spain.

Population density: a world of contrast

Spain is far from the European Union’s average population density, which stood at approximately 111.89 people per square kilometer in 2021, that is, a difference of over 17 people per square meter below the average. Monaco, the country with the highest population density in the world, featured about 24,621 inhabitants per square kilometer, making Spain’s population density look minimal. The results in Macao were very similar, with a population density that reached over 21,000 people per square kilometer.

The re-population of a country

The population of Spain declined for many years during the economic recession, returning to a positive trend after 2015. The Spanish population is projected to increase by nearly two million by 2028 compared to 2024. Despite this expected increase, Spain has one of the lowest fertility rate in the European Union, with barely 1.29 children per woman according to the latest reports.

1. Total length of railways worldwide exceeds 1 million kilometres and recent railway development directly impacts wildlife because of animal-train collisions. Few studies, however, have analysed factors driving ungulate-train collisions. 2. We analysed over 3500 ungulate-train collisions including roe deer, red deer, wild boar, and moose collected in 2012-2015 in Poland. We compared train traffic characteristics (e.g. traffic intensity, speed, rail curvature), land-use and habitat characteristics (e.g. share of forests and build-up areas) and local ungulate population densities at collision sites and random sites distributed along the rail network. 3. Forest coverage generally increased, while urban areas decreased ungulate collision risk. Local density of ungulate species was strongly positively related to the relative collision risk in all four ungulate species, but above certain densities, the risk levelled off for all four species. 4. Train speed and train traffic intensity were positively associated with elevated collision risk in all four species, but the latter in a non-linear manner reached an asymptote at the level of ca. 10 trains per day. Rail curvature also increased probability of collisions with roe deer and red deer and possibly also wild boar. 5. Mortality rate of ungulates on railways in Poland is estimated to be 0.13-0.42% of annual hunting bags of studied species assuming that only one individual is killed at each occasion and ignoring undetected collisions. These values are expected to increase in near future due to increasing train speed in Central European countries. 6. Synthesis and applications. Ungulate-train collisions spots are characterised by surrounding forest, rail curvature, high train speed, and a moderate to high train traffic intensity. To reduce collision risk in a cost-effective way, we suggest to prioritise mitigation actions at sections of the railway characterized by those factors, e.g. by fencing and various warning devices. Due to nonlinear correlation between collision risk and population density, reducing density of ungulates will most likely reduce collision risk only marginally, and only in regions of low population densities where collision risk is relatively low anyway.

Numerical top-down effects on red deer (Cervus elaphus) are mainly shaped by humans rather than large carnivores across Europe

https://doi.org/10.5061/dryad.0cfxpnw7w

Suzanne T.S van Beeck Calkoen, Dries P.J. Kuijper, M. Apollonio, Lena Blondel, Carsten F. Dormann, Ilse Storch, Marco Heurich

Abstract

1. Terrestrial ecosystems are shaped by interacting top-down and bottom-up processes, with the magnitude of top-down control by large carnivores largely depending on environmental productivity. While carnivore-induced numerical effects on ungulate prey populations have been demonstrated in large, relatively undisturbed ecosystems, whether large carnivores can play a similar role in more human-dominated systems is a clear knowledge gap. As humans influence both predator and prey in a variety of ways, the ecological impacts of large carnivores can be largely modified. We quantified the interactive effects of human activities and large carniv...

In 1938, the year before the outbreak of the Second world War, the countries with the largest populations were China, the Soviet Union, and the United States, although the United Kingdom had the largest overall population when it's colonies, dominions, and metropole are combined. Alongside France, these were the five Allied "Great Powers" that emerged victorious from the Second World War. The Axis Powers in the war were led by Germany and Japan in their respective theaters, and their smaller populations were decisive factors in their defeat. Manpower as a resource In the context of the Second World War, a country or territory's population played a vital role in its ability to wage war on such a large scale. Not only were armies able to call upon their people to fight in the war and replenish their forces, but war economies were also dependent on their workforce being able to meet the agricultural, manufacturing, and logistical demands of the war. For the Axis powers, invasions and the annexation of territories were often motivated by the fact that it granted access to valuable resources that would further their own war effort - millions of people living in occupied territories were then forced to gather these resources, or forcibly transported to work in manufacturing in other Axis territories. Similarly, colonial powers were able to use resources taken from their territories to supply their armies, however this often had devastating consequences for the regions from which food was redirected, contributing to numerous food shortages and famines across Africa, Asia, and Europe. Men from annexed or colonized territories were also used in the armies of the war's Great Powers, and in the Axis armies especially. This meant that soldiers often fought alongside their former-enemies. Aftermath The Second World War was the costliest in human history, resulting in the deaths of between 70 and 85 million people. Due to the turmoil and destruction of the war, accurate records for death tolls generally do not exist, therefore pre-war populations (in combination with other statistics), are used to estimate death tolls. The Soviet Union is believed to have lost the largest amount of people during the war, suffering approximately 24 million fatalities by 1945, followed by China at around 20 million people. The Soviet death toll is equal to approximately 14 percent of its pre-war population - the countries with the highest relative death tolls in the war are found in Eastern Europe, due to the intensity of the conflict and the systematic genocide committed in the region during the war.

This metadata corresponds to the EUNIS Littoral biogenic habitat (salt marshes) types, predicted distribution of habitat suitability dataset.

Littoral habitats are those formed by animals such as worms and mussels or plants (salt marshes).

The verified littoral biogenic habitat samples used are derived from the Braun-Blanquet database (http://www.sci.muni.cz/botany/vegsci/braun_blanquet.php?lang=en) which is a centralised database of vegetation plots and comprises copies of national and regional databases using a unified taxonomic reference database. The geographic extent of the distribution data are all European countries except Armenia and Azerbaijan.

The modelled suitability for EUNIS saltmarsh habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. However, note that it is not representing the actual distribution of the habitat type. As predictors for the suitabilty modelling not only Climate and Soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables like Landuse, Vegetation height, Phenology, LAI(Leave Area Index) and Population density. Because the EBV's are restricted by the extent of the Remote Sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats.

The Training map files show the modelled suitable distribution, omitting the 10% of occurrence records in the least suitable environment under the assumption that they are not representative of the overall suitable habitat distribution. The 10 percentile training presence is an arbitrary threshold which omits all regions with habitat suitability lower than the suitability values for the lowest 10% of occurrence records.

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

In 2025, the Ile-de-France region, sometimes called the Paris region, was the most populous in France. It is located in the northern part of France, divided into eight departments and crossed by the Seine River. The region contains Paris, its large suburbs, and several rural areas. The total population in metropolitan France was estimated at around 65 million inhabitants. In the DOM (Overseas Department), France had more than two million citizens spread over the islands of Guadeloupe, Martinique, Reunion, Mayotte, and the South American territory of French Guyana. Ile-de-France: most populous region in France According to the source, more than 12 million French citizens lived in the Ile-de-France region. Ile-de-France was followed by Auvergne-Rhône-Alpes and Occitanie region which is in the Southern part of the country. Ile-de-France is not only the most populated region in France, it is also the French region with the highest population density. In 2020, there were 1,021.6 residents per square kilometer in Ile-de-France compared to 115.9 for Auvergne-Rhône-Alpes, the second most populated region in France. More than two million people were living in the city of Paris in 2025. Thus, the metropolitan area outside the city of Paris, called suburbs or banlieue in French, had more than ten million inhabitants. Ile-de-France concentrates the majority of the country’s economic and political activities. An urban population In 2024, the total population of France amounted to over 68 million. The population in the country increased since the mid-2000s. As well as the other European countries, France is experiencing urbanization. In 2023, more than 81 percent of the French population lived in cities. This phenomenon shapes France’s geography.

The population density in France was 123.27 people per square kilometer (47.24 per square mile) in 2021. This number has been slowly increasing for the past ten years. Higher population density is associated with urbanization, but not necessarily economic growth.

Comparative densities

France’s population density is higher than the European average. In fact, it is higher than any region except Asia, as well as the total world population density. This is likely due to the number of large cities in France. The country has one of the largest urban populations in the world. This shapes the French economic and social landscapes; the cities become more expensive, but they also bring more economic opportunities. These opportunites attract people both from the French countryside and other countries who hope to benefit from such jobs.

A tale of two countries

For those who can afford it, Paris can be a cosmopolitan paradise. However, with the average price of a rental apartment twice that of most other French cities, few can afford to live in the richest parts of the city. This stark difference in costs implies that average annual wages should have a similar difference between cities. While this is not a perfectly even cause and effect, it gives some explanation for the increasing population density of France.

Monaco led the ranking for countries with the highest population density in 2021, with nearly 25,000 residents per square kilometer. The Special Administrative Region Macao came in second, followed by Singapore. The world’s smallest country by area, the Holy See, came in 13th with close to 1,200 people per square kilometer.

The world’s second smallest country

Monaco is the world’s second smallest country, with an area of about two square kilometers, and its population only numbers around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the most prestigious Formula One race in the world.

The global population

Globally, the population density per square kilometer stands at about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase as well. In 1950, for example, the global population stood at about 2.54 billion people, and is expected to pass eight billions during 2023.