Chart and table of Germany population density from 1950 to 2025. United Nations projections are also included through the year 2100.

Germany DE: Population Density: People per Square Km data was reported at 238.017 Person/sq km in 2020. This records an increase from the previous number of 237.823 Person/sq km for 2019. Germany DE: Population Density: People per Square Km data is updated yearly, averaging 228.349 Person/sq km from Dec 1961 (Median) to 2020, with 60 observations. The data reached an all-time high of 238.017 Person/sq km in 2020 and a record low of 210.173 Person/sq km in 1961. Germany DE: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;

4,244 people per square kilometer lived in Berlin in 2023. This was an increase compared to the previous year at 4,214. The population density has been increasing slowly during the specified period.

The population density in Hamburg has been steadily increasing in recent years, with 2,530 inhabitants per square kilometer in 2023. This statistic shows the population density in Hamburg from 1995 to 2023.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Germany: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

In 2023, 40-59-year-olds made up the largest age group in Germany, at almost 23 million people. The most recent figures confirm that the next-largest age group was 65 years and older, at 18.89 million. Aging population With the number of people belonging to older age groups visibly outstripping younger ones, in recent years it has become clear that Germany’s population is aging. In fact, figures on age structure in Germany depict a constant trend of a slowly increasing population share aged over 65 since 2012. Meanwhile, the share of population members aged 0 to 14 years has been falling, which was also reflected in the fluctuating national birth rate in recent years. A look at the future Germany’s current total population stands at 84.7 million. While this number is predicted to increase, the same goes for the age group of 65 years and older. This means that the national population will continue to age.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)

-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method.

Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

238.0 (people per sq. km) in 2020. Population density is midyear population divided by land area in square kilometers.

In 1800, the region of Germany was not a single, unified nation, but a collection of decentralized, independent states, bound together as part of the Holy Roman Empire. This empire was dissolved, however, in 1806, during the Revolutionary and Napoleonic eras in Europe, and the German Confederation was established in 1815. Napoleonic reforms led to the abolition of serfdom, extension of voting rights to property-owners, and an overall increase in living standards. The population grew throughout the remainder of the century, as improvements in sanitation and medicine (namely, mandatory vaccination policies) saw child mortality rates fall in later decades. As Germany industrialized and the economy grew, so too did the argument for nationhood; calls for pan-Germanism (the unification of all German-speaking lands) grew more popular among the lower classes in the mid-1800s, especially following the revolutions of 1948-49. In contrast, industrialization and poor harvests also saw high unemployment in rural regions, which led to waves of mass migration, particularly to the U.S.. In 1886, the Austro-Prussian War united northern Germany under a new Confederation, while the remaining German states (excluding Austria and Switzerland) joined following the Franco-Prussian War in 1871; this established the German Empire, under the Prussian leadership of Emperor Wilhelm I and Chancellor Otto von Bismarck. 1871 to 1945 - Unification to the Second World War The first decades of unification saw Germany rise to become one of Europe's strongest and most advanced nations, and challenge other world powers on an international scale, establishing colonies in Africa and the Pacific. These endeavors were cut short, however, when the Austro-Hungarian heir apparent was assassinated in Sarajevo; Germany promised a "blank check" of support for Austria's retaliation, who subsequently declared war on Serbia and set the First World War in motion. Viewed as the strongest of the Central Powers, Germany mobilized over 11 million men throughout the war, and its army fought in all theaters. As the war progressed, both the military and civilian populations grew increasingly weakened due to malnutrition, as Germany's resources became stretched. By the war's end in 1918, Germany suffered over 2 million civilian and military deaths due to conflict, and several hundred thousand more during the accompanying influenza pandemic. Mass displacement and the restructuring of Europe's borders through the Treaty of Versailles saw the population drop by several million more.

Reparations and economic mismanagement also financially crippled Germany and led to bitter indignation among many Germans in the interwar period; something that was exploited by Adolf Hitler on his rise to power. Reckless printing of money caused hyperinflation in 1923, when the currency became so worthless that basic items were priced at trillions of Marks; the introduction of the Rentenmark then stabilized the economy before the Great Depression of 1929 sent it back into dramatic decline. When Hitler became Chancellor of Germany in 1933, the Nazi government disregarded the Treaty of Versailles' restrictions and Germany rose once more to become an emerging superpower. Hitler's desire for territorial expansion into eastern Europe and the creation of an ethnically-homogenous German empire then led to the invasion of Poland in 1939, which is considered the beginning of the Second World War in Europe. Again, almost every aspect of German life contributed to the war effort, and more than 13 million men were mobilized. After six years of war, and over seven million German deaths, the Axis powers were defeated and Germany was divided into four zones administered by France, the Soviet Union, the UK, and the U.S.. Mass displacement, shifting borders, and the relocation of peoples based on ethnicity also greatly affected the population during this time. 1945 to 2020 - Partition and Reunification In the late 1940s, cold war tensions led to two distinct states emerging in Germany; the Soviet-controlled east became the communist German Democratic Republic (DDR), and the three western zones merged to form the democratic Federal Republic of Germany. Additionally, Berlin was split in a similar fashion, although its location deep inside DDR territory created series of problems and opportunities for the those on either side. Life quickly changed depending on which side of the border one lived. Within a decade, rapid economic recovery saw West Germany become western Europe's strongest economy and a key international player. In the east, living standards were much lower, although unemployment was almost non-existent; internationally, East Germany was the strongest economy in the Eastern Bloc (after the USSR), though it eventually fell behind the West by the 1970s. The restriction of movement between the two states also led to labor shortages in the West, and an influx of migrants from...

The system of social indicators for the Federal Republic of Germany - developed in its original version as part of the SPES project under the direction of Wolfgang Zapf - provides quantitative information on levels, distributions and changes in quality of life, social progress and social change in Germany from 1950 to 2013, i.e. over a period of more than sixty years. With the approximately 400 objective and subjective indicators that the indicator system comprises in total, it claims to measure welfare and quality of life in Germany in a differentiated way across various areas of life and to observe them over time. In addition to the indicators for 13 areas of life, including income, education and health, a selection of cross-cutting global welfare measures were also included in the dashboard, i.e. general welfare indicators such as life satisfaction, social isolation or the Human Development Index. Based on available data from official statistics and survey data, time series were compiled for all indicators, ideally with annual values from 1950 to 2013. Around 90 of the indicators were marked as "key indicators" in order to highlight central dimensions of welfare and quality of life across the various areas of life. The further development and expansion, regular maintenance and updating as well as the provision of the data of the system of social indicators for the Federal Republic of Germany have been among the tasks of the Center for Social Indicator Research, which is based at GESIS, since 1987. For a detailed description of the system of social indicators for the Federal Republic of Germany, see the study description under "Other documents".
The data for the area of life ´population´ is made up as follows:

Agglomeration and migration: external migration, number of immigration, net migration, share of immigration from the EU in total immigration, number of asylum seekers per 10,000 inhabitants. Population density: population density, population density in independent cities, population density in large cities, population density in communities with less than 5000 inhabitants. Regional mobility: internal migration. Burden on the working population: total burden of support (inactive population ratio), burden of supporting children (children´s quotient), burden of supporting students (education quotient), burden of supporting older people (old-age quotient). Population size, growth and structure: Population size (resident population (end of year), population growth rate, natural population growth), generative behavior (net production rate, combined birth rate, mean age at first child), population structure (proportion of the population under 15 years, proportion of the population between 15 and 15). y. and 65 y., proportion of the population over 65 years of age), ethnic structure and integration (proportion of foreigners, proportion of foreigners from the European Union, proportion of marriages between Germans and foreigners, consent for foreigners to remain). Forms of cohabitation: propensity to marry (marriage rate of 35 to 45 year olds, marriage age of single people, combined first marriage rate (= total marriage rate)), importance of stability of marriage and family (out-of-wedlock birth rate, divorce rate, combined divorce rate, remarriage rate), lifestyles and family types (Proportion of single-person households, proportion of incomplete families, proportion of non-marital partnerships, families with children, families with one child, families with two children, families with three children, families with four or more children), widowhood disparity (gender ratio of widowed people aged 65 and over). year of life), subjective evaluation of the family (ideal number of children, importance of the family, family satisfaction). Household structure: contraction tendency (proportion of 3- and 4-generation households, proportion of the population in large households (5 or more people)), solitarization (proportion of the population in single-person households).

Germany population density for 400m H3 hexagons.

Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution.

Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.

This statistic shows a distribution of beer sales in relation to the population in Germany as of 2023. In Thuringia and Saxony, beer sales in food retail stores made up 11 percent, with 7 percent of the German population living in this state.

Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, the yellow areas of highest density range from 30,000 to 150,000 persons per square kilometer. In those areas, if the people were spread out evenly across the area, there would be just 4 to 9 meters between them. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.This dataset is comprised of multiple sources. All of the demographic data are from Michael Bauer Research with the exception of the following countries:Australia: Esri Australia and MapData ServicesCanada: Esri Canada and EnvironicsFrance: Esri FranceGermany: Esri Germany and NexigaIndia: Esri India and IndicusJapan: Esri JapanSouth Korea: Esri Korea and OPENmateSpain: Esri España and AISUnited States: Esri Demographics

This dataset features three gridded population dadasets of Germany on a 10m grid. The units are people per grid cell.

Datasets

DE_POP_VOLADJ16: This dataset was produced by disaggregating national census counts to 10m grid cells based on a weighted dasymetric mapping approach. A building density, building height and building type dataset were used as underlying covariates, with an adjusted volume for multi-family residential buildings.

DE_POP_TDBP: This dataset is considered a best product, based on a dasymetric mapping approach that disaggregated municipal census counts to 10m grid cells using the same three underyling covariate layers.

DE_POP_BU: This dataset is based on a bottom-up gridded population estimate. A building density, building height and building type layer were used to compute a living floor area dataset in a 10m grid. Using federal statistics on the average living floor are per capita, this bottom-up estimate was created.

Please refer to the related publication for details.

Temporal extent

The building density layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: http://doi.org/10.1594/PANGAEA.920894)

The building height layer is representative for ca. 2015 (doi: 10.5281/zenodo.4066295)

The building types layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: 10.5281/zenodo.4601219)

The underlying census data is from 2018.

Data format

The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (.tif). There is a mosaic in GDAL Virtual format (.vrt), which can readily be opened in most Geographic Information Systems.

Further information

For further information, please see the publication or contact Franz Schug (franz.schug@geo.hu-berlin.de). A web-visualization of this dataset is available here.

Publication

Schug, F., Frantz, D., van der Linden, S., & Hostert, P. (2021). Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates. PLOS ONE. DOI: 10.1371/journal.pone.0249044

Acknowledgements

Census data were provided by the German Federal Statistical Offices.

Funding This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

Content

A dataset of counties that are representative for Germany with regard to

the average disposable income,

the quota of divorces,

the respective quotas of employees working in the services (excluding logistics, security, and cleaning) and the MINT sectors,

the proportions of age groups in the total proportion of the respective population, with age groups in five-year strata for the population aged between 30 and 65 and the population in the age range between 65 and 75 each considered separately for the calculation of representativeness.

In addition, data from the four big cities Berlin, München (Munich), Hamburg, and Köln (Cologne) were collected and reflected in the dataset.

The dataset is based on the most recent data available at the time of the creation of the dataset, mainly deriving from 2022, as set out in detail in the readme.md file.

Method applied

The selection of the representative counties, as reflected in the dataset, was performed on the basis of official statistics with the aim of obtaining a confidence rate of 95%. The selection was based on a principal component analysis of the statistical data available for Germany and the addition of the regions with the lowest population density and the highest and lowest per capita disposable income. A check of the representativity of the selected counties was performed.

In the case of Leipzig, the city and the district had to be treated together, in deviation from the official territorial division, with respect to a specific use case of the data.

Density of nursing and midwifery personnel of Germany decreased by 0.40% from 12.4 number per thousand population in 2020 to 12.3 number per thousand population in 2021. Since the 2.37% rise in 2019, density of nursing and midwifery personnel rose by 1.74% in 2021.

Population density by NUTS 3 region

Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, the yellow areas of highest density range from 30,000 to 150,000 persons per square kilometer. In those areas, if the people were spread out evenly across the area, there would be just 4 to 9 meters between them. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.This dataset is comprised of multiple sources. All of the demographic data are from Michael Bauer Research with the exception of the following countries:Australia: Esri Australia and MapData ServicesCanada: Esri Canada and EnvironicsFrance: Esri FranceGermany: Esri Germany and NexigaIndia: Esri India and IndicusJapan: Esri JapanSouth Korea: Esri Korea and OPENmateSpain: Esri España and AISUnited States: Esri Demographics

Chart and table of population level and growth rate for the Berlin, Germany metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

Timeseries of structure and development of the former German Democratic Republic’s population.

The aim of this data-collection is to inform about the population’s structure and development in the former GDR, including East-Berlin, from 1946 to 1989.

Basis of the compilation is the published statistical population overview of the German Federal Statistical Office (Statistisches Bundesamt (hrsg.): Sonderreihe mit Beiträgen für das Gebiet der ehemaligen DDR. Heft 3: Bevölkerungsstatistische Übersichten 1946 bis 1989. Wiesbaden, 1993), completed by census data and scientific publications.

The survey contains details on population and populationstructure (population-size, -growth, density, agegroups, etc.), on natural population movement (birth, decease, marriages, divorces), on spatial population movement (internal migration, migration beyond the borders of the former GDR), and on households.

The datacompilation covers the following topics:

A) population B) natural population movement C) households D) migration

Topics:

Data-Tables in the download-system HISTAT (Thema: Bevölkerung)

A. Bevölkerungsstand:

A01 Bevölkerungsstand und Bevölkerungsentwicklung (1939-1989) A02 Bevölkerung nach Altersgruppen 1946-1989 A03 Männliche Bevölkerung nach Altersgruppen 1946-1989 A04 Weibliche Bevölkerung nach Altersgruppen 1946-1989 A05. Bevölkerungsgröße, Bevölkerungswachstum, Bevölkerungsdichte und Sexualproportion 1950- 1992 A06. Bevölkerung insgesamt, männlich und weiblich nach Ländern 1950-1998 A07. Fläche, Bevölkerung am Ort der Hauptwohnung und Bevölkerungsdichte für 1950, 1964, 1971, 1981 A08. Bevölkerung am Ort der Hauptwohnung nach Altersgruppen und Geschlecht 1950-1981 A09. Bevölkerung am Ort der Hauptwohnung nach Altersgruppen und Geschlecht 1950-1981 A10. Bevölkerung ab 18 Jahre am Ort der Hauptwohnung nach Familienstand und Geschlecht 1950-1981 A11. Fläche und Bevölkerung nach Bezirken 1950-1989 A12. Bevölkerung nach Altersgruppen und Geschlecht für die neuen Länder und Berlin Ost 1950-1990 A13 Bevölkerung nach Gemeindegrößenklassen (in 1000) 1950-1989

B. Natürliche Bevölkerungsbewegung

B01 Natürliche Bevölkerungsbewegung 1946-1995 B02a Eheschließungen, durschnittliches Heiratsalter, Ehescheidungen 1946-1989 B02b Eheschließungen nach Familienstand der Partner vor Eheschließung 1946-1989 B03 Eheschließende, Ersteheschließende und Wiederverheiratete (insgesamt) 1946-1989 B04 Eheschließende nach Ersteheschließenden und Wiederverheirateten (je 100 Eheschließende) 1946-1989 B05 Eheschließende nach Familienstand vor der Eheschließung (insgesamt) 1946-1989 B06 Eheschließende nach Familienstand vor der Eheschließung (je 100 Eheschließende) 1946-1989 B07 Zusammengefasste Geburtenziffer nach Altersgruppen 1952-1989 B08 Das Reproduktionsniveau der Bevölkerung 1946-1989 B09 Durchschnittliche Lebenserwartung Neugeborener in Jahren 1946-1989 B10a Geborene, Lebendgeborene und Totgeborene nach Legitimität 1952-1989 B10b Lebend- und Totgeborene nach Geschlecht 1950-1989 B11 Zusammengefaßte Geburtenziffer nach Gemeindegrößenklassen (1965-1989) B12 Altersgruppenspezifische Sterbeziffern nach Geschlecht ( standardisiert) 1964-1989 B13a Gestorbene insgesamt und gestorbene Säuglinge nach Geschlecht (1946-1989) B13b Gestorbene nach ausgewählten Todesursachen und nach Geschlecht 1947-1989 B13c Gestorbene nach ausgewählten Krankheiten als Todesursachen und nach Geschlecht 1947-1989 B14 Gestorbene infolge Suizid- DDR 1947-1989 B15 Gestorbene infolge Suizid- BRD B16 Gestorbene infolge Mord und Totschlag- DDR 1949-1989 B17 Gestorbene infolge Mord und Totschlag- BRD / Bundesrepublik Deutschland (1961-1989) B18 Die Entwicklung der Fruchtbarkeitsziffern in den beiden Teilen Deutschlands (1946/50-1995)

C. Haushalte

C01 Privathaushalte nach Haushaltsgröße 1950-1981 C02 Personen in Privathaushalten und Gemeinschaftseinrichtungen 1950-1981 C03 Mehrpersonenhaushalte nach im Haushalt lebenden Kindern unter 17 Jahren 1950-1981 C04 Privathaushalte nach Haushaltsgroesse und nach Altersgruppen des Haushaltsvorstandes 1950 bis 1981 C05 Privathaushalte nach Haushaltsgroesse und nach Altersgruppen des maennlichen Haushaltsvorstandes 1950 bis 1981

D. Wanderung

D01 Wanderung über die Grenzen der DDR 1951-1989 D02 Wanderung über die Grenzen der DDR nach Altersgruppen 1965-1989 D03 Binnenwanderungsgewinn bzw.- verlust (-) nach Gemeindegrößenklassen 1970-1989 D04 Saldo aus zu- und Fortzügen (-) über die Grenzen der ehemaligen DDR nach Gemeindegrößeklassen 1965-1989 D05 Binnenwanderung über die Gemeinde- bzw. Kreisgrenzen 1953-1989