Berlin attracted the most tourist arrivals in Germany in 2023, which is perhaps to be expected. But the country has other city destinations with a lot to offer as well. Among them Hamburg in the north with the largest port in Germany and Munich, the capital of Bavaria, in the south. All three cities also have busy airports and railways. The top three Berlin recorded a significant drop in travel accommodation numbers in 2020, the year the COVID-19 pandemic began. Figures began to pick up again later, with 724 establishments open in 2024, though this was still less than in previous years. The numbers may also have to do with competition from such accommodation platforms as Airbnb. Hamburg is also catching up after the pandemic in terms of tourism, with noticeably more travel arrivals recorded recently. While 2021 saw around 3.3 million arrivals, there were already roughly 6.4 in 2023. Meanwhile, the average occupancy rate in Munich travel accommodation was also noticeably higher in 2022 than in previous years, with an almost 48 percent total. City tourism As of 2023, around 33.7 million people in Germany preferred city trips as a vacation. Numbers decreased somewhat in recent years. Various factors contribute to making a city attractive for tourists, among them mobility options, the ease of getting around, and spending time outside. In 2022, Germany’s largest cities were evaluated in terms of walking and cycling space availability. Munich scored highest at 51 percent, followed by Cologne with 46 percent and Hamburg with 42 percent. That same year, these cities were also evaluated in terms of traffic safety for pedestrians and cyclists. This time, Hamburg came first at 74 percent, and Berlin followed with 72 percent.

Out of the four largest cities in Germany, Munich received the highest score for space for walking and cycling in 2022. Munich scored 51 percent in the space for people category, which indicates how much road space is allocated to walking and cycling infrastructure, as well as levels of construction. Munich was followed by Cologne, which scored 46 percent.

Germany DE: Population in Largest City data was reported at 3,576,873.000 Person in 2024. This records an increase from the previous number of 3,573,938.000 Person for 2023. Germany DE: Population in Largest City data is updated yearly, averaging 3,388,441.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 3,576,873.000 Person in 2024 and a record low of 3,041,327.000 Person in 1983. Germany DE: Population in Largest City 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 in largest city is the urban population living in the country's largest metropolitan area.;United Nations, World Urbanization Prospects.;;

Population in largest city in Germany was reported at 3576873 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Germany DE: Population in Largest City: as % of Urban Population data was reported at 5.535 % in 2024. This records an increase from the previous number of 5.519 % for 2023. Germany DE: Population in Largest City: as % of Urban Population data is updated yearly, averaging 5.542 % from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 6.272 % in 1960 and a record low of 5.323 % in 1982. Germany DE: Population in Largest City: as % of Urban Population 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 in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.;United Nations, World Urbanization Prospects.;Weighted average;

Population in the largest city (% of urban population) in Germany was reported at 5.4986 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Germany - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

As of mid-2023, Hamburg was the German city with the highest public electric vehicle charging infrastructure index score, at ** percent. Munich was the only other German city with a score above ** percent.

🇩🇪 독일

In 2025, Moscow was the largest city in Europe with an estimated urban agglomeration of 12.74 million people. The French capital, Paris, was the second largest city in 2025 at 11.35 million, followed by the capitals of the United Kingdom and Spain, with London at 9.84 million and Madrid at 6.81 million people. Istanbul, which would otherwise be the largest city in Europe in 2025, is excluded as it is only partially in Europe, with a sizeable part of its population living in Asia. Europe’s population is almost 750 million Since 1950, the population of Europe has increased by approximately 200 million people, increasing from 550 million to 750 million in these seventy years. Before the turn of the millennium, Europe was the second-most populated continent, before it was overtaken by Africa, which saw its population increase from 228 million in 1950 to 817 million by 2000. Asia has consistently had the largest population of the world’s continents and was estimated to have a population of 4.6 billion. Europe’s largest countries Including its territory in Asia, Russia is by far the largest country in the world, with a territory of around 17 million square kilometers, almost double that of the next largest country, Canada. Within Europe, Russia also has the continent's largest population at 145 million, followed by Germany at 83 million and the United Kingdom at almost 68 million. By contrast, Europe is also home to various micro-states such as San Marino, which has a population of just 30 thousand.

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

Social and economic figures for 67 large West German cities. The data aggregated at city level have been collected for most topics over several years, but not necessarily over the entire reference time period.

Topics: 1. Situation of the city: surface area of the city; fringe location in the Federal Republic.

1. Residential population: total residential population; German and foreign residential population.

2. Population movement:live births; deaths; influx; departures; birth rate; death rate; population shifts; divorce rate; migration rate; illegitimate births.

3. Education figures: school degrees; occupational degrees; university degrees.

4. Wage and income: number of taxpayers in the various tax classes as well as municipality income tax revenue in the respective classes; calculated income figures, such as e.g. inequality of income distribution, mean income or mean wage of employees as well as standard deviation of these figures; GINI index.

5. Gross domestic product and gross product: gross product altogether; gross product organized according to area of business; gross domestic product; employees in the economic sectors.

6. Taxes and debts: debt per resident; income tax and business tax to which the municipality is entitled; municipality tax potential and indicators for municipality economic strength.

7. Debt repayment and management expenditures: debt repayment, interest expenditures, management expenditures and personnel expenditures.

8. From the ´BUNTE´ City Test of 1979 based on 100 respondents per city averages of satisfaction were calculated. satisfaction with: central location of the city, the number of green areas, historical buildings, the number of high-rises, the variety of the citizens, openness to the world, the dialect spoken, the sociability, the density of the traffic network, the OEPNV prices {local public passenger transport}, the supply of public transportation, provision with culture, the selection for consumers, the climate, clean air, noise pollution, the leisure selection, real estate prices, the supply of residences, one´s own payment, the job market selection, the distance from work, the number of one´s friends, contact opportunities, receptiveness of the neighbors, local recreational areas, sport opportunities and the selection of further education possibilities.

9. Traffic and economy: airport and Intercity connection; number of kilometers of subway available, kilometers of streetcar, and kilometers of bus lines per resident; car rate; index of traffic quality; commuters; property prices; prices for one´s own home; purchasing power.

10. Crime: recorded total crime and classification according to armed robbery, theft from living-rooms, of automobiles as well as from motor vehicles, robberies and purse snatching; classification according to young or adult suspects with these crimes; crime stress figures. 12. Welfare: welfare recipients and social expenditures; proportion of welfare recipients in the total population and classification according to German and foreign recipients; aid with livelihood; expenditures according to the youth welfare law; kindergarten openings; culture expenditures per resident. 13. Foreigners: proportion of foreigners in the residential population.

11. Students: number of German students and total number of students; proportion of students in the residential population.

12. Unemployed: unemployment rate; unemployed according to employment office districts and employment office departments.

13. Places of work: workers employed in companies, organized according to area of business.

14. Government employees: full-time, part-time and total government employees of federal government, states and municipalities as well as differentiated according to workers, employees, civil servants and judges.

15. Employees covered by social security according to education and branch of economy: proportion of various education levels in the individual branches of the economy.

Out of the four largest cities in Germany, Hamburg was scored the safest for walking and cycling in 2022. The northern German city scored ** percent in the safe roads category, which indicates how many pedestrian and cyclist fatalities occurred in the city in relation to its population.

This statistic shows the degree of urbanization in Germany from 2013 to 2023. Urbanization means the share of urban population in the total population of a country. In 2023, 77.77 percent of Germany's total population lived in urban areas and cities. Urbanization in Germany Currently, about three quarter of the German population live in urban areas and cities, which is more than in most nations around the world. Urbanization, as it can be seen in this graph, refers to the number of people living in an urban area and has nothing to do with the actual geographical size or footprint of an area or country. A country which is significantly bigger than Germany could have a similar degree of urbanization, just because not all areas in the country are inhabitable, for example. One example for this is Russia, where urbanization has reached comparable figures to Germany, even though its geographical size is significantly bigger. However, Germany’s level of urbanization does not make the list of the top 30 most urbanized nations in the world, where urbanization rates are higher than 83 percent. Also, while 25 percent of the population in Germany still lives in rural areas, rural livelihoods are not dependent on agriculture, as only 0.75 percent of GDP came from the agricultural sector in 2014. So while Germany's urbanization rate is growing, a significant percentage of the population is still living in rural areas. Furthermore, Germany has a number of shrinking cities which are located to the east and in older industrial regions around the country. Considering that population growth in Germany is on the decline, because of low fertility rates, and that a number of cities are shrinking, the urban population is likely shifting to bigger cities which have more economic opportunities than smaller ones.

In 2023, around 27.4 percent of residents in Bremen were at risk of living in poverty. This list shows the 15 cities in Germany with the highest at-risk-of-poverty rates.

Chart and table of population level and growth rate for the Berlin, Germany metro area from 1950 to 2025.

The author statistically depicts the population growth of the largest German cities between 1871 and 1910. He uses the official statistics. He breaks down the cities into zones in order to make their development comparable.In order to do this, he used the term agglomeration, with which he refers to the contiguous built-up area, with developed infrastructure as well as traffic routes and rail traffic, and their population. In order to find as uniform a demarcation as possible, he delimits the areas of the respective cities by drawing circles whose radius starts from the center of the city and is 10 km long. This is the entire agglomeration, which finally differentiates it into the inner agglomeration and outer agglomeration. The inner agglomeration is located within 5 km of the city center. The outer agglomeration refers to the areas at a distance of 5 to 10 km around the city center. The following cities are being investigated by him:Aachen; Augsburg; Berlin; Braunschweig; Bremen; Breslau (Wroclaw); Kassel (in the data old spelling: Cassel); Chemnitz; Cologne (in the data old spelling: Cöln); Krefeld (in the data old spelling: Crefeld); Danzig; Dortmund; Dresden; Dusseldorf; Duisburg; Elberfeld; Erfurt; Essen; Frankfurt a. Main; Halle; Hannover; Karlsruhe; Kiel; Koenigsberg; Leipzig; Magdeburg; Mainz; Mannheim; Munich; Nuremberg; Plauen; Posen; Saarbrücken; Stettin; Strasbourg; Stuttgart. Variables are the city area, the inhabitants of the city as a whole, the population as an index on the basis of 1971 = 100, the inhabitants of the territories incorporated into the cities between 1871 and 1910, and the population density of the city and the incorporated areas. Reporting years are 1871, 1880, 1890,1900, and 1910. The data has been classified in the online database histat (https://histat.gesis.org/histat/) under the topic ´population´.

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.

Among the four largest cities in Germany, Cologne scored the highest for availability of shared bicycles and e-scooters, indicating that it had the largest number of shared micro-mobility vehicles in relation to its population size. Hamburg ranked second among the largest cities in the country.

The present study is an exemplary analysis of the development and the changes of living in a big city of the 19th century. The study tries to develop indicators for the evaluation of the urban housing provision during the process of urbanization that relate occurrence and extent of housing shortage with quantifiable standards of housing provision looking at the example of Hamburg in the second part of the 19th century. Thereby a long term analysis of the material circumstances of housing conditions will be shown and at the same time the concept of housing shortage in its historical relativity through a comparison with the living conditions in the Federal Republic of Germany will be clarified. Based on this, in the second step standards and social disparities of housing in their social stratification and in its urban structure change will be examined. In how far the example of Hamburg in the late 19th century can be generalized will be reviewed through a comparison of housing types and housing provision levels of German cities using a cross-sectional comparison of 1905. “Based on a comparison of metropolitan living situations it will be attempted to show the level and extend of disparities in the housing provision in the late 19th century using a typology of metropolitan housing structures. We assume that the housing structure of a city can only be represented in a very imperfect way using a more or less arbitrary chosen random variable. Much more information can be derived from the correlation of many different characteristics of the basic structure of urban housing, that can be understood as quasi-independent variables and that build the basis of the comparison. For a hierarchical cluster analysis with 27 variables 30 cities were considered for statistical classification and an empirical typecast. The used data is based on statistical housing surveys of German cities that were made in the context of the population census from the first December of 1905 and on the information if the profession and establishment census from July 1907. Three fourth of the cities (with more than 100.000 inhabitants) of the German Empire were selected” (Wischermann, a. cit., p. 401).“The excellent public statistics from Hamburg were, especially in the turn of the century, adjusted with many private surveys. Therefor the state of the quantitative sources for Hamburg is probably the best one of the German Empire… The situation of the sources for the investigation of the development of the housing circumstances in the 19th century in Hamburg is better than in other parts of Germany. This data basis enabled this study going back until the beginning of the industrialization; it enabled the investigation of one of the most important German case studies of changes in urban housing in the 19th century in a city that was at the frontier of English, French and Berlin zones of influence on the development of living circumstances in Germany. It is also a paradigm for the investigation of structural changes of housing within a city under the impact of economic transitions (extension of the harbor), hygienic innovation (since the cholera epidemic) and several urban development projects. Especially in the German urbanization period quality and structure of housing in the developing cities are connected with the urban area and the socio-spatial differentiation of housing in an extent that has not been known so far.” (Wischermann, a. cit., p. 13, p. 15). Data tables in HISTAT:(In addition, the cross-sectional data for 1905 for cluster analysis of German cities (30 cities, 27 variables for the year 1905) can be ordered at the GESIS data archive number ZA8474). A. Tables from the appendixA.01 Development of the population in the inner city and the suburbs of Hamburg (1817-1866)A.02 Housing stock in the inner city and the suburbs of Hamburg (1817-1866)A.03 Present local population of Hamburg and the districts (1867-1910)A.04 Movement of the population in Hamburg (1864-1913)A.05 The population density of Hamburg’s districts (1871-1910)A.06 Housing stock density of Hamburg’s districts(1867-1910)A.07 The provision level of housing in Hamburg (1867-1912)A.08 Internal density of Hamburg and its districts A: residents per room without kitchens (1885-1910)A.09 Internal density of Hamburg and its districts B: inhabitants per heated room (1885-1910)A.10 Occupancy of Hamburg and its districts: residents per apartment (1867-1910)A.11 Empty rooms and their rental value in Hamburg (1866-1913)A.12 Empty rooms in Hamburg and its districts (1867-1910) A.13 New construction, alteration and demolition statistics of the city of Hamburg (1885-1912)A.14 Small housing production in Hamburg (1896-1912)A.15 Landowner relations in Hamburg (1875-1910)A.16 Development of floor living in Hamburg (1867-1910)A.17 Residents after number of floors on Hamburg (1867-1910)A.18 Basement apartments in the districts of Hamburg (1867-1910)A.19 Apartments in the back building in Ham...

This data includes Luxembourg cities with population 5 thousand and more created by GfK MACON company, Germany.