Mogadishu in Somalia led the ranking of cities with the highest population density in 2023, with ****** residents per square kilometer. When it comes to countries, Monaco is the most densely populated state worldwide.

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 of 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 a population of only 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 is 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. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

In 2022, the estimated population density of China was around 150.42 people per square kilometer. That year, China's population size declined for the first time in decades. Although China is the most populous country in the world, its overall population density is not much higher than the average population density in Asia. Uneven population distribution China is one of the largest countries in terms of land area, and its population density figures vary dramatically from region to region. Overall, the coastal regions in the East and Southeast have the highest population densities, as they belong to the more economically developed regions of the country. These coastal regions also have a higher urbanization rate. On the contrary, the regions in the West are covered with mountain landscapes which are not suitable for the development of big cities. Populous cities in China Several Chinese cities rank among the most populous cities in the world. According to estimates, Beijing and Shanghai will rank among the top ten megacities in the world by 2030. Both cities are also the largest Chinese cities in terms of land area. The previous colonial regions, Macao and Hong Kong, are two of the most densely populated cities in the world.

In the last century, the global population has increased by billions of people. And it is still growing. Job opportunities in large cities have caused an influx of people to these already packed locations. This has resulted in an increase in population density for these cities, which are now forced to expand in order to accommodate the growing population. Population density is the average number of people per unit, usually miles or kilometers, of land area. Understanding and mapping population density is important. Experts can use this information to inform decisions around resource allocation, natural disaster relief, and new infrastructure projects. Infectious disease scientists use these maps to understand the spread of infectious disease, a topic that has become critical after the COVID-19 global pandemic.While a useful tool for decision and policymakers, it is important to understand the limitations of population density. Population density is most effective in small scale places—cities or neighborhoods—where people are evenly distributed. Whereas at a larger scale, such as the state, region, or province level, population density could vary widely as it includes a mix of urban, suburban, and rural places. All of these areas have a vastly different population density, but they are averaged together. This means urban areas could appear to have fewer people than they really do, while rural areas would seem to have more. Use this map to explore the estimated global population density (people per square kilometer) in 2020. Where do people tend to live? Why might they choose those places? Do you live in a place with a high population density or a low one?

As of July 2022, Monaco is the country with the highest population density worldwide with an estimated population of nearly 24,500 per square kilometer. However, by 2050, it is expected to be overtaken by the Special Administrative Region of Macao.

This graph shows the population density of the United States of America from 1790 to 2019. In 2019, the population density was approximately 92.9 residents per square mile of land area. Population density in the United States Population density has been tracked for over two hundred years in the United States. Over the last two centuries, the number of people living in the United States per square mile has grown from 4.5 in 1790 to 87.4 in 2010. After examining the data in detail, it becomes clear that a major population increase started around 1870. Population density was roughly 11 at the time and has doubled in the last century. Since then, population density grew by about 16 percent each decade. Population density doubled in 1900, and grew in total by around 800 percent until 2010.

The population density of the United States varies from state to state. The most densely populated state is New Jersey, with 1,208 people per square mile living there. Rhode Island is the second most densely populated state, with slightly over 1,000 inhabitants per square mile. A number of New England states follow at the top of the ranking, making the northeastern region of the United States the most densely populated region of the country.

The least populated U.S. state is the vast territory of Alaska. Only 1.3 inhabitants per square mile reside in the largest state of the U.S.

Compared to other countries around the world, the United States does not rank within the top 50, in terms of population density. Most of the leading countries and territories are city states. However, the U.S. is one of the most populous countries in the world, with a total population of over 327 million inhabitants, as of 2018.

Canada, with 3.3 people per square kilometre, has one of the lowest population densities in the world. In 2001, most of Canada's population of 30 million lived within 200 kilometres of the United States. In fact, the inhabitants of our three biggest cities — Toronto, Montréal and Vancouver — can drive to the border in less than two hours. Thousands of kilometres to the north, our polar region — the Yukon Territory, the Northwest Territories and Nunavut — is relatively empty, embracing 41% of our land mass but only 0.3% of our population. Human habitation in the solitary north clings largely to scattered settlements: villages among vast expanses of virgin ice, snow, tundra and taiga.

Disclaimer: These data are updated by the author and are not an official product of the Federal Reserve Bank of Cleveland.This project provides two sets of migration estimates for the major US metro areas. The first series measures net migration of people to and from the urban neighborhoods of the metro areas. The second series covers all neighborhoods but breaks down net migration to other regions by four region types: (1) high-cost metros, (2) affordable, large metros, (3) midsized metros, and (4) small metros and rural areas. These series were introduced in a Cleveland Fed District Data Brief entitled “Urban and Regional Migration Estimates: Will Your City Recover from the Pandemic?"The migration estimates in this project are created with data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel (CCP). The CCP is a 5 percent random sample of the credit histories maintained by Equifax. The CCP reports the census block of residence for over 10 million individuals each quarter. Each month, Equifax receives individuals’ addresses, along with reports of debt balances and payments, from creditors (mortgage lenders, credit card issuers, student loan servicers, etc.). An algorithm maintained by Equifax considers all of the addresses reported for an individual and identifies the individual’s most likely current address. Equifax anonymizes the data before they are added to the CCP, removing names, addresses, and Social Security numbers (SSNs). In lieu of mailing addresses, the census block of the address is added to the CCP. Equifax creates a unique, anonymous identifier to enable researchers to build individuals’ panels. The panel nature of the data allows us to observe when someone has migrated and is living in a census block different from the one they lived in at the end of the preceding quarter. For more details about the CCP and its use in measuring migration, see Lee and Van der Klaauw (2010) and DeWaard, Johnson and Whitaker (2019). DefinitionsMetropolitan areaThe metropolitan areas in these data are combined statistical areas. This is the most aggregate definition of metro areas, and it combines Washington DC with Baltimore, San Jose with San Francisco, Akron with Cleveland, etc. Metro areas are combinations of counties that are tightly linked by worker commutes and other economic activity. All counties outside of metropolitan areas are tracked as parts of a rural commuting zone (CZ). CZs are also groups of counties linked by commuting, but CZ definitions cover all counties, both metropolitan and non-metropolitan. High-cost metropolitan areasHigh-cost metro areas are those where the median list price for a house was more than $200 per square foot on average between April 2017 and April 2022. These areas include San Francisco-San Jose, New York, San Diego, Los Angeles, Seattle, Boston, Miami, Sacramento, Denver, Salt Lake City, Portland, and Washington-Baltimore. Other Types of RegionsMetro areas with populations above 2 million and house price averages below $200 per square foot are categorized as affordable, large metros. Metro areas with populations between 500,000 and 2 million are categorized as mid-sized metros, regardless of house prices. All remaining counties are in the small metro and rural category.To obtain a metro area's total net migration, sum the four net migration values for the the four types of regions.Urban neighborhoodCensus tracts are designated as urban if they have a population density above 7,000 people per square mile. High density neighborhoods can support walkable retail districts and high-frequency public transportation. They are more likely to have the “street life” that people associate with living in an urban rather than a suburban area. The threshold of 7,000 people per square mile was selected because it was the average density in the largest US cities in the 1930 census. Before World War II, workplaces, shopping, schools and parks had to be accessible on foot. Tracts are also designated as urban if more than half of their housing units were built before WWII and they have a population density above 2,000 people per square mile. The lower population density threshold for the pre-war neighborhoods recognizes that many urban tracts have lost population since the 1960s. While the street grids usually remain, the area also needs su

Description

This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.

Key Features

• Country: Name of the country.
• Density (P/Km2): Population density measured in persons per square kilometer.
• Abbreviation: Abbreviation or code representing the country.
• Agricultural Land (%): Percentage of land area used for agricultural purposes.
• Land Area (Km2): Total land area of the country in square kilometers.
• Armed Forces Size: Size of the armed forces in the country.
• Birth Rate: Number of births per 1,000 population per year.
• Calling Code: International calling code for the country.
• Capital/Major City: Name of the capital or major city.
• CO2 Emissions: Carbon dioxide emissions in tons.
• CPI: Consumer Price Index, a measure of inflation and purchasing power.
• CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
• Currency_Code: Currency code used in the country.
• Fertility Rate: Average number of children born to a woman during her lifetime.
• Forested Area (%): Percentage of land area covered by forests.
• Gasoline_Price: Price of gasoline per liter in local currency.
• GDP: Gross Domestic Product, the total value of goods and services produced in the country.
• Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
• Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
• Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
• Largest City: Name of the country's largest city.
• Life Expectancy: Average number of years a newborn is expected to live.
• Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
• Minimum Wage: Minimum wage level in local currency.
• Official Language: Official language(s) spoken in the country.
• Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
• Physicians per Thousand: Number of physicians per thousand people.
• Population: Total population of the country.
• Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
• Tax Revenue (%): Tax revenue as a percentage of GDP.
• Total Tax Rate: Overall tax burden as a percentage of commercial profits.
• Unemployment Rate: Percentage of the labor force that is unemployed.
• Urban Population: Percentage of the population living in urban areas.
• Latitude: Latitude coordinate of the country's location.
• Longitude: Longitude coordinate of the country's location.

Potential Use Cases

• Analyze population density and land area to study spatial distribution patterns.
• Investigate the relationship between agricultural land and food security.
• Examine carbon dioxide emissions and their impact on climate change.
• Explore correlations between economic indicators such as GDP and various socio-economic factors.
• Investigate educational enrollment rates and their implications for human capital development.
• Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
• Study labor market dynamics through indicators such as labor force participation and unemployment rates.
• Investigate the role of taxation and its impact on economic development.
• Explore urbanization trends and their social and environmental consequences.

Important Note: This item is in mature support as of June 2023 and will retire in December 2025. A new version of this item is available for your use.The layers going from 1:1 to 1:1.5M present the 2010 Census Urbanized Areas (UA) and Urban Clusters (UC). A UA consists of contiguous, densely settled census block groups (BGs) and census blocks that meet minimum population density requirements (1000 people per square mile (ppsm) / 500 ppsm), along with adjacent densely settled census blocks that together encompass a population of at least 50,000 people. A UC consists of contiguous, densely settled census BGs and census blocks that meet minimum population density requirements, along with adjacent densely settled census blocks that together encompass a population of at least 2,500 people, but fewer than 50,000 people. The dataset covers the 50 States plus the District of Columbia within United States. The layer going over 1:1.5M presents the urban areas in the United States derived from the urban areas layer of the Digital Chart of the World (DCW). It provides information about the locations, names, and populations of urbanized areas for conducting geographic analysis on national and large regional scales. To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to USA Census Urban Areas.

Data Usage Notice

This version is not recommended for download. Please check the newest version.

We would like to inform you that the updated GlobPOP dataset (2021-2022) have been available in version 2.0. The GlobPOP dataset (2021-2022) in the current version is not recommended for your work. The GlobPOP dataset (1990-2020) in the current version is the same as version 1.0.

Thank you for your continued support of the GlobPOP.

If you encounter any issues, please contact us via email at lulingliu@mail.bnu.edu.cn.

Introduction

Continuously monitoring global population spatial dynamics is essential for implementing effective policies related to sustainable development, such as epidemiology, urban planning, and global inequality.

Here, we present GlobPOP, a new continuous global gridded population product with a high-precision spatial resolution of 30 arcseconds from 1990 to 2020. Our data-fusion framework is based on cluster analysis and statistical learning approaches, which intends to fuse the existing five products(Global Human Settlements Layer Population (GHS-POP), Global Rural Urban Mapping Project (GRUMP), Gridded Population of the World Version 4 (GPWv4), LandScan Population datasets and WorldPop datasets to a new continuous global gridded population (GlobPOP). The spatial validation results demonstrate that the GlobPOP dataset is highly accurate. To validate the temporal accuracy of GlobPOP at the country level, we have developed an interactive web application, accessible at https://globpop.shinyapps.io/GlobPOP/, where data users can explore the country-level population time-series curves of interest and compare them with census data.

With the availability of GlobPOP dataset in both population count and population density formats, researchers and policymakers can leverage our dataset to conduct time-series analysis of population and explore the spatial patterns of population development at various scales, ranging from national to city level.

Data description

The product is produced in 30 arc-seconds resolution(approximately 1km in equator) and is made available in GeoTIFF format. There are two population formats, one is the 'Count'(Population count per grid) and another is the 'Density'(Population count per square kilometer each grid)

Each GeoTIFF filename has 5 fields that are separated by an underscore "_". A filename extension follows these fields. The fields are described below with the example filename:

GlobPOP_Count_30arc_1990_I32

Field 1: GlobPOP(Global gridded population)
Field 2: Pixel unit is population "Count" or population "Density"
Field 3: Spatial resolution is 30 arc seconds
Field 4: Year "1990"
Field 5: Data type is I32(Int 32) or F32(Float32)

More information

Please refer to the paper for detailed information:

Liu, L., Cao, X., Li, S. et al. A 31-year (1990–2020) global gridded population dataset generated by cluster analysis and statistical learning. Sci Data 11, 124 (2024). https://doi.org/10.1038/s41597-024-02913-0.

The fully reproducible codes are publicly available at GitHub: https://github.com/lulingliu/GlobPOP.

A population is a subgroup of individuals within the same species that are living and breeding within a geographic area. The number of individuals living within that specific location determines the population density, or the number of individuals divided by the size of the area.Population density can be used to describe the location, growth, and migration of many organisms. In the case of humans, population density is often discussed in relation to urbanization, immigration, and population demographics.Globally, statistics related to population density are tracked by the United Nations Statistics Division, and the United States Constitution requires population data to be collected every 10 years, an operation carried out by the U.S. Census Bureau. However, data on human population density at the country level, and even at regional levels, may not be very informative; society tends to form clusters that can be surrounded by sparsely inhabited areas. Therefore, the most useful data describes smaller, more discrete population centers.Dense population clusters generally coincide with geographical locations often referred to as city, or as an urban or metropolitan area; sparsely populated areas are often referred to as rural. These terms do not have globally agreed upon definitions, but they are useful in general discussions about population density and geographic location.Population density data can be important for many related studies, including studies of ecosystems and improvements to human health and infrastructure. For example, the World Health Organization, the U.S. Energy Information Administration, the U.S. Global Change Research Program, and the U.S. Departments of Energy and Agriculture all use population data from the U.S. Census or UN statistics to understand and better predict resource use and health trends.Key areas of study include the following:Ecology: how increasing population density in certain areas impacts biodiversity and use of natural resources.Epidemiology: how densely populated areas differ with respect to incidence, prevalence, and transmission of infectious disease.Infrastructure: how population density drives specific requirements for energy use and the transport of goods.This list is not inclusive—the way society structures its living spaces affects many other fields of study as well. Scientists have even studied how happiness correlates with population density. A substantial area of study, however, focuses on demographics of populations as they relate to density. Areas of demographic breakdown and study include, but are not limited to:age (including tracking of elderly population centers);sex (biological classification as male or female); andrace and ethnic group, or cultural characteristics (ethnic origin and language use).

As of 2023, the top five most densely populated cities in Latin America and the Caribbean were in Colombia. The capital, Bogotá, ranked first with over 18,241 inhabitants per square kilometer.

Understanding scaling relations of social and environmental attributes of urban systems is necessary for effectively managing cities. Urban scaling theory (UST) has assumed that population density scales positively with city size. We present a new global analysis using a publicly available database of 933 cities from 38 countries. Our results showed that (18/38) 47% of countries analyzed supported increasing density scaling (pop ~ area) with exponents ~⅚ as UST predicts. In contrast, 17 of 38 countries (~45%) exhibited density scalings statistically indistinguishable from constant population densities across cities of varying sizes. These results were generally consistent in years spanning four decades from 1975 to 2015. Importantly, density varies by an order of magnitude between regions and countries and decreases in more developed economies. Our results (i) point to how economic and regional differences may affect the scaling of density with city size and (ii) show how understanding country- and region-specific strategies could inform effective management of urban systems for biodiversity, public health, conservation and resiliency from local to global scales.200 word statement of contribution: Urban Scaling Theory (UST) is a general scaling framework that makes quantitative predictions for how many urban attributes spanning physical, biological and social dimensions scale with city size; thus, UST has great implications in guiding future city developments. A major assumption of UST is that larger cities become denser. We evaluated this assumption using a publicly available global dataset of 933 cities in 38 countries. Our scaling analysis of population size and area of cities revealed that while many countries analyzed showed increasing densities with city size, about 45% of countries showed constant densities across cities. These results question a key assumption of UST. Our results suggest policies and management strategies for biodiversity conservation, public health and sustainability of urban systems may need to be tailored to national and regional scaling relations to be effective.

Canada, with 3.33 people per square kilometre, has one of the lowest population densities in the world. In 2001, most of Canada's population of 30,007,094 lived within 200 kilometres of the United States (along Canada's south). In fact, the inhabitants of our three biggest cities -- Toronto, Montréal and Vancouver -- can drive to the border in less than two hours. Thousands of kilometres to the north, our polar region -- the Yukon, the Northwest Territories and Nunavut -- is relatively empty, embracing 41% of our land mass but only 0.3% of our population. An inset map shows in greater detail the Windsor-Québec Corridor where a high concentration of Canadians live.

Canada, with 3.33 people per square kilometre, has one of the lowest population densities in the world. In 2001, most of Canada's population of 30,007,094 lived within 200 kilometres of the United States (along Canada's south). In fact, the inhabitants of our three biggest cities -- Toronto, Montréal and Vancouver -- can drive to the border in less than two hours. Thousands of kilometres to the north, our polar region -- the Yukon, the Northwest Territories and Nunavut -- is relatively empty, embracing 41% of our land mass but only 0.3% of our population. An inset map shows in greater detail the Windsor-Québec Corridor where a high concentration of Canadians live.

This map is part of an interactive Story Map series about global change in the US.With the global human population expected to exceed 8 billion people by 2030, our species is already irreversibly changing the future of our planet. The US itself is expected to grow by 16.5% to over 360 million people, making it the third largest country in the world, behind India and China. This population increase isn’t distributed evenly - 81% of people will live in cities, urban, and suburban areas, which will continue to shape how resources are produced, transported, and consumed. The percent of foreign-born and second-generation immigrants in the US is also expected to rise in the future, contributing to an increasingly diverse population. Across the globe, immigration will likely account for significant population changes in the near future, as climate change fuels drought, crop failures, and political instability, creating climate refugees particularly among countries who do not have the infrastructure to mitigate or adapt to global change. Numbers aren’t the only thing that matter: people of different socioeconomic backgrounds use resources differently, both within and between countries.If the rest of the world used energy as intensely as the United States does, the world population would need more than 4 entire Earths to provide us with the resources to feed this rate consumption. This unfortunately means that even regions of the US that contribute less towards the problems of global change will still feel their impacts. To ensure a high quality of life for all citizens, we must address not only population growth, but also excess consumption of and reliance on resources across different regions. Geographic, population, and economic differences among regions can provide opportunities for success in the face of global change. Renewable energy sources have created entrepreneurial economic ventures, and communities have found environmental solutions through forming sustainable local food systems. Environmental justice movements are working now to ensure that all citizens have access to nature, recreational areas, and a healthy future for all.

Population of Urban Agglomerations with 300,000 Inhabitants or more in 2014, by city, 1950-2030 (thousands). Data for 1,692 cities contained in the Excel file.

Note: Each country has its own definition of what is 'urban' and therefore use exercise caution when comparing cities in different countries.

Data available from the United Nations, Department of Economic and Social Affairs, Population Division (2014). World Urbanization Prospects: The 2014 Revision, CD-ROM Edition.

Further detail of population estimates, land area, and population density for world urban areas with over 500,000 people (924 areas) is available with Demographia's World Urban Areas report (2014). Much of this data is based on the UN urban agglomerations, though a range of other sources are also used.

This statistic shows the largest urban settlements in the Netherlands in 2021. In 2021, around 1.13 million people lived in Amsterdam, making it the largest city in the Netherlands. Population of the Netherlands With the global financial crisis in 2008 as well as the Euro zone crisis, many countries in Europe suffered a great economic impact. In spite of the crisis, the Netherlands maintained a stable economy over the past decade. The country's unemployment rate, for example, has been kept at a relatively low level in comparison to other countries in Europe also affected by the economic crisis. In 2014, Spain had an unemployment rate of more than 25 percent. The Netherlands' population has also seen increases in growth in comparison to previous years, with the figures slowly decreasing since 2011. As a result of the increase in population, the degree of urbanization - which is the share of the population living in urban areas - has increased, while the size of the labor force in the Netherlands has been relatively stable over the past decade. The population density of inhabitants per square kilometer in the Netherlands has also increased. Large cities in the Netherlands have experienced the impact of the population density growth and increase in the size of the labor force first hand. Three cities in the Netherlands have over half a million residents (as can be seen above). Additionally, more and more visitors are coming to the kingdom: The number of tourists in the Netherlands has increased significantly since 2001, a change which has also impacted the country's metropolises. Due to its location and affordable accommodation prices, the country’s tourism industry is developing and the largest cities in the Netherlands are taking advantage of it.