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.

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.

This raster dataset represents 2020 population density from the Gridded Population of the World, Version 4 (GPWv4) dataset, sourced from the Center for International Earth Science Information Network (CIESIN). The data has been clipped to the Northeast USA and normalized to a 0-100 scale to facilitate comparison between population distribution and recreational use of forests. This raster helps identify spatial outliers, where forest recreation is high in areas with low population density, offering insights for land management and conservation planning.Data Source:GPWv4 Population Density, 2020 Revision 11Clipped to the Northeast (ME, NH, VT, NY, MA, CT, RI, PA, NJ)Use Case:Used to compare forest recreation hotspots with population density, revealing areas where recreation is disproportionate to local population, assisting in identifying outliers for focused study or management efforts.

Our Population Density Grid Dataset for Northern Europe offers detailed, grid-based insights into the distribution of population across cities, towns, and rural areas. Free to explore and visualize, this dataset provides an invaluable resource for businesses and researchers looking to understand demographic patterns and optimize their location-based strategies.

By creating an account, you gain access to advanced tools for leveraging this data in geomarketing applications. Perfect for OOH advertising, retail planning, and more, our platform allows you to integrate population insights with your business intelligence, enabling you to make data-driven decisions for your marketing and expansion strategies.

The population density in France is unevenly distributed. The country, which enjoys a great variety of regions and landscapes, is becoming more and more urbanized, and big cities concentrate economic activities. Ile-de-France and overseas regions: the most densely populated French regions In 2022, Ile-de-France was the French region with the highest population density. According to the source, there were ******* residents per square kilometer in Ile-de-France. In 2025, more than ***** million people lived in this region, which contains the city of Paris and its greater suburbs. The overseas regions, such as Guadeloupe, Reunion, and Martinique, are the most densely populated French regions after the Paris region. On the other hand, Corsica was the least densely populated region in metropolitan France. However, it is Guyane, the largest overseas department, which has the lowest density in France, with only *** inhabitants per square kilometre. Largely covered by the Amazon jungle, this French territory is almost entirely populated along the coasts. The overall population density in metropolitan France reached ****** inhabitants per square kilometer in 2021, compared to ****** in 2007. Ile-de-France, and particularly Paris, is the center of most of the economic, political, and social activities in France. For instance, the ten most visited national French museums and galleries in 2017 were all located in Paris. In 2014, Ile-de-France was the French region that had the highest expenditure on Research and Development (19 billion euros). Regions in France Hauts-de-France, in the northern part of the country, and Provence-Alpes-Côte d’Azur in the southeastern part, were the second and the third most densely populated regions in Metropolitan France. The French southeastern coast is known for being highly urbanized, while its living conditions (sun, Mediterranean sea…) make it one of the most attractive regions to work and live in France. Hauts-de-France, which used to be one of the leading industrial regions of the country, now benefits from its geographical proximity to the heart of Europe: Brussels. Furthermore, rural regions like Centre-Val de Loire or Bourgogne Franche-Comté are less populous, and the share of the rural population in France is decreasing for years now.

Population density (people per sq. km of land area) in Northern Mariana Islands was reported at 98.14 sq. Km in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Northern Mariana Islands - Population density (people per sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

As of 2024, the population density in London was by far the highest number of people per square km in the UK, at *****. Of the other regions and countries which constitute the United Kingdom, North West England was the next most densely populated area at *** people per square kilometer. Scotland, by contrast, is the most sparsely populated country or region in the United Kingdom, with only ** people per square kilometer. Countries, regions, and cities According to the official mid-year population estimate, the population of the United Kingdom was just almost **** million in 2022. Most of the population lived in England, where an estimated **** million people resided, followed by Scotland at **** million, Wales at **** million and finally Northern Ireland at just over *** million. Within England, the South East was the region with the highest population at almost **** million, followed by the London region at around *** million. In terms of urban areas, Greater London is the largest city in the United Kingdom, followed by Greater Manchester and Birmingham in the North West and West Midlands regions of England. London calling London's huge size in relation to other UK cities is also reflected by its economic performance. In 2021, London's GDP was approximately *** billion British pounds, almost a quarter of UK GDP overall. In terms of GDP per capita, Londoners had a GDP per head of ****** pounds, compared with an average of ****** for the country as a whole. Productivity, expressed as by output per hour worked, was also far higher in London than the rest of the country. In 2021, London was around **** percent more productive than the rest of the country, with South East England the only other region where productivity was higher than the national average.

Niger NE: Population Density: People per Square Km data was reported at 16.955 Person/sq km in 2017. This records an increase from the previous number of 16.320 Person/sq km for 2016. Niger NE: Population Density: People per Square Km data is updated yearly, averaging 6.133 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 16.955 Person/sq km in 2017 and a record low of 2.752 Person/sq km in 1961. Niger NE: 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 Niger – Table NE.World Bank: 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;

As of 2025, Asia was the most densely populated region of the world, with nearly 156 inhabitants per square kilometer, whereas Oceania's population density was just over five inhabitants per square kilometer.

Studying the spatial relationship and driving forces between grain production and economic development in China can assist in the coordinated development of economic growth and grain production in both China and other developing countries. Based on panel data from 2000 to 2019 covering 2018 county-level units in China, this study comprehensively investigated the spatial distribution, spatial differences, dynamic evolution of distribution, and driving factors of China’s county-level spatial deviation index of grain and economy (SDIGE) using methods such as the standard deviation ellipse method, the three-stage nested decomposition of Theil index, kernel density estimation, and geographically weighted regression (GWR) model. The results show that (1) from 2000 to 2019, China’s SDIGE showed a development trend of "up—down—up," and the highest SDIGE was in the northeast region, the lowest in the east region, and the spatial pattern of "high in the northeast—low in the east coast" was increasingly prominent. (2) In terms of spatial difference, the overall difference of SDIGE in China from 2000 to 2019 showed a rising trend of development; The average contribution rate of the regional difference to the overall difference was the lowest, maintained at about 17.82%; The average contribution rate of intra city and inter-county differences to the overall difference is the highest, which is about 34.20%. (3) In terms of the driving force, the level of economic development hurts SDIGE, while population density, industrial structure, fiscal decentralisation, and terrain fluctuation have a positive and negative impact on SDIGE. To alleviate the imbalance between China’s economic development and grain production, it is necessary to implement differentiated policy measures tailored to the specific characteristics of different regions to assist agricultural producers and enhance the stability of grain production.

Vietnam Population Density: Northern Midlands and Mountain Areas (NM) data was reported at 138.300 Person/sq km in 2023. This records an increase from the previous number of 137.000 Person/sq km for 2022. Vietnam Population Density: Northern Midlands and Mountain Areas (NM) data is updated yearly, averaging 128.400 Person/sq km from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 138.300 Person/sq km in 2023 and a record low of 118.700 Person/sq km in 2011. Vietnam Population Density: Northern Midlands and Mountain Areas (NM) data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G003: Population Density: By Provinces.

National and subnational mid-year population estimates for the UK and its constituent countries by administrative area, age and sex (including components of population change, median age and population density).

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.

This population dataset complements 13 other datasets as part of a study that compared ancient settlement patterns with modern environmental conditions in the Jazira region of Syria. This study examined settlement distribution and density patterns over the past five millennia using archaeological survey reports and French 1930s 1:200,000 scale maps to locate and map archaeological sites. An archaeological site dataset was created and compared to and modelled with soil, geology, terrain (contour), surface and subsurface hydrology and normal and dry year precipitation pattern datasets; there are also three spreadsheet datasets providing 1963 precipitation and temperature readings collected at three locations in the region. The environmental datasets were created to account for ancient and modern population subsistence activities, which comprise barley and wheat farming and livestock grazing. These environmental datasets were subsequently modelled with the archaeological site dataset, as well as, land use and population density datasets for the Jazira region. Ancient trade routes were also mapped and factored into the model, and a comparison was made to ascertain if there was a correlation between ancient and modern settlement patterns and environmental conditions; the latter influencing subsistence activities. Creation of this population dataset, derived from a 1961 census, was created to compare modern population density patterns with the distribution of ancient settlement patterns to ascertain if patterns are shared. There is a similarity between these patterns with higher concentrations of settlements and population along the banks of rivers until reaching the northern area of the Jazira where both extend across the wider landscape and away from rivers. Derived from 1:1 million scale map produced for the following report: Food and Agriculture Organization (FAO), United Nations. Etude des Ressources en Eaux Souterraines de la Jezireh Syrienne. Rome: FAO, 1966.Population map was copied to mylar and scanned to create a polygon coverage of the soil classes, which include land-use attribute information. Each polygon was labelled and attributed with population count. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-07-05 and migrated to Edinburgh DataShare on 2017-02-21.

The population density picture of Boston is generally a story of two Bostons: the high density central and northern neighborhoods, and the low density southern neighborhoods.The highest density areas of Boston are particularly concentrated in Brighton, Allston, and the Fenway area, areas of the city with large numbers of college students and young adults. There is also high population density in areas such as the Back Bay, the South End, Charlestown, the North End, and South Boston. These are all relatively small areas geographically, but have housing stock conducive to population density (e.g. multi-family dwelling units, row housing, large apartment buildings). The southern neighborhoods, specifically Hyde Park and West Roxbury, have significant numbers of people living in them, but lots sizes tend to be much larger. These areas of the city also tend to have more single family dwelling units. In that, there are fewer people per square mile than places north in the city. 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, areas of highest density exceed 30,000 persons per square kilometer. 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.How to make this map for your city

Social vulnerability is defined as the disproportionate susceptibility of some social groups to the impacts of hazards, including death, injury, loss, or disruption of livelihood. In this dataset from Climate Ready Boston, groups identified as being more vulnerable are older adults, children, people of color, people with limited English proficiency, people with low or no incomes, people with disabilities, and people with medical illnesses. Source:The analysis and definitions used in Climate Ready Boston (2016) are based on "A framework to understand the relationship between social factors that reduce resilience in cities: Application to the City of Boston." Published 2015 in the International Journal of Disaster Risk Reduction by Atyia Martin, Northeastern University.Population Definitions:Older Adults:Older adults (those over age 65) have physical vulnerabilities in a climate event; they suffer from higher rates of medical illness than the rest of the population and can have some functional limitations in an evacuation scenario, as well as when preparing for and recovering from a disaster. Furthermore, older adults are physically more vulnerable to the impacts of extreme heat. Beyond the physical risk, older adults are more likely to be socially isolated. Without an appropriate support network, an initially small risk could be exacerbated if an older adult is not able to get help.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for population over 65 years of age.Attribute label: OlderAdultChildren: Families with children require additional resources in a climate event. When school is cancelled, parents need alternative childcare options, which can mean missing work. Children are especially vulnerable to extreme heat and stress following a natural disaster.Data source: 2010 American Community Survey 5-year Estimates (ACS) data by census tract for population under 5 years of age.Attribute label: TotChildPeople of Color: People of color make up a majority (53 percent) of Boston’s population. People of color are more likely to fall into multiple vulnerable groups aswell. People of color statistically have lower levels of income and higher levels of poverty than the population at large. People of color, many of whom also have limited English proficiency, may not have ready access in their primary language to information about the dangers of extreme heat or about cooling center resources. This risk to extreme heat can be compounded by the fact that people of color often live in more densely populated urban areas that are at higher risk for heat exposure due to the urban heat island effect.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract: Black, Native American, Asian, Island, Other, Multi, Non-white Hispanics.Attribute label: POC2Limited English Proficiency: Without adequate English skills, residents can miss crucial information on how to preparefor hazards. Cultural practices for information sharing, for example, may focus on word-of-mouth communication. In a flood event, residents can also face challenges communicating with emergency response personnel. If residents are more sociallyisolated, they may be less likely to hear about upcoming events. Finally, immigrants, especially ones who are undocumented, may be reluctant to use government services out of fear of deportation or general distrust of the government or emergency personnel.Data Source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract, defined as speaks English only or speaks English “very well”.Attribute label: LEPLow to no Income: A lack of financial resources impacts a household’s ability to prepare for a disaster event and to support friends and neighborhoods. For example, residents without televisions, computers, or data-driven mobile phones may face challenges getting news about hazards or recovery resources. Renters may have trouble finding and paying deposits for replacement housing if their residence is impacted by flooding. Homeowners may be less able to afford insurance that will cover flood damage. Having low or no income can create difficulty evacuating in a disaster event because of a higher reliance on public transportation. If unable to evacuate, residents may be more at risk without supplies to stay in their homes for an extended period of time. Low- and no-income residents can also be more vulnerable to hot weather if running air conditioning or fans puts utility costs out of reach.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for low-to- no income populations. The data represents a calculated field that combines people who were 100% below the poverty level and those who were 100–149% of the poverty level.Attribute label: Low_to_NoPeople with Disabilities: People with disabilities are among the most vulnerable in an emergency; they sustain disproportionate rates of illness, injury, and death in disaster events.46 People with disabilities can find it difficult to adequately prepare for a disaster event, including moving to a safer place. They are more likely to be left behind or abandoned during evacuations. Rescue and relief resources—like emergency transportation or shelters, for example— may not be universally accessible. Research has revealed a historic pattern of discrimination against people with disabilities in times of resource scarcity, like after a major storm and flood.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for total civilian non-institutionalized population, including: hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty. Attribute label: TotDisMedical Illness: Symptoms of existing medical illnesses are often exacerbated by hot temperatures. For example, heat can trigger asthma attacks or increase already high blood pressure due to the stress of high temperatures put on the body. Climate events can interrupt access to normal sources of healthcare and even life-sustaining medication. Special planning is required for people experiencing medical illness. For example, people dependent on dialysis will have different evacuation and care needs than other Boston residents in a climate event.Data source: Medical illness is a proxy measure which is based on EASI data accessed through Simply Map. Health data at the local level in Massachusetts is not available beyond zip codes. EASI modeled the health statistics for the U.S. population based upon age, sex, and race probabilities using U.S. Census Bureau data. The probabilities are modeled against the census and current year and five year forecasts. Medical illness is the sum of asthma in children, asthma in adults, heart disease, emphysema, bronchitis, cancer, diabetes, kidney disease, and liver disease. A limitation is that these numbers may be over-counted as the result of people potentially having more than one medical illness. Therefore, the analysis may have greater numbers of people with medical illness within census tracts than actually present. Overall, the analysis was based on the relationship between social factors.Attribute label: MedIllnesOther attribute definitions:GEOID10: Geographic identifier: State Code (25), Country Code (025), 2010 Census TractAREA_SQFT: Tract area (in square feet)AREA_ACRES: Tract area (in acres)POP100_RE: Tract population countHU100_RE: Tract housing unit countName: Boston Neighborhood

Vietnam Population Density: Northern Central & Central Coastal Area (NC) data was reported at 216.700 Person/sq km in 2023. This records an increase from the previous number of 216.000 Person/sq km for 2022. Vietnam Population Density: Northern Central & Central Coastal Area (NC) data is updated yearly, averaging 208.100 Person/sq km from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 216.700 Person/sq km in 2023 and a record low of 199.500 Person/sq km in 2011. Vietnam Population Density: Northern Central & Central Coastal Area (NC) data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G003: Population Density: By Provinces.

A population ecumene is the area of inhabited lands or settled areas generally delimited by a minimum population density. This ecumene shows the areas of the densest and most extended population within census divisions. Census divisions are the provincially legislated areas (such as county, municipalité régionale de comté, and regional district) or their equivalents. Census divisions are intermediate geographic areas between the province or territory level and the municipality (census subdivision). For further information, consult the Statistics Canada’s 2016 Illustrated Glossary (see below under Data Resources). The assemblage of dissemination area population density data from the 2016 Census of Population are used to form the ecumene within census divisions. Areas included in the ecumene are dissemination areas where the population density is greater than or equal to 0.4 persons per square kilometre or about one person per square mile. In some areas to capture more population within the ecumene the criteria was extended to 0.2 persons per square kilometre. The ecumene areas were generalized in certain areas to enhance the size of some isolated ecumene areas in northern Canada. This map can be used as an “ecumene” overlay to differentiate the sparsely populated areas from the ecumene in conjunction with census division data or other small-scale maps. This ecumene shows a more meaningful distribution of the population for Canada.

The 2015 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the "urban footprint." There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2010.

Historical dataset showing Northern Mariana Islands population density by year from 1991 to 2022.