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.
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 statistics shows a ranking of the metropolitan areas in the United States in 2013 with the highest population density. As of 2013, Los Angeles-Long Beach-Anaheim in California was ranked first with a population density of 1,046 inhabitants per square kilometer.
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This data set included population and expenditure breakdowns by LGA, demographic statistics, labor statistics and Socio Economis Indexes for Areas (SEIFA) LGA score and ranking per LGA.
Detailed descriptions of this data set include:
- LGA name
- LGA code
- Region
- Total Net Expenditure
- SEIFA DIS RANK State
- SEIFA DIS RANK Country
- SEIFA DIS RANK Metro
- SEIFA ADV DIS Score
- SEIFA ADV DIS RANK State
- SEIFA ADV DIS RANK Country
- SEIFA ADV DIS RANK Metro
- Adult population
- Adult population per venue
- EGM numbers per 1000 adults
- Expenditure per adult
- Workforce
- Unemployment
- Unemployment rate
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.
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California was the state with the highest resident population in the United States in 2024, with 39.43 million people. Wyoming had the lowest population with about 590,000 residents. Living the American Dream Ever since the opening of the West in the United States, California has represented the American Dream for both Americans and immigrants to the U.S. The warm weather, appeal of Hollywood and Silicon Valley, as well as cities that stick in the imagination such as San Francisco and Los Angeles, help to encourage people to move to California. Californian demographics California is an extremely diverse state, as no one ethnicity is in the majority. Additionally, it has the highest percentage of foreign-born residents in the United States. By 2040, the population of California is expected to increase by almost 10 million residents, which goes to show that its appeal, both in reality and the imagination, is going nowhere fast.
This table presents the 2021 and 2016 population and dwelling counts, land area and population density for Canada, the provinces and the territories. It also shows the percentage change in the population and dwelling counts between 2016 and 2021.
U.S. Government Workshttps://www.usa.gov/government-works
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The Family Violence Prevention and Services Act of 1984 (FVPSA) provided funding, through the Office of Victims of Crime in the United States Department of Justice, for 23 law enforcement training projects across the nation from 1986 to 1992. FVPSA was enacted to assist states in (1) developing and maintaining programs for the prevention of family violence and for the provision of shelter to victims and their dependents and (2) providing training and technical assistance for personnel who provide services for victims of family violence. The National Institute of Justice awarded a grant to the Urban Institute in late 1992 to evaluate the police training projects. One of the program evaluation methods the Urban Institute used was to conduct surveys of victims in New York and Texas. The primary objectives of the survey were to find out, from victims who had contact with law enforcement officers in the pre-training period and/or in the post-training period, what their experiences and evaluations of law enforcement services were, how police interventions had changed over time, and how the quality of services and changes related to the police training funded under the FVPSA. Following the conclusion of training, victims of domestic assault in New York and Texas were surveyed through victim service programs across each state. Similar, but not identical, instruments were used at the two sites. Service providers were asked to distribute the questionnaires to victims of physical or sexual abuse who had contact with law enforcement officers. The survey instruments were developed to obtain information and victim perceptions of the following key subject areas: history of abuse, characteristics of the victim-abuser relationship, demographic characteristics of the abuser and the victim, history of law enforcement contacts, services received from law enforcement officers, and victims' evaluations of these services. Variables on history of abuse include types of abuse experienced, first and last time physically or sexually abused, and frequency of abuse. Characteristics of the victim-abuser relationship include length of involvement with the abuser, living arrangement and relationship status at time of last abuse, number of children the victim had, and number of children at home at the time of last abuse. Demographic variables provide age, race/ethnicity, employment status, and education level of the abuser and the victim. Variables on the history of law enforcement contacts and services received include number of times law enforcement officers were called because of assaults on the victim, number of times law enforcement officers actually came to the scene, first and last time officers came to the scene, number of times officers were involved because of assaults on the victim, number of times officers were involved in the last 12 months, and type of law enforcement agencies the officers were from. Data are also included on city size by population, city median household income, county population density, county crime rate, and region of state of the responding law enforcement agencies. Over 30 variables record the victims' evaluations of the officers' responsiveness, helpfulness, and attitudes.
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<ul style='margin-top:20px;'>
<li>India population density for 2021 was <strong>475.65</strong>, a <strong>0.83% increase</strong> from 2020.</li>
<li>India population density for 2020 was <strong>471.76</strong>, a <strong>0.98% increase</strong> from 2019.</li>
<li>India population density for 2019 was <strong>467.19</strong>, a <strong>1.05% increase</strong> from 2018.</li>
</ul>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.
In 2022, the union territory of Delhi had the highest urban population density of over 18 thousand persons per square kilometer. While the rural population density was highest in union territory of Puducherry, followed by the state of Bihar.
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This supporting document should allow one to recreate the analysis performed as part of “The optimal species richness environments for human populations, ” By Freeman et al. 2018 Submitted to PNAS July 2018. The annotated scripts in this directory (RichnessSIScripts.pdf) contain code to replicate the analysis, as well as code for additional analyses not included in the main paper or supplemental information. To replicate the analysis, one can either analyze the data files provided or build their own data set. As discussed in the main body of the text, we built three data sets following the procedures outlined by Tallavaara et al. (2017) for linking species richness values, net primary productivity and pathogen stress to each ethnographic case. We do not replicate the scripts provided by Tallavaara et al.(2017) as these are available, clear and should be cited when used.To replicate our analysis, one needs to set their working directory in R to the file location that contains the data files. There are 11 files that follow the naming convention “name.csv.” The 11 files are “MainFinal.csv”. “AGPOP3Eco.csv”, “HGFEM4R.csv”, “AGPOPClass.csv”, “CountryMeansEco2.csv”, “AGPOP3EcoH.csv”, “AGPOP3EcoL.csv”, “HiHG.csv”, “LowHG,csv”, “CountryMeansEco2H.csv”, and “CountryMeansEco2L.csv”. The first five files are the main files, the second six files are divided into high and low species richness environments by economy type for convenience. In each file, the variables are defined as follows:
1. Group/Country–name of the ethnographic society of country
2. Latitude–the latitude at the geographic center of a group’s territory or a country’s territory.
3. Longitude–the longitude at the geographic center of a group’s territory or a country’s territory.
4. Class–an ordinal ranking of wealth and status differentiation among the hunter-gatherer and agriculturalists societies (see main text for more details)
5. Class2–an binary ranking of wealth and status differentiation among the hunter-gatherer and agriculturalists societies (see main text for more details).
6. ECI–The average economic complexity index since 1973 as measured among modern countries.
7. DENSITY–Population density in people per square kilometer. This is a point in time estimatefor hunter-gatherer and agricultural groups and an average density since 1973 among nation states.
8. LnDENSITY–The natural log of population density
9. npp–net primary productivity estimated at the center of each group’s territory
10. npp2-Net primary productivity squared
11. biodiv–Standardized estimate of species richness at the center of each group’s range.
12. biodiv2–Species richness *100 ad squared.
13. pathos–Index of pathogen stress at the center of a group’s territory.
14. DivDiff–The absolute value of species richness-the species richness value of peak population density (values identified in Fig. 2 of the main manuscript).1
5. ID–A nominal variable that denotes economy type. HG=hunter-gatherer, AG=subsistence agriculturalist, IND=modern nation state
Tallavaara, M., J. T. Eronen, and M. Luoto2017. Supporting data and script for ”productivity, biodiversity, and pathogens influence the global hunter-gatherer population density” (Tallavaara et al. pnas 2018).https://doi.org/10.5281/zenodo.1167852
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This map shows four of these densely populated areas are in California. The San Francisco-Oakland and San Jose Urban Areas rank second and third, respectively. That the New York Metropolitan area ranks fifth on this list shows that this density ranking is greatly affected by the nature of the land area designated as urban. Census Urban Areas comprise an urban core and associated suburbs. California's urban and suburban areas are more uniform in density when compared to New York's urban core and suburban periphery which have vastly different densities. Delano ranks fourth because it has a very small land area and its population is augmented by two large California State Prisons housing 10,000 inmates.
This is a MD iMAP hosted service. Find more information on http://imap.maryland.gov. Coastal storm and flood events may increase the likelihood of danger or damage to life and property as a consequence of inundation and shoreline erosion. These hazards are caused by storms and exacerbated by sea level rise. The Community Flood Risk Areas represent residential areas at risk to coastal flooding where populations may be less equipped to prepare for - respond to - or recover from a coastal hazard event. Risk Areas are ranked from 1 to 5 to indicate relative risk - with 1 indicating very low risk and 5 indicating very high risk. Risk rankings incorporate population density - social parameters (i.e. age - income - language proficiency) - and probability of exposure to a flood hazard event in any one given year. 2013 US Census Bureau American Community Survey - 2010 Maryland Department of Planning land use land cover - and effective FEMA floodplain data as of December 2015 were used to identify and rank risk areas. Last Updated: 3/31/2016Feature Service Link: https://mdgeodata.md.gov/imap/rest/services/Environment/MD_CoastalResiliencyAssessment/FeatureServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.
This table presents the 2021 and 2016 population and dwelling counts, land area, population density and population ranking for census metropolitan areas or census agglomerations. It also shows the percentage change in the population and dwelling counts between 2016 and 2021.
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Data sources: World Health Organization [5]; World Health Organization [6]; Mullan et al. [7]; Foundation for Advancement of International Medical Education and Research [8]; University of Copenhagen and World Health Organization [9]; Redi-Med Data [10]; United States Census Bureau [11].aCirca 1970, 1969–1976; circa 2010, 2003–2012.
https://www.icpsr.umich.edu/web/ICPSR/studies/38528/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38528/terms
These datasets contain measures of socioeconomic and demographic characteristics by U.S. census tract for the years 1990-2022 and ZIP code tabulation area (ZCTA) for the years 2008-2022. Example measures include population density; population distribution by race, ethnicity, age, and income; income inequality by race and ethnicity; and proportion of population living below the poverty level, receiving public assistance, and female-headed or single parent families with kids. The datasets also contain a set of theoretically derived measures capturing neighborhood socioeconomic disadvantage and affluence, as well as a neighborhood index of Hispanic, foreign born, and limited English.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
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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).
https://www.maine-demographics.com/terms_and_conditionshttps://www.maine-demographics.com/terms_and_conditions
A dataset listing Maine cities by population for 2024.
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.