100+ datasets found
  1. Cities with the highest population density globally 2025

    • statista.com
    Updated Nov 28, 2025
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    Statista (2025). Cities with the highest population density globally 2025 [Dataset]. https://www.statista.com/statistics/1237290/cities-highest-population-density/
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    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    World
    Description

    Mogadishu in Somalia led the ranking of cities with the highest population density in 2025, with ****** residents per square kilometer. When it comes to countries, Monaco is the most densely populated state worldwide.

  2. Highest population density by country 2024

    • statista.com
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    Statista, Highest population density by country 2024 [Dataset]. https://www.statista.com/statistics/264683/top-fifty-countries-with-the-highest-population-density/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    World
    Description

    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.

  3. List of World Cities by Population Density

    • kaggle.com
    zip
    Updated Apr 12, 2023
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    Raj Kumar Pandey (2023). List of World Cities by Population Density [Dataset]. https://www.kaggle.com/rajkumarpandey02/list-of-world-cities-by-population-density
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    zip(1947 bytes)Available download formats
    Dataset updated
    Apr 12, 2023
    Authors
    Raj Kumar Pandey
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    CONTENT

    This is a list of cities worldwide by population density. The population, population density and land area for the cities listed are based on the entire city proper, the defined boundary or border of a city or the city limits of the city. The population density of the cities listed is based on the average number of people living per square kilometer or per square mile. This list does not refer to the population, population density or land area of the greater metropolitan area or urban area, nor particular districts in any of the cities listed.

  4. Covid-19 Highest City Population Density

    • kaggle.com
    zip
    Updated Mar 25, 2020
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    lookfwd (2020). Covid-19 Highest City Population Density [Dataset]. https://www.kaggle.com/lookfwd/covid19highestcitypopulationdensity
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    zip(4685 bytes)Available download formats
    Dataset updated
    Mar 25, 2020
    Authors
    lookfwd
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    This is a dataset of the most highly populated city (if applicable) in a form easy to join with the COVID19 Global Forecasting (Week 1) dataset. You can see how to use it in this kernel

    Content

    There are four columns. The first two correspond to the columns from the original COVID19 Global Forecasting (Week 1) dataset. The other two is the highest population density, at city level, for the given country/state. Note that some countries are very small and in those cases the population density reflects the entire country. Since the original dataset has a few cruise ships as well, I've added them there.

    Acknowledgements

    Thanks a lot to Kaggle for this competition that gave me the opportunity to look closely at some data and understand this problem better.

    Inspiration

    Summary: I believe that the square root of the population density should relate to the logistic growth factor of the SIR model. I think the SEIR model isn't applicable due to any intervention being too late for a fast-spreading virus like this, especially in places with dense populations.

    After playing with the data provided in COVID19 Global Forecasting (Week 1) (and everything else online or media) a bit, one thing becomes clear. They have nothing to do with epidemiology. They reflect sociopolitical characteristics of a country/state and, more specifically, the reactivity and attitude towards testing.

    The testing method used (PCR tests) means that what we measure could potentially be a proxy for the number of people infected during the last 3 weeks, i.e the growth (with lag). It's not how many people have been infected and recovered. Antibody or serology tests would measure that, and by using them, we could go back to normality faster... but those will arrive too late. Way earlier, China will have experimentally shown that it's safe to go back to normal as soon as your number of newly infected per day is close to zero.

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F197482%2F429e0fdd7f1ce86eba882857ac7a735e%2Fcovid-summary.png?generation=1585072438685236&alt=media" alt="">

    My view, as a person living in NYC, about this virus, is that by the time governments react to media pressure, to lockdown or even test, it's too late. In dense areas, everyone susceptible has already amble opportunities to be infected. Especially for a virus with 5-14 days lag between infections and symptoms, a period during which hosts spread it all over on subway, the conditions are hopeless. Active populations have already been exposed, mostly asymptomatic and recovered. Sensitive/older populations are more self-isolated/careful in affluent societies (maybe this isn't the case in North Italy). As the virus finishes exploring the active population, it starts penetrating the more isolated ones. At this point in time, the first fatalities happen. Then testing starts. Then the media and the lockdown. Lockdown seems overly effective because it coincides with the tail of the disease spread. It helps slow down the virus exploring the long-tail of sensitive population, and we should all contribute by doing it, but it doesn't cause the end of the disease. If it did, then as soon as people were back in the streets (see China), there would be repeated outbreaks.

    Smart politicians will test a lot because it will make their condition look worse. It helps them demand more resources. At the same time, they will have a low rate of fatalities due to large denominator. They can take credit for managing well a disproportionally major crisis - in contrast to people who didn't test.

    We were lucky this time. We, Westerners, have woken up to the potential of a pandemic. I'm sure we will give further resources for prevention. Additionally, we will be more open-minded, helping politicians to have more direct responses. We will also require them to be more responsible in their messages and reactions.

  5. Population Density Around the Globe

    • covid19.esriuk.com
    • directrelief.hub.arcgis.com
    • +3more
    Updated Feb 14, 2015
    + more versions
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    Urban Observatory by Esri (2015). Population Density Around the Globe [Dataset]. https://covid19.esriuk.com/maps/fb393372ef8347b19491f3eb8c859a82
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    Dataset updated
    Feb 14, 2015
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

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

  6. V

    Vietnam Population Density: SE: Ho Chi Minh city

    • ceicdata.com
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    CEICdata.com, Vietnam Population Density: SE: Ho Chi Minh city [Dataset]. https://www.ceicdata.com/en/vietnam/population-density-by-provinces/population-density-se-ho-chi-minh-city
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    Vietnam
    Variables measured
    Population
    Description

    Vietnam Population Density: SE: Ho Chi Minh city data was reported at 4,513.100 Person/sq km in 2023. This records an increase from the previous number of 4,481.000 Person/sq km for 2022. Vietnam Population Density: SE: Ho Chi Minh city data is updated yearly, averaging 4,196.400 Person/sq km from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 4,513.100 Person/sq km in 2023 and a record low of 3,633.100 Person/sq km in 2011. Vietnam Population Density: SE: Ho Chi Minh city 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.

  7. Population density in the U.S. 2023, by state

    • statista.com
    • akomarchitects.com
    Updated Sep 21, 2024
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    Statista (2024). Population density in the U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/183588/population-density-in-the-federal-states-of-the-us/
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    Dataset updated
    Sep 21, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    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.

  8. G

    Population Density, 1996

    • open.canada.ca
    • datasets.ai
    • +1more
    jp2, zip
    Updated Mar 14, 2022
    + more versions
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    Natural Resources Canada (2022). Population Density, 1996 [Dataset]. https://open.canada.ca/data/dataset/e7ba9651-8893-11e0-8d01-6cf049291510
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    zip, jp2Available download formats
    Dataset updated
    Mar 14, 2022
    Dataset provided by
    Natural Resources Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    The majority of the Canadian population, about 60% is concentrated within a thin belt of land representing 2.2% of the land between Windsor, Ontario and Quebec City. Even though Canada is the second largest country in the world in terms of land area, it only ranks 33rd in terms of population. The agricultural areas in the Prairies and eastern Canada have higher population densities than the sparsely populated North, but not as high as southern Ontario or southern Quebec.

  9. P

    Philippines Population Density: NCR: City of Manila

    • ceicdata.com
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    CEICdata.com, Philippines Population Density: NCR: City of Manila [Dataset]. https://www.ceicdata.com/en/philippines/population-and-population-density-census/population-density-ncr-city-of-manila
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1975 - Dec 1, 2015
    Area covered
    Philippines
    Variables measured
    Population
    Description

    Philippines Population Density: NCR: City of Manila data was reported at 71,263.000 Person/sq km in 2015. This records an increase from the previous number of 66,140.000 Person/sq km for 2010. Philippines Population Density: NCR: City of Manila data is updated yearly, averaging 65,706.000 Person/sq km from Dec 1975 (Median) to 2015, with 8 observations. The data reached an all-time high of 71,263.000 Person/sq km in 2015 and a record low of 59,164.640 Person/sq km in 1975. Philippines Population Density: NCR: City of Manila data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G005: Population Density.

  10. Population density of the United States 2019

    • statista.com
    Updated Dec 15, 2019
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    Statista (2019). Population density of the United States 2019 [Dataset]. https://www.statista.com/statistics/183475/united-states-population-density/
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    Dataset updated
    Dec 15, 2019
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  11. GloGCI-World Ghost Cities Index Ranking

    • figshare.com
    • data.mendeley.com
    application/x-rar
    Updated Apr 9, 2025
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    Yecheng Zhang; Tangqi Tu; Ying Long (2025). GloGCI-World Ghost Cities Index Ranking [Dataset]. http://doi.org/10.6084/m9.figshare.28248038.v3
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    application/x-rarAvailable download formats
    Dataset updated
    Apr 9, 2025
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Yecheng Zhang; Tangqi Tu; Ying Long
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description

    Due to rapid urbanization over the past 20 years, many newly developed areas have lagged in socio-economic maturity, creating an imbalance with older cities and leading to the rise of "ghost cities". However, the complexity of socio-economic factors has hindered global studies from measuring this phenomenon. To address this gap, a unified framework based on urban vitality theory and multi-source data is proposed to measure the Ghost City Index (GCI), which has been validated using various data sources. The study encompasses 8,841 natural cities worldwide with areas exceeding 5 km², categorizing each into new urban areas (developed after 2005) and old urban areas (developed before 2005). Urban vitality was gauged using the density of road networks, points of interest (POIs), and population density with 1 km resolution across morphological, functional, and social dimensions. By comparing urban vitality in new and old urban areas, we quantify the GCI globally using the theory of urban vitality for the first time. The results reveal that the vitality of new urban areas is 7.69% that of old ones. The top 5% (442) of cities were designated as ghost cities, a finding mirrored by news media and other research. This study sheds light on strategies for sustainable global urbanization, crucial for the United Nations' Sustainable Development Goals.The code file gives the calculation process of data respectively, and the excel file gives the obtained data. For the explanation of the fields in “citypoint.shp”, please refer to the Supplementary Information of the paper (https://doi.org/10.1016/j.habitatint.2025.103350).Ref: Zhang, Y., Tu, T., & Long, Y. (2025). Inferring ghost cities on the globe in newly developed urban areas based on urban vitality with multi-source data. Habitat International, 158, 103350. https://doi.org/10.1016/j.habitatint.2025.103350

  12. Global Country Information Dataset 2023

    • kaggle.com
    zip
    Updated Jul 8, 2023
    + more versions
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    Nidula Elgiriyewithana ⚡ (2023). Global Country Information Dataset 2023 [Dataset]. https://www.kaggle.com/datasets/nelgiriyewithana/countries-of-the-world-2023
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    zip(24063 bytes)Available download formats
    Dataset updated
    Jul 8, 2023
    Authors
    Nidula Elgiriyewithana ⚡
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

    DOI

    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.

    Data Source: This dataset was compiled from multiple data sources

    If this was helpful, a vote is appreciated ❤️ Thank you 🙂

  13. f

    Florida Cities by Population

    • florida-demographics.com
    Updated Jun 20, 2024
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    Kristen Carney (2024). Florida Cities by Population [Dataset]. https://www.florida-demographics.com/cities_by_population
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    Dataset updated
    Jun 20, 2024
    Dataset provided by
    Cubit Planning, Inc.
    Authors
    Kristen Carney
    License

    https://www.florida-demographics.com/terms_and_conditionshttps://www.florida-demographics.com/terms_and_conditions

    Area covered
    Florida City, Florida
    Description

    A dataset listing Florida cities by population for 2024.

  14. A

    Australia AU: Population Density: People per Square Km

    • ceicdata.com
    + more versions
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    CEICdata.com, Australia AU: Population Density: People per Square Km [Dataset]. https://www.ceicdata.com/en/australia/population-and-urbanization-statistics/au-population-density-people-per-square-km
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    Australia
    Variables measured
    Population
    Description

    Australia Population Density: People per Square Km data was reported at 3.382 Person/sq km in 2022. This records an increase from the previous number of 3.339 Person/sq km for 2021. Australia Population Density: People per Square Km data is updated yearly, averaging 2.263 Person/sq km from Dec 1961 (Median) to 2022, with 62 observations. The data reached an all-time high of 3.382 Person/sq km in 2022 and a record low of 1.365 Person/sq km in 1961. Australia 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 Australia – Table AU.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.;Food and Agriculture Organization and World Bank population estimates.;Weighted average;

  15. World Population Live Dataset 2022

    • kaggle.com
    zip
    Updated Sep 10, 2022
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    Aman Chauhan (2022). World Population Live Dataset 2022 [Dataset]. https://www.kaggle.com/datasets/whenamancodes/world-population-live-dataset/code
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    zip(10169 bytes)Available download formats
    Dataset updated
    Sep 10, 2022
    Authors
    Aman Chauhan
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    World
    Description

    The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on earth, which far exceeds the world population of 7.2 billion from 2015. Our own estimate based on UN data shows the world's population surpassing 7.7 billion.

    China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, the country of India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.

    The next 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.

    Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.

    In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added each year.

    This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by the year 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

    Global life expectancy has also improved in recent years, increasing the overall population life expectancy at birth to just over 70 years of age. The projected global life expectancy is only expected to continue to improve - reaching nearly 77 years of age by the year 2050. Significant factors impacting the data on life expectancy include the projections of the ability to reduce AIDS/HIV impact, as well as reducing the rates of infectious and non-communicable diseases.

    Population aging has a massive impact on the ability of the population to maintain what is called a support ratio. One key finding from 2017 is that the majority of the world is going to face considerable growth in the 60 plus age bracket. This will put enormous strain on the younger age groups as the elderly population is becoming so vast without the number of births to maintain a healthy support ratio.

    Although the number given above seems very precise, it is important to remember that it is just an estimate. It simply isn't possible to be sure exactly how many people there are on the earth at any one time, and there are conflicting estimates of the global population in 2016.

    Some, including the UN, believe that a population of 7 billion was reached in October 2011. Others, including the US Census Bureau and World Bank, believe that the total population of the world reached 7 billion in 2012, around March or April.

    ColumnsDescription
    CCA33 Digit Country/Territories Code
    NameName of the Country/Territories
    2022Population of the Country/Territories in the year 2022.
    2020Population of the Country/Territories in the year 2020.
    2015Population of the Country/Territories in the year 2015.
    2010Population of the Country/Territories in the year 2010.
    2000Population of the Country/Territories in the year 2000.
    1990Population of the Country/Territories in the year 1990.
    1980Population of the Country/Territories in the year 1980.
    1970Population of the Country/Territories in the year 1970.
    Area (km²)Area size of the Country/Territories in square kilometer.
    Density (per km²)Population Density per square kilometer.
    Grow...
  16. GlobPOP: A 33-year (1990-2022) global gridded population dataset (Version...

    • zenodo.org
    tiff
    Updated Sep 4, 2024
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    Luling Liu; Xin Cao; Xin Cao; Shijie Li; Na Jie; Luling Liu; Shijie Li; Na Jie (2024). GlobPOP: A 33-year (1990-2022) global gridded population dataset (Version 2.0-test-alpha) [Dataset]. http://doi.org/10.5281/zenodo.11071249
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    tiffAvailable download formats
    Dataset updated
    Sep 4, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Luling Liu; Xin Cao; Xin Cao; Shijie Li; Na Jie; Luling Liu; Shijie Li; Na Jie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  17. P

    Philippines Population Density: NCR: City of Muntinlupa

    • ceicdata.com
    Updated Oct 15, 2025
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    CEICdata.com (2025). Philippines Population Density: NCR: City of Muntinlupa [Dataset]. https://www.ceicdata.com/en/philippines/population-and-population-density-census/population-density-ncr-city-of-muntinlupa
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    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1975 - Dec 1, 2015
    Area covered
    Philippines
    Variables measured
    Population
    Description

    Philippines Population Density: NCR: City of Muntinlupa data was reported at 12,692.000 Person/sq km in 2015. This records an increase from the previous number of 11,571.000 Person/sq km for 2010. Philippines Population Density: NCR: City of Muntinlupa data is updated yearly, averaging 9,800.500 Person/sq km from Dec 1975 (Median) to 2015, with 8 observations. The data reached an all-time high of 12,692.000 Person/sq km in 2015 and a record low of 2,375.955 Person/sq km in 1975. Philippines Population Density: NCR: City of Muntinlupa data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G005: Population Density.

  18. world_population

    • kaggle.com
    zip
    Updated Feb 8, 2023
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    farzam ajili (2023). world_population [Dataset]. https://www.kaggle.com/datasets/farzamajili/world-population
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    zip(16061 bytes)Available download formats
    Dataset updated
    Feb 8, 2023
    Authors
    farzam ajili
    Area covered
    World
    Description

    Context The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on earth, which far exceeds the world population of 7.2 billion in 2015. Our own estimate based on UN data shows the world's population surpassing 7.7 billion.

    China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, the country of India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.

    The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.

    Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.

    In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added each year.

    This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growing more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

    Content In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc.

  19. Bangladesh Population and GDP Growth Datasets

    • kaggle.com
    zip
    Updated May 26, 2022
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    Md. Rasel Meya (2022). Bangladesh Population and GDP Growth Datasets [Dataset]. https://www.kaggle.com/datasets/raselmeya/bangladesh-population-and-gdp-growth-datasets
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    zip(3092 bytes)Available download formats
    Dataset updated
    May 26, 2022
    Authors
    Md. Rasel Meya
    License

    Attribution-ShareAlike 3.0 (CC BY-SA 3.0)https://creativecommons.org/licenses/by-sa/3.0/
    License information was derived automatically

    Area covered
    Bangladesh
    Description

    Bangladesh is largely ethnically homogeneous, and its name derives from the Bengali ethno-linguistic group which comprises 98% of the population. The Chittagong Hill Tracts, Sylhet, Mymensingh and North Bengal divisions are home to diverse indigenous peoples. There are many dialects of Bengali spoken throughout the region. The dialect spoken by those in Chittagong and Sylhet are particularly distinctive. In 2013 the population was estimated at 160 million. About 87% of Bangladeshis are Muslims, followed by Hindus (12%), Buddhists (1%) and Christians (0.5%).

    Bangladesh has the highest population density in the world, excluding a handful of city-states and small countries with populations under 10m, such as Malta and Hong Kong.

    Most of the demographic statistics below are from the Bangladesh Bureau of Statistics, World Bank and CIA World Fackbook, unless otherwise indicated.

  20. u

    Population Density, 1996 - Catalogue - Canadian Urban Data Catalogue (CUDC)

    • data.urbandatacentre.ca
    Updated Oct 19, 2025
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    (2025). Population Density, 1996 - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-e7ba9651-8893-11e0-8d01-6cf049291510
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    Dataset updated
    Oct 19, 2025
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada
    Description

    The majority of the Canadian population, about 60% is concentrated within a thin belt of land representing 2.2% of the land between Windsor, Ontario and Quebec City. Even though Canada is the second largest country in the world in terms of land area, it only ranks 33rd in terms of population. The agricultural areas in the Prairies and eastern Canada have higher population densities than the sparsely populated North, but not as high as southern Ontario or southern Quebec.

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Statista (2025). Cities with the highest population density globally 2025 [Dataset]. https://www.statista.com/statistics/1237290/cities-highest-population-density/
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Cities with the highest population density globally 2025

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11 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Nov 28, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2025
Area covered
World
Description

Mogadishu in Somalia led the ranking of cities with the highest population density in 2025, with ****** residents per square kilometer. When it comes to countries, Monaco is the most densely populated state worldwide.

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