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

As of 2025, Tokyo-Yokohama in Japan was the largest world urban agglomeration, with 37 million people living there. Delhi ranked second with more than 34 million, with Shanghai in third with more than 30 million inhabitants.

A range of indicators for a selection of cities from the New York City Global City database.

Dataset includes the following:

Geography

City Area (km2)

Metro Area (km2)

People

City Population (millions)

Metro Population (millions)

Foreign Born

Annual Population Growth

Economy

GDP Per Capita (thousands $, PPP rates, per resident)

Primary Industry

Secondary Industry

Share of Global 500 Companies (%)

Unemployment Rate

Poverty Rate

Transportation

Public Transportation

Mass Transit Commuters

Major Airports

Major Ports

Education

Students Enrolled in Higher Education

Percent of Population with Higher Education (%)

Higher Education Institutions

Tourism

Total Tourists Annually (millions)

Foreign Tourists Annually (millions)

Domestic Tourists Annually (millions)

Annual Tourism Revenue ($US billions)

Hotel Rooms (thousands)

Health

Infant Mortality (Deaths per 1,000 Births)

Life Expectancy in Years (Male)

Life Expectancy in Years (Female)

Physicians per 100,000 People

Number of Hospitals

Anti-Smoking Legislation

Culture

Number of Museums

Number of Cultural and Arts Organizations

Environment

Green Spaces (km2)

Air Quality

Laws or Regulations to Improve Energy Efficiency

Retrofitted City Vehicle Fleet

Bike Share Program

This world cities layer presents the locations of many cities of the world, both major cities and many provincial capitals.Population estimates are provided for those cities listed in open source data from the United Nations and US Census.

World urban population for 2023 was 4,614,425,176, a 1.67% increase from 2022.

<ul style='margin-top:20px;'>

<li>World urban population for 2022 was <strong>4,538,431,007</strong>, a <strong>1.65% increase</strong> from 2021.</li>
<li>World urban population for 2021 was <strong>4,464,635,019</strong>, a <strong>1.57% increase</strong> from 2020.</li>
<li>World urban population for 2020 was <strong>4,395,641,624</strong>, a <strong>1.82% increase</strong> from 2019.</li>
</ul>Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.

The graph shows the proportion of the population in cities worldwide from 1985 to 2050. **** percent of the world's population lived in cities in the year of 2015. This percentage is forecasted to grow to **** percent in the year 2050.

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

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

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

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

The global urban population overtook the rural population in numbers in 2007. Today, 4.5 billion people live in urban areas, compared to 3.4 million in rural areas. This development underlines that rapid urbanization the world has seen in recent decades.

Population in the largest city (% of urban population) in World was reported at 16.08 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

The World Cities Culture Forum, established in 2012, is a leading global network of civic leaders from over 40 creative cities across six continents, representing a combined population of over 245 million. The forum fosters collaborations to place culture at the core of urban development, addressing 21st-century challenges such as climate change, affordable workspaces, cultural tourism, and diversity in public spaces. Through its Global Summit, partnerships, and programs like the Leadership Exchange Programme and Digital Dialogue Masterclasses, the forum promotes cultural integration in city planning. The World Cities Culture Report 2022 provides comprehensive open-source data on culture, including over 60 datasets from 40 cities. Contextual Data: Includes demographics such as characteristics of the overall and working-age populations (including percent who were foreign born) and of the geographical area, such as the percentage of national population living in the city and the percentage of the area devoted to parks and other public green spaces. Cultural Infrastructure: Provides counts (and rates) of various facilities and venues, including art galleries, artists' studios, rehearsal spaces, bars, bookshops, cinemas, community centers, concert halls, museums, nightclubs, libraries, video game arcades, and theatres. Participation and Tourism: Focuses on cultural participation metrics, such as cinema and theatre admissions, festival attendance, museum visits, average daily attendance at the top five art exhibits, and international tourist numbers. Creative Economy: Encompasses data on book publishing, creative industries employment, film festivals, restaurant ratings, and performances. Education: Includes statistics on public library book loans, higher education levels, international student enrollment, and specialist institutes in art and design education. The source for each number is identified within the dataset. Data users can freely download selected datasets as .csv files.

2007 marked the first year where more of the world's population lived in an urban setting than a rural setting. In 1960, roughly a third of the world lived in an urban setting; it is expected that this figure will reach two thirds by 2050. Urbanization is a fairly new phenomenon; for the vast majority of human history, fewer than five percent of the world lived in urban areas, due to the dependency on subsistence agriculture. Advancements in agricultural practices and technology then coincided with the beginning of the industrial revolution in Europe in the late 19th century, which resulted in waves of urbanization to meet the demands of emerging manufacturing industries. This trend was replicated across the rest of the world as it industrialized over the following two centuries, and the most significant increase coincided with the industrialization of the most populous countries in Asia. In more developed economies, urbanization remains high even as economies de-industrialize, due to a variety of factors such as housing availability, labor demands in service industries, and social trends.

World Cities provides a base map layer of the cities for the world. The cities include national capitals, provincial capitals, major population centers, and landmark cities.

United States US: Urban Population data was reported at 267,278,643.000 Person in 2017. This records an increase from the previous number of 264,746,567.000 Person for 2016. United States US: Urban Population data is updated yearly, averaging 184,283,180.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 267,278,643.000 Person in 2017 and a record low of 126,462,473.000 Person in 1960. United States US: Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Population and Urbanization Statistics. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Sum;

Hong Kong HK: Population in Largest City: as % of Urban Population data was reported at 99.637 % in 2017. This records an increase from the previous number of 99.540 % for 2016. Hong Kong HK: Population in Largest City: as % of Urban Population data is updated yearly, averaging 99.382 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 100.000 % in 2010 and a record low of 94.548 % in 1974. Hong Kong HK: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hong Kong – Table HK.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

The urban–rural continuum classifies the global population, allocating rural populations around differently-sized cities. The classification is based on four dimensions: population distribution, population density, urban center location, and travel time to urban centers, all of which can be mapped globally and consistently and then aggregated as administrative unit statistics.Using spatial data, we matched all rural locations to their urban center of reference based on the time needed to reach these urban centers. A hierarchy of urban centers by population size (largest to smallest) is used to determine which center is the point of “reference” for a given rural location: proximity to a larger center “dominates” over a smaller one in the same travel time category. This was done for 7 urban categories and then aggregated, for presentation purposes, into “large cities” (over 1 million people), “intermediate cities” (250,000 –1 million), and “small cities and towns” (20,000–250,000).Finally, to reflect the diversity of population density across the urban–rural continuum, we distinguished between high-density rural areas with over 1,500 inhabitants per km2 and lower density areas. Unlike traditional functional area approaches, our approach does not define urban catchment areas by using thresholds, such as proportion of people commuting; instead, these emerge endogenously from our urban hierarchy and by calculating the shortest travel time.Urban-Rural Catchment Areas (URCA).tif is a raster dataset of the 30 urban–rural continuum categories for the urban–rural continuum showing the catchment areas around cities and towns of different sizes. Each rural pixel is assigned to one defined travel time category: less than one hour, one to two hours, and two to three hours travel time to one of seven urban agglomeration sizes. The agglomerations range from large cities with i) populations greater than 5 million and ii) between 1 to 5 million; intermediate cities with iii) 500,000 to 1 million and iv) 250,000 to 500,000 inhabitants; small cities with populations v) between 100,000 and 250,000 and vi) between 50,000 and 100,000; and vii) towns of between 20,000 and 50,000 people. The remaining pixels that are more than 3 hours away from any urban agglomeration of at least 20,000 people are considered as either hinterland or dispersed towns being that they are not gravitating around any urban agglomeration. The raster also allows for visualizing a simplified continuum created by grouping the seven urban agglomerations into 4 categories.Urban-Rural Catchment Areas (URCA).tif is in GeoTIFF format, band interleaved with LZW compression, suitable for use in Geographic Information Systems and statistical packages. The data type is byte, with pixel values ranging from 1 to 30. The no data value is 128. It has a spatial resolution of 30 arc seconds, which is approximately 1km at the equator. The spatial reference system (projection) is EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long). The geographic extent is 83.6N - 60S / 180E - 180W. The same tif file is also available as an ESRI ArcMap MapPackage Urban-Rural Catchment Areas.mpkFurther details are in the ReadMe_data_description.docx

Urban population in World was reported at 4614425176 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Urban population - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

The Global Population Density Grid Time Series Estimates provide a back-cast time series of population density grids based on the year 2000 population grid from SEDAC's Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) data set. The grids were created by using rates of population change between decades from the coarser resolution History Database of the Global Environment (HYDE) database to back-cast the GRUMPv1 population density grids. Mismatches between the spatial extent of the HYDE calculated rates and GRUMPv1 population data were resolved via infilling rate cells based on a focal mean of values. Finally, the grids were adjusted so that the population totals for each country equaled the UN World Population Prospects (2008 Revision) estimates for that country for the respective year (1970, 1980, 1990, and 2000). These data do not represent census observations for the years prior to 2000, and therefore can at best be thought of as estimations of the populations in given locations. The population grids are consistent internally within the time series, but are not recommended for use in creating longer time series with any other population grids, including GRUMPv1, Gridded Population of the World, Version 4 (GPWv4), or non-SEDAC developed population grids. These population grids served as an input to SEDAC's Global Estimated Net Migration Grids by Decade: 1970-2000 data set.

Urban population (% of total population) in World was reported at 57.25 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Urban population (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

1. Global_1028_cities_Gini_trend.shpThis data represents the annual dynamic and trends of the Gini index for global 1028 cities in 2000-2018 using the WorldPop population and Landsat-derived greenspace mappings. Key attributes in the shapefile data:(1) Trend: temporal trend of Gini index;(2) P: P-value at a statistically significant level of 0.05;(3) Y2000-Y2018: Annual Gini index for year 2000 to 2018;(4) SouthNorth: Categories of Global South or Global North;(5) Continent: Categories of continents;(6) lat/long: Latitude/longitude of the city centriod;(7) urbanArea: urban areas in Km2.2. Global_1028_cities_Gini_thres20_trend.shpThis data represents the annual dynamic and trends of the Gini index (threshold = 0.20) for global 1028 cities in 2000-2018 using the WorldPop population and Landsat-derived greenspace mappings, together with threshold-based linear unmixing classification approach Key attributes in the shapefile data:(1) Trend_20: temporal trend of Gini index;(2) P_20: P-value at a statistically significant level of 0.05;(3) Y2000-Y2018: Annual Gini index for year 2000 to 2018;(4) SouthNorth: Categories of Global South or Global North;(5) Continent: Categories of continents;(6) lat/long: Latitude/longitude of the city centriod;(7) urbanArea: urban areas in Km2.3. Global_1028_cities_Gini_thres30_trend.shpThis data represents the annual dynamic and trends of the Gini index (threshold = 0.30) for global 1028 cities in 2000-2018 using the WorldPop population and Landsat-derived greenspace mappings, together with threshold-based linear unmixing classification approach Key attributes in the shapefile data:(1) Trend_30: temporal trend of Gini index;(2) P_30: P-value at a statistically significant level of 0.05;(3) Y2000-Y2018: Annual Gini index for year 2000 to 2018;(4) SouthNorth: Categories of Global South or Global North;(5) Continent: Categories of continents;(6) lat/long: Latitude/longitude of the city centriod;(7) urbanArea: urban areas in Km2.4. Global_1028_cities_Gini_thres40_trend.shpThis data represents the annual dynamic and trends of the Gini index (threshold = 0.40) for global 1028 cities in 2000-2018 using the WorldPop population and Landsat-derived greenspace mappings, together with threshold-based linear unmixing classification approach Key attributes in the shapefile data:(1) Trend_40: temporal trend of Gini index;(2) P_40: P-value at a statistically significant level of 0.05;(3) Y2000-Y2018: Annual Gini index for year 2000 to 2018;(4) SouthNorth: Categories of Global South or Global North;(5) Continent: Categories of continents;(6) lat/long: Latitude/longitude of the city centriod;(7) urbanArea: urban areas in Km2.5. Global_1028_cities_Gini_thres50_trend.shpThis data represents the annual dynamic and trends of the Gini index (threshold = 0.50) for global 1028 cities in 2000-2018 using the WorldPop population and Landsat-derived greenspace mappings, together with threshold-based linear unmixing classification approach Key attributes in the shapefile data:(1) Trend_50: temporal trend of Gini index;(2) P_50: P-value at a statistically significant level of 0.05;(3) Y2000-Y2018: Annual Gini index for year 2000 to 2018;(4) SouthNorth: Categories of Global South or Global North;(5) Continent: Categories of continents;(6) lat/long: Latitude/longitude of the city centriod;(7) urbanArea: urban areas in Km2.

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