The highest city in the world with a population of more than one million is La Paz. The Capital of Bolivia sits ***** meters above sea level, and is more than 1,000 meters higher than the second-ranked city, Quito. La Paz is also higher than Mt. Fuji in Japan, which has a height of 3,776 meters. Many of the world's largest cities are located in South America. The only city in North America that makes the top 20 list is Denver, Colorado, which has an altitude of ***** meters.

This dataset provides a comprehensive overview of the population statistics for 800 largest cities in the world, detailing the population estimates for the years 2023 and 2024. Additionally, it includes the calculated growth rate for each city over this period. This dataset can be instrumental for urban studies, demographic analysis, and economic research. Columns Description • City: The name of the city. • Country: The country where the city is located. • Population (2024): Estimated population of the city for the year 2024. • Population (2023): Estimated population of the city for the year 2023. • Growth Rate: The rate of population growth from 2023 to 2024. This is calculated as the difference between the 2024 and 2023 populations, divided by the 2023 population.

As of 2024, Hong Kong was the city in the world with the most skyscrapers that were at least *** meters high. The next city in the ranking was Shenzhen with *** buildings exceeding that height, followed by New York City with *** buildings. Some of the other cities on the list were Dubai and Guangzhou. The Burj Khalifa in Dubai was the highest building in the world.

List of addresses from the top 1000 biggest cities in the world, including coordinates.

List of the columns: - Geoname ID - Name - ASCII Name - Alternate Names - Feature Class - Feature Code - Country Code - Country name EN - Country Code 2 - Admin1 Code - Admin2 Code - Admin3 Code - Admin4 Code - Population (Millions) - Elevation - DIgital Elevation Model - Timezone - Modification Date - LABEL EN - Coordinates

The below dataset shows the top 800 biggest cities in the world and their populations in the year 2024. It also tells us which country and continent each city is in, and their rank based on population size. Here are the top ten cities:

• Tokyo, Japan - in Asia, with 37,115,035 people.
• Delhi, India - in Asia, with 33,807,403 people.
• Shanghai, China - in Asia, with 29,867,918 people.
• Dhaka, Bangladesh - in Asia, with 23,935,652 people.
• Sao Paulo, Brazil - in South America, with 22,806,704 people.
• Cairo, Egypt - in Africa, with 22,623,874 people.
• Mexico City, Mexico - in North America, with 22,505,315 people.
• Beijing, China - in Asia, with 22,189,082 people.
• Mumbai, India - in Asia, with 21,673,149 people.
• Osaka, Japan - in Asia, with 18,967,459 people.

Content

Data was pulled from a table in the following Wikipedia article: https://en.wikipedia.org/wiki/List_of_United_States_cities_by_population I used Microsoft Excel's PowerQuery function to pull the table from Wikipedia. Lists each city, its rank (based on 2020 population), some data on its area, and population in both 2020 and 2010.

Banner image source: https://unsplash.com/photos/wh-7GeXxItI

In 2025, Pietermaritzburg in South Africa ranked as the world's most dangerous city with a crime rate of 82 per 100,000 inhabitants. Five of the 10 cities with the highest crime rates worldwide are found in South Africa. The list does not include countries where war and conflict exist. South Africa dominates crime statistics When looking at crime rates, among the 10 most dangerous cities in the world, half of them are found in South Africa. The country is struggling with extremely high levels of inequality, and is struggling with high levels of crime and power outages, harming the country's economy and driving more people into unemployment and poverty. Crime in Latin America On the other hand, when looking at murder rates, Latin America dominates the list of the world's most dangerous countries. Violence in Latin America is caused in great part by drug trafficking, weapons trafficking, and gang wars.

Source

The data file is from https://simplemaps.com/data/world-cities.

IntroductionClimate Central’s Surging Seas: Risk Zone map shows areas vulnerable to near-term flooding from different combinations of sea level rise, storm surge, tides, and tsunamis, or to permanent submersion by long-term sea level rise. Within the U.S., it incorporates the latest, high-resolution, high-accuracy lidar elevation data supplied by NOAA (exceptions: see Sources), displays points of interest, and contains layers displaying social vulnerability, population density, and property value. Outside the U.S., it utilizes satellite-based elevation data from NASA in some locations, and Climate Central’s more accurate CoastalDEM in others (see Methods and Qualifiers). It provides the ability to search by location name or postal code.The accompanying Risk Finder is an interactive data toolkit available for some countries that provides local projections and assessments of exposure to sea level rise and coastal flooding tabulated for many sub-national districts, down to cities and postal codes in the U.S. Exposure assessments always include land and population, and in the U.S. extend to over 100 demographic, economic, infrastructure and environmental variables using data drawn mainly from federal sources, including NOAA, USGS, FEMA, DOT, DOE, DOI, EPA, FCC and the Census.This web tool was highlighted at the launch of The White House's Climate Data Initiative in March 2014. Climate Central's original Surging Seas was featured on NBC, CBS, and PBS U.S. national news, the cover of The New York Times, in hundreds of other stories, and in testimony for the U.S. Senate. The Atlantic Cities named it the most important map of 2012. Both the Risk Zone map and the Risk Finder are grounded in peer-reviewed science.Back to topMethods and QualifiersThis map is based on analysis of digital elevation models mosaicked together for near-total coverage of the global coast. Details and sources for U.S. and international data are below. Elevations are transformed so they are expressed relative to local high tide lines (Mean Higher High Water, or MHHW). A simple elevation threshold-based “bathtub method” is then applied to determine areas below different water levels, relative to MHHW. Within the U.S., areas below the selected water level but apparently not connected to the ocean at that level are shown in a stippled green (as opposed to solid blue) on the map. Outside the U.S., due to data quality issues and data limitations, all areas below the selected level are shown as solid blue, unless separated from the ocean by a ridge at least 20 meters (66 feet) above MHHW, in which case they are shown as not affected (no blue).Areas using lidar-based elevation data: U.S. coastal states except AlaskaElevation data used for parts of this map within the U.S. come almost entirely from ~5-meter horizontal resolution digital elevation models curated and distributed by NOAA in its Coastal Lidar collection, derived from high-accuracy laser-rangefinding measurements. The same data are used in NOAA’s Sea Level Rise Viewer. (High-resolution elevation data for Louisiana, southeast Virginia, and limited other areas comes from the U.S. Geological Survey (USGS)). Areas using CoastalDEM™ elevation data: Antigua and Barbuda, Barbados, Corn Island (Nicaragua), Dominica, Dominican Republic, Grenada, Guyana, Haiti, Jamaica, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, San Blas (Panama), Suriname, The Bahamas, Trinidad and Tobago. CoastalDEM™ is a proprietary high-accuracy bare earth elevation dataset developed especially for low-lying coastal areas by Climate Central. Use our contact form to request more information.Warning for areas using other elevation data (all other areas)Areas of this map not listed above use elevation data on a roughly 90-meter horizontal resolution grid derived from NASA’s Shuttle Radar Topography Mission (SRTM). SRTM provides surface elevations, not bare earth elevations, causing it to commonly overestimate elevations, especially in areas with dense and tall buildings or vegetation. Therefore, the map under-portrays areas that could be submerged at each water level, and exposure is greater than shown (Kulp and Strauss, 2016). However, SRTM includes error in both directions, so some areas showing exposure may not be at risk.SRTM data do not cover latitudes farther north than 60 degrees or farther south than 56 degrees, meaning that sparsely populated parts of Arctic Circle nations are not mapped here, and may show visual artifacts.Areas of this map in Alaska use elevation data on a roughly 60-meter horizontal resolution grid supplied by the U.S. Geological Survey (USGS). This data is referenced to a vertical reference frame from 1929, based on historic sea levels, and with no established conversion to modern reference frames. The data also do not take into account subsequent land uplift and subsidence, widespread in the state. As a consequence, low confidence should be placed in Alaska map portions.Flood control structures (U.S.)Levees, walls, dams or other features may protect some areas, especially at lower elevations. Levees and other flood control structures are included in this map within but not outside of the U.S., due to poor and missing data. Within the U.S., data limitations, such as an incomplete inventory of levees, and a lack of levee height data, still make assessing protection difficult. For this map, levees are assumed high and strong enough for flood protection. However, it is important to note that only 8% of monitored levees in the U.S. are rated in “Acceptable” condition (ASCE). Also note that the map implicitly includes unmapped levees and their heights, if broad enough to be effectively captured directly by the elevation data.For more information on how Surging Seas incorporates levees and elevation data in Louisiana, view our Louisiana levees and DEMs methods PDF. For more information on how Surging Seas incorporates dams in Massachusetts, view the Surging Seas column of the web tools comparison matrix for Massachusetts.ErrorErrors or omissions in elevation or levee data may lead to areas being misclassified. Furthermore, this analysis does not account for future erosion, marsh migration, or construction. As is general best practice, local detail should be verified with a site visit. Sites located in zones below a given water level may or may not be subject to flooding at that level, and sites shown as isolated may or may not be be so. Areas may be connected to water via porous bedrock geology, and also may also be connected via channels, holes, or passages for drainage that the elevation data fails to or cannot pick up. In addition, sea level rise may cause problems even in isolated low zones during rainstorms by inhibiting drainage.ConnectivityAt any water height, there will be isolated, low-lying areas whose elevation falls below the water level, but are protected from coastal flooding by either man-made flood control structures (such as levees), or the natural topography of the surrounding land. In areas using lidar-based elevation data or CoastalDEM (see above), elevation data is accurate enough that non-connected areas can be clearly identified and treated separately in analysis (these areas are colored green on the map). In the U.S., levee data are complete enough to factor levees into determining connectivity as well.However, in other areas, elevation data is much less accurate, and noisy error often produces “speckled” artifacts in the flood maps, commonly in areas that should show complete inundation. Removing non-connected areas in these places could greatly underestimate the potential for flood exposure. For this reason, in these regions, the only areas removed from the map and excluded from analysis are separated from the ocean by a ridge of at least 20 meters (66 feet) above the local high tide line, according to the data, so coastal flooding would almost certainly be impossible (e.g., the Caspian Sea region).Back to topData LayersWater Level | Projections | Legend | Social Vulnerability | Population | Ethnicity | Income | Property | LandmarksWater LevelWater level means feet or meters above the local high tide line (“Mean Higher High Water”) instead of standard elevation. Methods described above explain how each map is generated based on a selected water level. Water can reach different levels in different time frames through combinations of sea level rise, tide and storm surge. Tide gauges shown on the map show related projections (see just below).The highest water levels on this map (10, 20 and 30 meters) provide reference points for possible flood risk from tsunamis, in regions prone to them.

This horizontal bar chart displays land area (km²) by capital city using the aggregation sum in Peru. The data is filtered where the date is 2021. The data is about countries per year.

Two Mexican, two Thai, and two Japanese cities were among the world's ten best-rated destinations in 2025, according to a survey conducted among Travel + Leisure readers. San Miguel de Allende ranked first with a score of 93.33.

The "Major Cities" layer is derived from the "World Cities" dataset provided by ArcGIS Data and Maps group as part of the global data layers made available for public use. "Major cities" layer specifically contains National and Provincial capitals that have the highest population within their respective country. Cities were filtered based on the STATUS (“National capital”, “National and provincial capital”, “Provincial capital”, “National capital and provincial capital enclave”, and “Other”). Majority of these cities within larger countries have been filtered at the highest levels of POP_CLASS (“5,000,000 and greater” and “1,000,000 to 4,999,999”). However, China for example, was filtered with cities over 11 million people due to many highly populated cities. Population approximations are sourced from US Census and UN Data. Credits: ESRI, CIA World Factbook, GMI, NIMA, UN Data, UN Habitat, US Census Bureau Disclaimer: The designations employed and the presentation of material at this site do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

Japan Urban Land Price Index: Biggest 6 City: Highest Price List data was reported at 15.100 31Mar1990=100 in Mar 2002. This records a decrease from the previous number of 15.800 31Mar1990=100 for Sep 2001. Japan Urban Land Price Index: Biggest 6 City: Highest Price List data is updated semiannually, averaging 13.500 31Mar1990=100 from Mar 1955 (Median) to Mar 2002, with 95 observations. The data reached an all-time high of 103.200 31Mar1990=100 in Sep 1990 and a record low of 0.950 31Mar1990=100 in Mar 1955. Japan Urban Land Price Index: Biggest 6 City: Highest Price List data remains active status in CEIC and is reported by Japan Real Estate Institute. The data is categorized under Global Database’s Japan – Table JP.EB017: Urban Land Price Index: 31Mar1990=100.

Actual value and historical data chart for World Population In The Largest City Percent Of Urban Population

CONTENT

• It is perhaps unsurprising that the majority of the most populous cities in the world are in the two most populated countries in the world, China and India. Among these are Shanghai and Beijing, with populations of 25 and 22 million respectively, Delhi (27 million), and Mumbai (over 21.5 million).

• Tokyo is the largest city in the world if the entire Tokyo metro area is included, with a total of more than 38 million residents. Another Japanese city, Osaka, also has a very large population of almost 20.5 million. There are also a number of non-Asian cities with high populations, including Mexico City (over 21 million), Cairo (almost 19.5 million), and Buenos Aires (almost 15.5 million).

• European cities, Istanbul is the most populous, with more than 14.5 million residents. This is followed by Moscow (over 12 million) and Paris (11 million including the Paris metro area). These cities are of course also culturally significant and between them welcome millions of tourists each year.

• There are quite a number of popular and culturally rich cities that have smaller populations, often making for higher living standards for their residents. Barcelona, Sydney, Berlin and Vancouver all have fewer than five million residents, but are very popular choices for city living. There are also some comparatively very small cities with big cultural, historical or political reputations, such as Sarajevo (314,000), Edinburgh (502,000), and Venice (631,000), demonstrating that small cities can be highly significant regardless of the size of their population.

This horizontal bar chart displays land area (km²) by capital city using the aggregation sum in Oceania. The data is about countries.

ESA, in collaboration with European Space Imaging, has collected this WorldView-2 dataset covering the most populated areas in Europe at 40 cm resolution. The products have been acquired between July 2010 and July 2015. Spatial coverage: Check the spatial coverage of the collection on a map available on the Third Party Missions Dissemination Service.

The hottest average annual temperature recorded at a single location was **** degrees Celsius in Makkah, Saudi Arabia in 2010 and again in 2016. Makkah, also spelled Mecca, sees millions of Muslim enter the city every year. Although 2010 set the record for the hottest year globally on record, the record was then broken several times throughout the following decade. As of 2019, the hottest year on record globally was 2016, followed by 2019.

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.

This is a Dataset of german cities that are classified as "Großstadt" (eng: "Large-City", def: minimum population= 100.000). This is scraped off of Wikipedia and cleaned up to be usable. No values are changed.