{"id":1195795,"name":"Share of total population living in the capital city","unit":"%","createdAt":"2026-02-24T11:28:39.000Z","updatedAt":"2026-04-10T13:15:44.000Z","coverage":"","timespan":"1950-2020","datasetId":7291,"shortUnit":"%","columnOrder":0,"shortName":"total_pop_share_capital_estimates","catalogPath":"grapher/urbanization/2025-12-10/ghsl_urban_centers/ghsl_urban_centers#total_pop_share_capital_estimates","descriptionShort":"Percentage of the total population living in the country's capital city. [Cities](#dod:cities-degurba) are identified using satellite imagery and population data, applying the same definitions across countries.","type":"float","dataChecksum":"11428455499694246614","metadataChecksum":"8346438330515046282","datasetName":"GHSL Urban Centre Database 2025 (GHS-UCDB R2024A)","updatePeriodDays":365,"datasetVersion":"2025-12-10","nonRedistributable":false,"display":{"unit":"%","shortUnit":"%","numDecimalPlaces":1,"entityAnnotationsMap":"Afghanistan: Kabul\nAlbania: Tirana\nAlgeria: Algiers\nAngola: Luanda\nArgentina: Buenos Aires\nArmenia: Yerevan\nAruba: Oranjestad\nAustralia: Canberra\nAustria: Vienna\nAzerbaijan: Baku\nBahamas: Nassau\nBahrain: Manama\nBangladesh: Dhaka\nBarbados: Bridgetown\nBelarus: Minsk\nBelgium: Brussels\nBenin: Porto-Novo\nBolivia: La Paz\nBosnia and Herzegovina: Sarajevo\nBotswana: Gaborone\nBrazil: Brasilia\nBrunei: Bandar Seri Begawan\nBulgaria: Sofia\nBurkina Faso: Ouagadougou\nBurundi: Gitega\nCambodia: Phnom Penh\nCameroon: Yaoundé\nCanada: Ottawa\nCentral African Republic: Bangui\nChad: N'Djamena\nChile: Santiago\nChina: Beijing\nColombia: Bogota\nComoros: Moroni\nCosta Rica: San José\nCroatia: Zagreb\nCuba: Havana\nCuracao: Willemstad\nCyprus: Strovolos [Nicosia]\nCzechia: Prague\nCote d'Ivoire: Yamoussoukro\nDemocratic Republic of Congo: Kinshasa\nDenmark: Copenhagen\nDjibouti: Djibouti\nDominican Republic: Santo Domingo\nEcuador: Quito\nEgypt: Cairo\nEl Salvador: San Salvador\nEquatorial Guinea: Malabo\nEritrea: Asmara\nEstonia: Tallinn\nEthiopia: Addis Ababa\nFiji: Suva\nFinland: Helsinki\nFrance: Paris\nFrench Guiana: Cayenne\nFrench Polynesia: Papeete\nGabon: Libreville\nGeorgia: Tbilisi\nGermany: Berlin\nGhana: Accra\nGreece: Athens\nGuatemala: Guatemala City\nGuinea-Bissau: Bissau\nGuyana: Georgetown\nHaiti: Port-au-Prince\nHonduras: Tegucigalpa\nHungary: Budapest\nIceland: Reykjavik\nIndia: New Delhi\nIndonesia: Jakarta\nIran: Tehran\nIraq: Baghdad\nIreland: Dublin\nIsrael: Jerusalem\nItaly: Rome\nJamaica: Kingston\nJapan: Tokyo\nJersey: St. Helier\nJordan: Amman\nKazakhstan: Astana\nKenya: Nairobi\nKosovo: Pristina\nKuwait: Kuwait City\nKyrgyzstan: Bishkek\nLaos: Vientiane\nLatvia: Riga\nLebanon: Beirut\nLesotho: Maseru\nLiberia: Monrovia\nLibya: Tripoli\nLithuania: Vilnius\nLuxembourg: Luxembourg\nMadagascar: Antananarivo\nMalawi: Lilongwe\nMalaysia: Putrajaya\nMaldives: Malé\nMali: Bamako\nMalta: Valletta\nMauritania: Nouakchott\nMauritius: Port Louis\nMayotte: Mamoudzou\nMoldova: Chișinău\nMongolia: Ulaanbaatar\nMontenegro: Podgorica\nMorocco: Rabat\nMozambique: Maputo\nMyanmar: Pyinmana [Nay Pyi Taw]\nMexico: Mexico City\nNamibia: Windhoek\nNepal: Kathmandu\nNetherlands: The Hague\nNew Caledonia: Nouméa\nNew Zealand: Wellington\nNicaragua: Managua\nNiger: Niamey\nNigeria: Abuja\nNorth Korea: P'yŏngyang\nNorth Macedonia: Skopje\nNorthern Cyprus: Nicosia\nNorway: Oslo\nOman: Muscat\nPakistan: Islamabad\nPalestine: Ramallah\nPanama: Panama City\nPapua New Guinea: Port Moresby\nParaguay: Asuncion\nPeru: Lima\nPhilippines: Manila\nPoland: Warsaw\nPortugal: Lisbon\nPuerto Rico: Bayamón [San Juan]\nQatar: Doha\nCongo: Brazzaville\nRomania: Bucharest\nRussia: Moscow\nRwanda: Kigali\nReunion: Saint-Denis\nSamoa: Apia\nSaudi Arabia: Riyadh\nSenegal: Dakar\nSerbia: Belgrade\nSierra Leone: Freetown\nSingapore: Singapore\nSlovakia: Bratislava\nSlovenia: Ljubljana\nSolomon Islands: Honiara\nSomalia: Mogadishu\nSouth Africa: Pretoria\nSouth Korea: Seoul\nSouth Sudan: Juba\nSpain: Madrid\nSri Lanka: Colombo [Sri Jayawardenepura Kotte]\nSudan: Khartoum\nSuriname: Paramaribo\nSweden: Stockholm\nSwitzerland: Bern\nSyria: Damascus\nSao Tome and Principe: São Tomé\nTaiwan: Taipei\nTajikistan: Dushanbe\nTanzania: Dodoma\nThailand: Bangkok\nEast Timor: Dili\nTogo: Lomé\nTonga: Nuku'alofa\nTrinidad and Tobago: Port of Spain\nTunisia: Tunis\nTurkey: Ankara\nTurkmenistan: Ashgabat\nUganda: Kampala\nUkraine: Kyiv\nUnited Arab Emirates: Abu Dhabi\nUnited Kingdom: London\nUnited States: Washington\nUruguay: Montevideo\nUzbekistan: Tashkent\nVanuatu: Port Vila\nVenezuela: Caracas\nVietnam: Hanoi\nYemen: Sana'a\nZambia: Lusaka\nZimbabwe: Harare"},"schemaVersion":2,"processingLevel":"minor","presentation":{"topicTagsLinks":["Urbanization"]},"descriptionKey":["Estimated share of a country's total population living in its capital city, based on satellite imagery and census data.","The [GHSL Urban Centre Database (GHS-UCDB R2024A)](https://human-settlement.emergency.copernicus.eu/ghs_ucdb2024.php) tracks population and land use for 11,422 [cities](#dod:cities-degurba) around the world. Cities are identified using the [Degree of Urbanization](https://human-settlement.emergency.copernicus.eu/degurba.php), based on population density and settlement size rather than administrative boundaries. To qualify as a city, an area must have at least 1,500 people per square kilometre and a total population of at least 50,000. The classification uses 1 km² grid cells, combining satellite imagery with census data to map where people actually live.","City boundaries are fixed at their 2025 extent and held constant across all years. This means historical values reflect conditions within today's city boundary, not the city as it was defined at the time. For density in particular, this can make fast-growing cities appear less dense in the past than they actually were, since the area used in the calculation includes land that wasn't yet part of the city.","Cities are also split at country borders, so a city that straddles two countries will appear as two separate entries.","City boundaries are model-derived and won't always match official administrative limits. In some countries, what is considered a single city may appear as multiple cities in this data, depending on how built-up areas are distributed. Data quality also varies by region and tends to be less reliable in countries with sparse or outdated census data.","The underlying population figures have been rescaled to match UN World Population Prospects 2022 national totals, so country-level numbers are consistent with UN estimates.","For the years 1950–1975, there are no detailed maps showing where people lived within countries. So instead of using grid-level or satellite data, the estimates are reconstructed using national statistics from the UN. From 1975 onwards, population is mapped to 1 km² grid cells by combining census data with satellite imagery of built-up areas from the [Global Human Settlement Layer (GHSL)](https://human-settlement.emergency.copernicus.eu/).","The total population includes both urban and rural populations.","Where a country has multiple capital cities, the population shown is for the administrative capital.","Data is excluded for Gibraltar, Macao, and Monaco because their urban centers are cross-border agglomerations that extend beyond the country's boundaries, making the share calculation invalid."],"dimensions":{"years":{"values":[{"id":1950},{"id":1955},{"id":1960},{"id":1965},{"id":1970},{"id":1975},{"id":1980},{"id":1985},{"id":1990},{"id":1995},{"id":2000},{"id":2005},{"id":2010},{"id":2015},{"id":2020}]},"entities":{"values":[{"id":15,"name":"Afghanistan","code":"AFG"},{"id":273,"name":"Africa","code":"OWID_AFR"},{"id":16,"name":"Albania","code":"ALB"},{"id":17,"name":"Algeria","code":"DZA"},{"id":19,"name":"Angola","code":"AGO"},{"id":21,"name":"Argentina","code":"ARG"},{"id":22,"name":"Armenia","code":"ARM"},{"id":275,"name":"Asia","code":"OWID_ASI"},{"id":24,"name":"Austria","code":"AUT"},{"id":25,"name":"Azerbaijan","code":"AZE"},{"id":26,"name":"Bahamas","code":"BHS"},{"id":27,"name":"Bahrain","code":"BHR"},{"id":28,"name":"Bangladesh","code":"BGD"},{"id":29,"name":"Barbados","code":"BRB"},{"id":30,"name":"Belarus","code":"BLR"},{"id":4,"name":"Belgium","code":"BEL"},{"id":32,"name":"Benin","code":"BEN"},{"id":33,"name":"Bhutan","code":"BTN"},{"id":34,"name":"Bolivia","code":"BOL"},{"id":35,"name":"Bosnia and Herzegovina","code":"BIH"},{"id":36,"name":"Botswana","code":"BWA"},{"id":37,"name":"Brazil","code":"BRA"},{"id":38,"name":"Brunei","code":"BRN"},{"id":39,"name":"Bulgaria","code":"BGR"},{"id":40,"name":"Burkina Faso","code":"BFA"},{"id":41,"name":"Burundi","code":"BDI"},{"id":42,"name":"Cambodia","code":"KHM"},{"id":43,"name":"Cameroon","code":"CMR"},{"id":44,"name":"Canada","code":"CAN"},{"id":174,"name":"Central African Republic","code":"CAF"},{"id":173,"name":"Chad","code":"TCD"},{"id":172,"name":"Chile","code":"CHL"},{"id":171,"name":"China","code":"CHN"},{"id":170,"name":"Colombia","code":"COL"},{"id":169,"name":"Comoros","code":"COM"},{"id":168,"name":"Congo","code":"COG"},{"id":166,"name":"Costa Rica","code":"CRI"},{"id":143,"name":"Cote d'Ivoire","code":"CIV"},{"id":165,"name":"Croatia","code":"HRV"},{"id":164,"name":"Cuba","code":"CUB"},{"id":163,"name":"Cyprus","code":"CYP"},{"id":162,"name":"Czechia","code":"CZE"},{"id":167,"name":"Democratic Republic of Congo","code":"COD"},{"id":161,"name":"Denmark","code":"DNK"},{"id":154,"name":"Djibouti","code":"DJI"},{"id":160,"name":"Dominican Republic","code":"DOM"},{"id":225,"name":"East Timor","code":"TLS"},{"id":201,"name":"Ecuador","code":"ECU"},{"id":65,"name":"Egypt","code":"EGY"},{"id":259,"name":"El Salvador","code":"SLV"},{"id":159,"name":"Equatorial Guinea","code":"GNQ"},{"id":157,"name":"Eritrea","code":"ERI"},{"id":156,"name":"Estonia","code":"EST"},{"id":158,"name":"Ethiopia","code":"ETH"},{"id":276,"name":"Europe","code":"OWID_EUR"},{"id":202,"name":"Fiji","code":"FJI"},{"id":155,"name":"Finland","code":"FIN"},{"id":3,"name":"France","code":"FRA"},{"id":253,"name":"French Guiana","code":"GUF"},{"id":203,"name":"French Polynesia","code":"PYF"},{"id":153,"name":"Gabon","code":"GAB"},{"id":152,"name":"Georgia","code":"GEO"},{"id":6,"name":"Germany","code":"DEU"},{"id":150,"name":"Ghana","code":"GHA"},{"id":149,"name":"Greece","code":"GRC"},{"id":148,"name":"Guatemala","code":"GTM"},{"id":94,"name":"Guinea-Bissau","code":"GNB"},{"id":146,"name":"Guyana","code":"GUY"},{"id":145,"name":"Haiti","code":"HTI"},{"id":457,"name":"High-income countries","code":"OWID_HIC"},{"id":139,"name":"Honduras","code":"HND"},{"id":144,"name":"Hong Kong","code":"HKG"},{"id":138,"name":"Hungary","code":"HUN"},{"id":207,"name":"Iceland","code":"ISL"},{"id":137,"name":"India","code":"IND"},{"id":136,"name":"Indonesia","code":"IDN"},{"id":135,"name":"Iran","code":"IRN"},{"id":134,"name":"Iraq","code":"IRQ"},{"id":2,"name":"Ireland","code":"IRL"},{"id":133,"name":"Israel","code":"ISR"},{"id":8,"name":"Italy","code":"ITA"},{"id":132,"name":"Jamaica","code":"JAM"},{"id":14,"name":"Japan","code":"JPN"},{"id":283,"name":"Jersey","code":"JEY"},{"id":130,"name":"Jordan","code":"JOR"},{"id":131,"name":"Kazakhstan","code":"KAZ"},{"id":129,"name":"Kenya","code":"KEN"},{"id":379,"name":"Kosovo","code":"OWID_KOS"},{"id":208,"name":"Kuwait","code":"KWT"},{"id":126,"name":"Kyrgyzstan","code":"KGZ"},{"id":125,"name":"Laos","code":"LAO"},{"id":122,"name":"Latvia","code":"LVA"},{"id":124,"name":"Lebanon","code":"LBN"},{"id":123,"name":"Lesotho","code":"LSO"},{"id":121,"name":"Liberia","code":"LBR"},{"id":120,"name":"Libya","code":"LBY"},{"id":119,"name":"Lithuania","code":"LTU"},{"id":461,"name":"Low-income countries","code":"OWID_LIC"},{"id":460,"name":"Lower-middle-income countries","code":"OWID_LMC"},{"id":210,"name":"Luxembourg","code":"LUX"},{"id":118,"name":"Madagascar","code":"MDG"},{"id":117,"name":"Malawi","code":"MWI"},{"id":116,"name":"Malaysia","code":"MYS"},{"id":211,"name":"Maldives","code":"MDV"},{"id":115,"name":"Mali","code":"MLI"},{"id":212,"name":"Malta","code":"MLT"},{"id":284,"name":"Martinique","code":"MTQ"},{"id":114,"name":"Mauritania","code":"MRT"},{"id":213,"name":"Mauritius","code":"MUS"},{"id":193,"name":"Mayotte","code":"MYT"},{"id":113,"name":"Mexico","code":"MEX"},{"id":111,"name":"Moldova","code":"MDA"},{"id":112,"name":"Mongolia","code":"MNG"},{"id":215,"name":"Montenegro","code":"MNE"},{"id":110,"name":"Morocco","code":"MAR"},{"id":109,"name":"Mozambique","code":"MOZ"},{"id":142,"name":"Myanmar","code":"MMR"},{"id":108,"name":"Namibia","code":"NAM"},{"id":107,"name":"Nepal","code":"NPL"},{"id":5,"name":"Netherlands","code":"NLD"},{"id":220,"name":"New Caledonia","code":"NCL"},{"id":106,"name":"New Zealand","code":"NZL"},{"id":105,"name":"Nicaragua","code":"NIC"},{"id":104,"name":"Niger","code":"NER"},{"id":103,"name":"Nigeria","code":"NGA"},{"id":294,"name":"North America","code":"OWID_NAM"},{"id":128,"name":"North Korea","code":"PRK"},{"id":66,"name":"North Macedonia","code":"MKD"},{"id":102,"name":"Norway","code":"NOR"},{"id":277,"name":"Oceania","code":"OWID_OCE"},{"id":217,"name":"Oman","code":"OMN"},{"id":101,"name":"Pakistan","code":"PAK"},{"id":140,"name":"Palestine","code":"PSE"},{"id":100,"name":"Panama","code":"PAN"},{"id":99,"name":"Papua New Guinea","code":"PNG"},{"id":98,"name":"Paraguay","code":"PRY"},{"id":97,"name":"Peru","code":"PER"},{"id":96,"name":"Philippines","code":"PHL"},{"id":11,"name":"Poland","code":"POL"},{"id":95,"name":"Portugal","code":"PRT"},{"id":93,"name":"Puerto Rico","code":"PRI"},{"id":226,"name":"Qatar","code":"QAT"},{"id":245,"name":"Reunion","code":"REU"},{"id":92,"name":"Romania","code":"ROU"},{"id":12,"name":"Russia","code":"RUS"},{"id":91,"name":"Rwanda","code":"RWA"},{"id":232,"name":"Sao Tome and Principe","code":"STP"},{"id":90,"name":"Saudi Arabia","code":"SAU"},{"id":89,"name":"Senegal","code":"SEN"},{"id":88,"name":"Serbia","code":"SRB"},{"id":87,"name":"Sierra Leone","code":"SLE"},{"id":86,"name":"Singapore","code":"SGP"},{"id":85,"name":"Slovakia","code":"SVK"},{"id":83,"name":"Slovenia","code":"SVN"},{"id":195,"name":"Solomon Islands","code":"SLB"},{"id":82,"name":"Somalia","code":"SOM"},{"id":81,"name":"South Africa","code":"ZAF"},{"id":295,"name":"South America","code":"OWID_SAM"},{"id":127,"name":"South Korea","code":"KOR"},{"id":258,"name":"South Sudan","code":"SSD"},{"id":9,"name":"Spain","code":"ESP"},{"id":141,"name":"Sri Lanka","code":"LKA"},{"id":79,"name":"Sudan","code":"SDN"},{"id":234,"name":"Suriname","code":"SUR"},{"id":10,"name":"Sweden","code":"SWE"},{"id":7,"name":"Switzerland","code":"CHE"},{"id":77,"name":"Syria","code":"SYR"},{"id":198,"name":"Taiwan","code":"TWN"},{"id":76,"name":"Tajikistan","code":"TJK"},{"id":64,"name":"Tanzania","code":"TZA"},{"id":75,"name":"Thailand","code":"THA"},{"id":74,"name":"Togo","code":"TGO"},{"id":73,"name":"Trinidad and Tobago","code":"TTO"},{"id":71,"name":"Tunisia","code":"TUN"},{"id":70,"name":"Turkey","code":"TUR"},{"id":69,"name":"Turkmenistan","code":"TKM"},{"id":68,"name":"Uganda","code":"UGA"},{"id":67,"name":"Ukraine","code":"UKR"},{"id":72,"name":"United Arab Emirates","code":"ARE"},{"id":1,"name":"United Kingdom","code":"GBR"},{"id":13,"name":"United States","code":"USA"},{"id":459,"name":"Upper-middle-income countries","code":"OWID_UMC"},{"id":63,"name":"Uruguay","code":"URY"},{"id":62,"name":"Uzbekistan","code":"UZB"},{"id":238,"name":"Venezuela","code":"VEN"},{"id":84,"name":"Vietnam","code":"VNM"},{"id":355,"name":"World","code":"OWID_WRL"},{"id":61,"name":"Yemen","code":"YEM"},{"id":60,"name":"Zambia","code":"ZMB"},{"id":80,"name":"Zimbabwe","code":"ZWE"}]}},"origins":[{"id":9488,"titleSnapshot":"Global Human Settlement Layer Dataset - Urban centers","title":"Global Human Settlement Layer Dataset","description":"The dataset includes population projections by degree of urbanisation and at the city level.\n\nFor every country and territory in the world, the authors estimated their population from 1950 to 2100 in cities, towns and semi-dense areas, and rural areas. It relies on the UN-endorsed Degree of Urbanisation methodology. As a result, the definitions used in each country are fully harmonised; while national definitions vary considerably.\n\nThe long time series consists of three parts:\n\n- From 1950 to 1970, it is based on backcasting by blending data using national definitions of urban and rural areas with data using the Degree of Urbanisation.\n- From 1975 to 2020, it is based on the Global Human Settlement Layer (GHSL), because it has the longest time series and uses a transparent and reproducible method.\n- From 2020 to 2100, it relies on a new model, \"Cities and Rural Integrated Spatial Projections\" (CRISP).\n\nThe CRISP model estimates population and built-up area change for a global grid of 1 km2 cells in an evidence-based, three-step process. First, the authors estimate population and built-up area change for roughly 1000 functional areas based on past trends and national population projections. Second, they allocate new built-up area to grid cells considering distance to settlements, roads, water, current share of built-up area and other characteristics. Finally, they add population to newly built-up areas and more suitable locations and reduce it in less suitable locations to capture internal migration and natural population decline.\n\nBeyond population, the dataset also delivers maps showing the evolving spatial extent of cities, towns and rural areas. For every city in the world, it also provides updated boundaries, land area and built-up area at five-year intervals from 1975 to 2100.","producer":"European Commission, Joint Research Centre (JRC)","citationFull":"Schiavina, Marcello; Alessandrini, Alfredo; Melchiorri, Michele; Dijkstra, Lewis (2025): GHS-WUP-MTUC R2025A – GHS-WUP multitemporal urban centres, obtained from the Degree of Urbanisation grids (GHS-WUP-DEGURBA R2025A) and linked across epochs, multitemporal (1950-2100). European Commission, Joint Research Centre (JRC). PID: http://data.europa.eu/89h/1ea967e5-bedc-4cf3-a0b0-3851742ee7e2 , doi: 10.2905/1ea967e5-bedc-4cf3-a0b0-3851742ee7e2\n\nPesaresi, Martino, Marcello Schiavina, Panagiotis Politis, Sergio Freire, Katarzyna Krasnodębska, Johannes H. Uhl, Alessandra Carioli, et al. (2024). Advances on the Global Human Settlement Layer by Joint Assessment of Earth Observation and Population Survey Data. International Journal of Digital Earth 17 (1). doi:10.1080/17538947.2024.2390454\n\nJacobs-Crisioni, Chris et al (2025). Population projections by degree of urbanisation for the UN World Urbanization Prospects: introducing the CRISP model, Publications Office of the European Union, Luxembourg, 2025, doi:10.2760/7163875","urlMain":"https://human-settlement.emergency.copernicus.eu/ghs_wup2025.php","urlDownload":"https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_WUP_MTUC_GLOBE_R2025A/V1-0/GHS_WUP_MTUC_GLOBE_R2025A_V1_0_statistics.zip","dateAccessed":"2025-12-10","datePublished":"2025","license":{"url":"https://human-settlement.emergency.copernicus.eu/GHSLhowToCite.php","name":"European Union, 1995-2025"}}]}