{"id": 1002866, "name": "Population density of the top 100 most populous cities", "unit": "people/km\u00b2", "createdAt": "2024-12-06T16:57:51.000Z", "updatedAt": "2025-03-14T15:14:22.000Z", "coverage": "", "timespan": "1975-2020", "datasetId": 6856, "columnOrder": 0, "shortName": "urban_density_top_100_estimates", "catalogPath": "grapher/urbanization/2024-12-02/ghsl_urban_centers/ghsl_urban_centers#urban_density_top_100_estimates", "descriptionShort": "The number of people per km\u00b2 of land area for cities ranked among the top 100 most populous in 2020.", "descriptionProcessing": "Population density was calculated by dividing the population of the city by the total area it covers, providing a measure of the number of people living in each km\u00b2.", "type": "float", "dataChecksum": "8976377326179070578", "metadataChecksum": "-4368605296582943554", "datasetName": "Global Human Settlement Layer Dataset -  Stats in the City Database", "updatePeriodDays": 365, "datasetVersion": "2024-12-02", "nonRedistributable": false, "display": {"unit": "people/km\u00b2", "numDecimalPlaces": 0}, "schemaVersion": 2, "processingLevel": "minor", "presentation": {"topicTagsLinks": ["Urbanization"]}, "descriptionKey": ["The European Commission integrates satellite imagery with national census data to delineate the boundaries of capital cities and estimate their populations.\nTo predict future urbanization (2025 and 2030), both static (land features) and dynamic (past satellite images) components are used to project growth. DEGURBA defines cities by population, not administrative borders, aligning with UN guidelines, though fixed thresholds may not always capture local differences."], "dimensions": {"years": {"values": [{"id": 1975}, {"id": 1980}, {"id": 1985}, {"id": 1990}, {"id": 1995}, {"id": 2000}, {"id": 2005}, {"id": 2010}, {"id": 2015}, {"id": 2020}]}, "entities": {"values": [{"id": 371090, "name": "Abidjan (C\u00f4te d'Ivoire)", "code": null}, {"id": 371065, "name": "Accra (Ghana)", "code": null}, {"id": 371002, "name": "Addis Ababa (Ethiopia)", "code": null}, {"id": 371005, "name": "Ahmedabad (India)", "code": null}, {"id": 371079, "name": "Alexandria (Egypt)", "code": null}, {"id": 371111, "name": "Amman (Jordan)", "code": null}, {"id": 371033, "name": "Baghdad (Iraq)", "code": null}, {"id": 370998, "name": "Bandung (Indonesia)", "code": null}, {"id": 371021, "name": "Bangkok (Thailand)", "code": null}, {"id": 371031, "name": "Beijing (China)", "code": null}, {"id": 371025, "name": "Belo Horizonte (Brazil)", "code": null}, {"id": 371028, "name": "Bengaluru (India)", "code": null}, {"id": 371015, "name": "Bogota (Colombia)", "code": null}, {"id": 371101, "name": "Buenos Aires (Argentina)", "code": null}, {"id": 371051, "name": "Cairo (Egypt)", "code": null}, {"id": 370985, "name": "Casablanca (Morocco)", "code": null}, {"id": 371085, "name": "Chattogram (Bangladesh)", "code": null}, {"id": 370989, "name": "Chengdu (China)", "code": null}, {"id": 371083, "name": "Chennai (India)", "code": null}, {"id": 371020, "name": "Chicago (United States)", "code": null}, {"id": 371080, "name": "Chongqing (China)", "code": null}, {"id": 371075, "name": "Colombo [Sri Jayawardenepura Kotte] (Sri Lanka)", "code": null}, {"id": 371042, "name": "Dar es-Salaam (Tanzania)", "code": null}, {"id": 371088, "name": "Dhaka (Bangladesh)", "code": null}, {"id": 371074, "name": "Dubai (United Arab Emirates)", "code": null}, {"id": 371053, "name": "Faisalabad (Pakistan)", "code": null}, {"id": 371040, "name": "Guangzhou (China)", "code": null}, {"id": 371008, "name": "Hajipur (India)", "code": null}, {"id": 371106, "name": "Hangzhou (China)", "code": null}, {"id": 370994, "name": "Hanoi (Vietnam)", "code": null}, {"id": 371044, "name": "Harbin (China)", "code": null}, {"id": 371081, "name": "Hefei (China)", "code": null}, {"id": 370982, "name": "Ho Chi Minh City (Vietnam)", "code": null}, {"id": 36559, "name": "Hong Kong (China)", "code": null}, {"id": 371086, "name": "Hyderabad (India)", "code": null}, {"id": 371018, "name": "Islamabad (Pakistan)", "code": null}, {"id": 371026, "name": "Istanbul (Turkey)", "code": null}, {"id": 371068, "name": "Jakarta (Indonesia)", "code": null}, {"id": 371050, "name": "Jeddah (Saudi Arabia)", "code": null}, {"id": 371039, "name": "Johannesburg (South Africa)", "code": null}, {"id": 371087, "name": "Kabul (Afghanistan)", "code": null}, {"id": 371063, "name": "Kampala (Uganda)", "code": null}, {"id": 370993, "name": "Kano (Nigeria)", "code": null}, {"id": 371067, "name": "Kanpur (India)", "code": null}, {"id": 371055, "name": "Karachi (Pakistan)", "code": null}, {"id": 371036, "name": "Khartoum (Sudan)", "code": null}, {"id": 371011, "name": "Kinshasa (Democratic Republic of the Congo)", "code": null}, {"id": 371043, "name": "Kochi (India)", "code": null}, {"id": 370995, "name": "Kolkata (India)", "code": null}, {"id": 370988, "name": "Kozhikode (India)", "code": null}, {"id": 371004, "name": "Kuala Lumpur (Malaysia)", "code": null}, {"id": 371084, "name": "Lagos (Nigeria)", "code": null}, {"id": 371096, "name": "Lahore (Pakistan)", "code": null}, {"id": 371006, "name": "Lima (Peru)", "code": null}, {"id": 371037, "name": "London (United Kingdom)", "code": null}, {"id": 371070, "name": "Los Angeles (United States)", "code": null}, {"id": 371027, "name": "Luanda (Angola)", "code": null}, {"id": 371078, "name": "Lucknow (India)", "code": null}, {"id": 371092, "name": "Madrid (Spain)", "code": null}, {"id": 371001, "name": "Manila (Philippines)", "code": null}, {"id": 370978, "name": "Mashhad (Iran)", "code": null}, {"id": 371009, "name": "Medan (Indonesia)", "code": null}, {"id": 370986, "name": "Mexico City (M\u00e9xico)", "code": null}, {"id": 371094, "name": "Miami (United States)", "code": null}, {"id": 371012, "name": "Moscow (Russia)", "code": null}, {"id": 371019, "name": "Mumbai (India)", "code": null}, {"id": 371073, "name": "Nagoya (Japan)", "code": null}, {"id": 371061, "name": "Nairobi (Kenya)", "code": null}, {"id": 371047, "name": "Nanjing (China)", "code": null}, {"id": 371100, "name": "New Delhi (India)", "code": null}, {"id": 371045, "name": "New York City (United States)", "code": null}, {"id": 371010, "name": "Onitsha (Nigeria)", "code": null}, {"id": 371007, "name": "Osaka (Japan)", "code": null}, {"id": 370991, "name": "Paris (France)", "code": null}, {"id": 371029, "name": "Pune (India)", "code": null}, {"id": 371104, "name": "Rio de Janeiro (Brazil)", "code": null}, {"id": 371034, "name": "Riyadh (Saudi Arabia)", "code": null}, {"id": 371102, "name": "Saint Petersburg (Russia)", "code": null}, {"id": 371103, "name": "San Francisco (United States)", "code": null}, {"id": 371110, "name": "Santiago (Chile)", "code": null}, {"id": 37861, "name": "Santo Domingo (Dominican Republic)", "code": null}, {"id": 371016, "name": "Seoul (South Korea)", "code": null}, {"id": 371076, "name": "Shanghai (China)", "code": null}, {"id": 371041, "name": "Shantou (China)", "code": null}, {"id": 371066, "name": "Shenyang (China)", "code": null}, {"id": 370979, "name": "Singapore (Singapore)", "code": null}, {"id": 371022, "name": "Surabaya (Indonesia)", "code": null}, {"id": 371064, "name": "Surat (India)", "code": null}, {"id": 371023, "name": "S\u00e3o Paulo (Brazil)", "code": null}, {"id": 370984, "name": "Taipei (Taiwan)", "code": null}, {"id": 370996, "name": "Tehran (Iran)", "code": null}, {"id": 370987, "name": "Tianjin (China)", "code": null}, {"id": 371057, "name": "Tokyo (Japan)", "code": null}, {"id": 371000, "name": "Toronto (Canada)", "code": null}, {"id": 371072, "name": "Wenzhou (China)", "code": null}, {"id": 371091, "name": "Wuhan (China)", "code": null}, {"id": 371071, "name": "Xi'an (China)", "code": null}, {"id": 371032, "name": "Yangon (Myanmar)", "code": null}, {"id": 371046, "name": "Yaound\u00e9 (Cameroon)", "code": null}, {"id": 370983, "name": "Zhengzhou (China)", "code": null}]}}, "origins": [{"id": 2175, "title": "Global Human Settlement Layer Dataset -  Stats in the City Database", "description": "The \"Stats in the City Database\" offers harmonized data on population and population density for 11,422 urban centres.\n\nThis data, based on the Global Human Settlement Layer Dataset, uses the Degree of Urbanisation framework to delineate spatial entities and integrates geospatial data from a variety of open-source datasets. It represents one of the most comprehensive resources for understanding urban population patterns and densities worldwide", "producer": "European Commission, Joint Research Centre (JRC)", "citationFull": "Center For International Earth Science Information Network-CIESIN-Columbia University. 2018. \u201cGridded Population of the World, Version 4 (GPWv4): Population Count, Revision 11.\u201d Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4JW8BX5\nPesaresi M., Politis P. (2023): GHS-BUILT-V R2023A - GHS built-up volume grids derived from joint assessment of Sentinel2, Landsat, and global DEM data, multitemporal (1975-2030).European Commission, Joint Research Centre (JRC) PID:\u00a0http://data.europa.eu/89h/ab2f107a-03cd-47a3-85e5-139d8ec63283, doi:10.2905/AB2F107A-03CD-47A3-85E5-139D8EC63283\nPesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID:\u00a0http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA\nSchiavina M., Freire S., Carioli A., MacManus K. (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030).European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe, doi:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE\nSchiavina M., Freire S., Carioli A., MacManus K. (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030).European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe, doi:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE\nSchiavina M., Melchiorri M., Pesaresi M. (2023): GHS-SMOD R2023A - GHS settlement layers, application of the Degree of Urbanisation methodology (stage I) to GHS-POP R2023A and GHS-BUILT-S R2023A, multitemporal (1975-2030)European Commission, Joint Research Centre (JRC) PID: http://data.europa.eu/89h/a0df7a6f-49de-46ea-9bde-563437a6e2ba, doi:10.2905/A0DF7A6F-49DE-46EA-9BDE-563437A6E2BA", "urlMain": "https://human-settlement.emergency.copernicus.eu/ghs_ucdb_2024.php", "dateAccessed": "2024-12-02", "datePublished": "2024", "license": {"url": "https://commission.europa.eu/legal-notice_en", "name": "CC BY 4.0"}}]}