World's largest cities

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Lua error in package.lua at line 80: module 'strict' not found. Determining the world's largest cities depends on which definitions of city are used. The United Nations uses three definitions for what constitutes a city, as not all cities may be classified using the same criteria.[1] Cities may be defined by the extent of their urban area, the metropolitan region, and the city proper.[1]

Common methods for defining the boundaries of a city

Urban areas

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A city can be defined as a conditionally contiguous urban area, without regard to territorial or other boundaries inside an urban area. UNICEF[1] defines urban area as follows:

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The definition of "urban" varies from country to country, and, with periodic reclassification, can also vary within one country over time, making direct comparisons difficult. An urban area can be defined by one or more of the following: administrative criteria or political boundaries (e.g., area within the jurisdiction of a municipality or town committee), a threshold population size (where the minimum for an urban settlement is typically in the region of 2,000 people, although this varies globally between 200 and 50,000), population density, economic function (e.g., where a significant majority of the population is not primarily engaged in agriculture, or where there is surplus employment) or the presence of urban characteristics (e.g., paved streets, electric lighting, sewerage).

Metropolitan area

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A city can be defined by the habits of its demographic population, as by metropolitan area, labour market area, or similar in a metropolitan area. UNICEF[1] defines metropolitan area as follows:

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A formal local government area comprising the urban area as a whole and its primary commuter areas, typically formed around a city with a large concentration of people (i.e., a population of at least 100,000). In addition to the city proper, a metropolitan area includes both the surrounding territory with urban levels of residential density and some additional lower-density areas that are adjacent to and linked to the city (e.g., through frequent transport, road linkages or commuting facilities).

City proper (administrative)

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A city can be defined by its administrative boundaries (city proper). World Urbanization Prospects, a UN publication, defines population of a city proper as "the population living within the administrative boundaries of a city or controlled directly from the city by a single authority." UNICEF[1] defines city proper as "the population living within the administrative boundaries of a city, e.g., Washington, D.C.". A city proper is a locality defined according to legal or political boundaries and an administratively recognised urban status that is usually characterised by some form of local government.[2][3][4] Cities proper and their boundaries and population data may not include suburbs.[5]

The use of city proper as defined by administrative boundaries may not include suburban areas where an important proportion of the population working or studying in the city lives.[5] Because of this definition, the city proper population figure may differ greatly with the urban area population figure, as many cities are amalgamations of smaller cities (Australia), and conversely, many Chinese cities govern territories that extend well beyond the traditional "city proper" into suburban and rural areas.[6]

List

City Country Image City proper population Urban area population[7] Metropolitan area population
Shanghai  China PudongSkyline-pjt (cropped).jpg 24,256,800[8] 23,416,000[lower-alpha 1] 34,750,000[9]
Karachi  Pakistan Karachi Clifton Skyline.JPG 23,500,000[10] 25,400,000[11] 25,400,000
Beijing  China View of Beijing.jpg 21,516,000[12] 21,009,000 21,148,000[13]
São Paulo  Brazil Ponte estaiada Octavio Frias - Sao Paulo.jpg 21,292,893[14] 20,365,000 36,842,102[15]
Delhi  India LotusDelhi.jpg 16,787,941[16] 24,998,000 21,753,486[17]
Lagos  Nigeria Lagos Island.jpg 16,060,303[note 1] 13,123,000 21,000,000[20]
Istanbul  Turkey Halic.png 14,657,000[21] 15,328,000[22] 16,703,000[23]
Tokyo  Japan Skyscrapers of Shinjuku 2009 January (revised).jpg 13,297,629[24] 37,843,000 36,923,000[25]
Mumbai  India Mumbai 03-2016 10 skyline of Lotus Colony.jpg 12,478,447[17] 17,712,000 20,748,395[17]
Moscow  Russia 125px 12,197,596[26] 16,170,000
Guangzhou  China Guangzhou skyline.jpg 12,080,500[27] 20,597,000 23,900,000[28]
Shenzhen  China Shenzhen CBD and River.jpg 10,780,000[29] 12,084,000 10,630,000[30]
Kinshasa  Democratic Republic of the Congo Kinshasa-Gombe, from CCIC.JPG 10,130,000[31] 13,265,000
Cairo  Egypt Kairo 001.jpg 10,230,350[32] 18,290,000 22,439,541
Jakarta  Indonesia Jakarta Panorama.jpg 10,075,310[33] 30,539,000 30,075,310[34]
Lahore  Pakistan Kalma Underpass1.jpg 10,052,000
Seoul  South Korea View of YangJe-Cheon.jpg 9,995,784[35] 12,700,000 25,520,000[36]
Mexico City  Mexico Ciudad.de.Mexico.City.Distrito.Federal.DF.Paseo.Reforma.Skyline.jpg 8,974,724[37] 20,063,000 21,178,959[38]
Lima  Peru City of Lima, Peru.jpg 8,852,000[39] 10,750,000 9,886,647[40]
London  United Kingdom Canary Wharf Skyline 2, London UK - Oct 2012.jpg 8,538,689[41] 10,236,000 14,031,830[42]
New York  United States LowerManhattanSept2013.png 8,491,079[43] 20,630,000 20,092,883[44]
Bengaluru  India 125px 8,425,970[17] 9,807,000 8,728,906[17]
Bangkok  Thailand The Baiyoke Tower II in Bangkok, Thailand.jpg 8,280,925[45] 14,998,000 8,305,218[46]
Dongguan  China Dongguan -03.jpg 8,220,207[47]
Chongqing  China SkylineOfChongqing.jpg 8,189,800[lower-alpha 2]
Nanjing  China Nanjingpanorama001.jpg 8,187,828[49]
Tehran  Iran North Tehran Towers.jpg 8,154,051[50] 13,532,000 14,595,904[51]
Shenyang  China Shenyang Qingnian Street.JPG 8,106,171[52]
Bogotá  Colombia Centro-Internacional-Bogotá.jpg 7,776,845[53] 7,878,783[54]
Ho Chi Minh City  Vietnam Một khúc sông Sài Gòn.JPG 7,681,700[55]
Ningbo  China Juncture of three main rivers in Ningbo China.jpg 7,605,689[56]
Hong Kong  Hong Kong Hong Kong view from The Peak 01.jpg 7,298,600[57] 7,331,699[58]
Baghdad  Iraq Haifa street, as seen from the medical city hospital across the tigres.jpg 7,180,889[59]
Chennai  India Chennai India.jpg 7,088,000[60] 9,373,521[17]
Changsha  China The Huángxīng Lù Commercial Pedestrian Street in Changsha.jpg 7,044,118
Dhaka  Bangladesh Dhaka-skyline-aymash.jpg 6,970,105[61] 15,669,000 18,305,671[62][not in citation given]
Wuhan  China WuhanSkyline.jpg 6,886,253[63]
Tianjin  China 炫彩津门99海河夜景.jpg 6,859,779[64] 10,920,000
Hyderabad  India MindSpace campus in Hyderabad, India.jpg 6,809,970[17] 7,749,334[17]
Hanoi  Vietnam Hanoi Cityscape.jpg 6,844,100[55]
Faisalabad  Pakistan Clock Tower Faisalabad by Usman Nadeem.jpg 6,480,765[65]
Rio de Janeiro  Brazil Vista aérea Centro do Rio de Janeiro RJ.jpg 6,429,923[66] 12,727,000 13,973,505[14]
Foshan  China Downtown of Guicheng.jpg 6,151,622[67][68]
Zunyi  China Zunyi.JPG 6,127,009
Santiago  Chile Santiago de Chile.jpg 5,743,719[69] 6,683,852[70]
Riyadh  Saudi Arabia Riyadh 1337.jpg 5,676,621[71]
Ahmedabad  India Amdavad Aerial.jpg 5,570,585[17] 6,352,254[17]
Singapore  Singapore Singapore CBD skyline from Esplanade at dusk.jpg 5,535,000[72]
Shantou  China China-shantou03.jpg 5,391,028[73]
Yangon  Myanmar 125px 5,214,000[74]
Saint Petersburg  Russia Petersburg-square.jpg 5,191,690[75]
Abidjan  Ivory Coast Plateau Centre-est.jpg 4,765,000[76]
Chengdu  China Jiuyanqiao.jpg 4,741,929[77] 10,376,000
Alexandria  Egypt Alexandria - Egypt.jpg 4,616,625[78]
Kolkata  India Victoria Memorial Kolkata panorama.jpg 4,486,679[17] 14,667,000 14,617,882[17]
Ankara  Turkey Ankara and mosque wza.jpg 5,271,000[79] 4,585,000[80] 4,919,000[81]
Xi'an  China 1 xian china wild goose pagoda view.JPG 4,467,837[82]
Surat  India GauravPath1.jpg 4,462,002[17]
Johannesburg  South Africa Johannesburg CBD.jpg 4,434,827[83]
Dar es Salaam  Tanzania Dar es Salaam aerial.jpg 4,364,541[84]
Suzhou  China Panmen Scenic Area 1.jpg 4,327,066[85]
Harbin  China Kitayskaya Street.jpg 4,280,701[86][87]
Giza  Egypt Egipt 383.jpg 4,239,988[88] 15,600,000
Zhengzhou  China Hnyszx.png 4,122,087[89]
New Taipei City  Taiwan Roctpchall.jpg 3,954,929[90]
Los Angeles  United States LA Skyline Mountains2.jpg 3,884,307[91] 15,058,000 13,262,220[44]
Cape Town  South Africa Central Cape Town.jpg 3,740,026[83]
Yokohama  Japan Minato Mirai In Blue.jpg 3,680,267[92]
Hangzhou  China Hangzhou-yellow-dragon-stad.jpg 3,560,391[93]
Xiamen  China View of Urban Area of Amoy from Mount Riguangyan.jpg 3,531,347[94]
Quanzhou  China Lingshan Islamic Cemetery - city view - DSCF8486.JPG 3,520,846[95]
Berlin  Germany PotsdamerPlatz Vogelperspektive 2004 1.jpg 3,517,424[96]
Busan  South Korea August Afternoon in Haeundae 2.jpg 3,510,833[36]
Rawalpindi  Pakistan AWT building.jpg 3,510,000[citation needed]
Jeddah  Saudi Arabia Jeddeh4.jpg 3,456,259[97]
Durban  South Africa VWestDurban.jpg 3,442,361[83]
Hyderabad  Pakistan Citynazimoffice.JPG 3,429,471[98]
Kabul  Afghanistan Khair Khana in 2012.jpg 3,414,100[99]
Casablanca  Morocco CasablancaFAR.jpg 3,359,818[100]
Hefei  China Hefei Street Scene.jpg 3,352,076[101]
Pyongyang  North Korea 0322 Pyongyang Turm der Juche Idee Aussicht.jpg 3,255,388[102]
Madrid  Spain Gran Vía (Madrid) 1.jpg 3,207,247[103] 6,378,297[42]
Peshawar  Pakistan Khyber pass.jpeg 3,201,000[citation needed]
Ekurhuleni  South Africa Germiston CBD.jpg 3,178,470[83]
Nairobi  Kenya NBO5.jpg 3,138,369[104]
Zhongshan  China Zhongshan City -02.jpg 3,121,275[105]
Pune  India AmonoraTownCentre.jpg 3,115,431[17]
Addis Ababa  Ethiopia Aerials Ethiopia 2009-08-27 15-26-13.JPG 3,103,673[106]
Jaipur  India World Trade Park Jaipur in 2012.jpg 3,073,350[17]
Buenos Aires  Argentina Banco de la Nación Argentina, Buenos Aires, Argentina, 2014-11-20 WTourAR AA 03.jpg 3,054,300[107] 14,122,000 13,074,000[108]
Lucknow  India Night View of the Ambedkar Memorial at Lucknow.jpg 3,001,475[17] 6,500,000[17]
Wenzhou  China Vue générale de Wenzhou.JPG 3,039,439[109]
Osaka  Japan Osaka Central Public Hall in 201504 007.JPG 17,444,000 19,342,000[25]
Paris  France 10,858,000 12,005,077[42]
Manila  Philippines 1,652,171[110] 12,877,253[111] 24,123,000
Izmir  Turkey 4,168,000[112] 3,019,000[113] 3,575,000[114]
Chicago  United States 9,554,598[44]
Nagoya  Japan 10,177,000 9,107,000[25]
Taipei  Taiwan 7,045,488[115]
Taipei  Taiwan 6,954,330[44]
Luanda  Angola 6,542,944[116]
Houston  United States 6,490,180[44]
Philadelphia  United States 6,051,170[44]
  1. Shanghai, Hangzhou, Nanjing, Suzhou, Wuxi, Ningbo, Changzhou, Shaoxing, and urban area of Zhangjiaggang-Jiangyin within the prefecture-level cities of Suzhou and Wuxi are treated as separate urban areas which constitute the Yangtze River Delta economic zone. Huai'an (1,856,000; 148 km2), Xuzhou (1,246,000; 233 km2), Nantong (1,036,000; 233 km2), Lianyungang (985,000; 155 km2), Zhenjiang (983,000; 168 km2), Yancheng (797,000; 207 km2), Huzhou (690,000; 111 km2), Taizhou (in Jiangsu Province; 300,000; 117 km2) and Suqian (220,000; 36 km2), as well as urban areas of Yangzhou (1,593,000; 233 km2) and Gaoyou (180,000; 39 km2) within the prefecture-level city of Yangzhou, urban areas of Kunshan (1,596,000; 492 km2), Changshu (1,139,000; 285 km2) and Taicang (523,000; 117 km2) within the prefecture-level city of Suzhou, urban areas of Cixi (1,200,000; 298 km2) and Yuyao (650,000; 122 km2) within the sub-provincial city of Ningbo, urban areas of Jiaxing (1,044,000; 259 km2) and Tongxiang (510,000; 52 km2) within the prefecture-level city of Jiaxing, urban areas of Wenling (510,000; 52 km2), Jiaojiang (375,000; 41 km2) and Huangyan (200,000; 34 km2) within the prefecture-level city of Taizhou (in Zhejiang Province), urban areas of Zhuji (500,000; 117 km2) and Shangyu (400,000; 158 km2) within the prefecture-level city of Shaoxing, urban areas of Yiwu-Dongyang (925,000; 233 km2), Jinhua (520,000; 186 km2), Yongkang (500,000; 223 km2), Dongyang (260,000; 104 km2) and Lanxi (220,000; 34 km2) within the prefecture-level city of Jinhua, and urban area of Fuyang (450,000; 49 km2) within the sub-provincial city of Hangzhou are also excluded.
  2. Sum of the 2014 population estimates for the "urban-function core district" and "urban-function extended district" of Chongqing, which were 3,677,600 and 4,512,200 respectively.[48] See also the next note.

See also

Notes

  1. Lagos consists 16 out of Lagos State's 20 LGA, which excludes: Badagry, Epe, Ibeju-Lekki and Ikorodu.[18][19]

References

  1. 1.0 1.1 1.2 1.3 1.4 Lua error in package.lua at line 80: module 'strict' not found.
  2. Lua error in package.lua at line 80: module 'strict' not found.
  3. Lua error in package.lua at line 80: module 'strict' not found.
  4. Lua error in package.lua at line 80: module 'strict' not found.
  5. 5.0 5.1 Lua error in package.lua at line 80: module 'strict' not found.
  6. Lua error in package.lua at line 80: module 'strict' not found.
  7. Lua error in package.lua at line 80: module 'strict' not found.
  8. Lua error in package.lua at line 80: module 'strict' not found.
  9. National Development and Reform Commission (PRC)
  10. Lua error in package.lua at line 80: module 'strict' not found.
  11. Lua error in package.lua at line 80: module 'strict' not found.
  12. Lua error in package.lua at line 80: module 'strict' not found.
  13. (Chinese) 国家统计局北京调查总队, "北京市2013年国民经济和社会发展统计公报", 北京市统计局 2014-02-13
  14. 14.0 14.1 Lua error in package.lua at line 80: module 'strict' not found.
  15. Lua error in package.lua at line 80: module 'strict' not found.
  16. Lua error in package.lua at line 80: module 'strict' not found.
  17. 17.00 17.01 17.02 17.03 17.04 17.05 17.06 17.07 17.08 17.09 17.10 17.11 17.12 17.13 17.14 17.15 17.16 Lua error in package.lua at line 80: module 'strict' not found.
  18. Lua error in package.lua at line 80: module 'strict' not found.
  19. Lua error in package.lua at line 80: module 'strict' not found.
  20. Lua error in package.lua at line 80: module 'strict' not found.
  21. Turkish Statistical Institute - Address Based Population Record System, 2015
  22. Turkish Statistical Institute - Address Based Population Record System, 2015
  23. Turkish Statistical Institute - Address Based Population Record System, 2015
  24. Lua error in package.lua at line 80: module 'strict' not found.
  25. 25.0 25.1 25.2 Lua error in package.lua at line 80: module 'strict' not found.
  26. Lua error in package.lua at line 80: module 'strict' not found.
  27. Lua error in package.lua at line 80: module 'strict' not found.
  28. http://data.gzstats.gov.cn/gzStat1/chaxun/njsj.jsp
  29. Lua error in package.lua at line 80: module 'strict' not found.
  30. [1]
  31. Lua error in package.lua at line 80: module 'strict' not found.
  32. Lua error in package.lua at line 80: module 'strict' not found.
  33. Lua error in package.lua at line 80: module 'strict' not found.
  34. Lua error in package.lua at line 80: module 'strict' not found.
  35. Lua error in package.lua at line 80: module 'strict' not found.
  36. 36.0 36.1 Lua error in package.lua at line 80: module 'strict' not found.
  37. Lua error in package.lua at line 80: module 'strict' not found.
  38. Lua error in package.lua at line 80: module 'strict' not found.
  39. Lua error in package.lua at line 80: module 'strict' not found.
  40. Lua error in package.lua at line 80: module 'strict' not found.
  41. Lua error in package.lua at line 80: module 'strict' not found.
  42. 42.0 42.1 42.2 Lua error in package.lua at line 80: module 'strict' not found.
  43. Lua error in package.lua at line 80: module 'strict' not found.
  44. 44.0 44.1 44.2 44.3 44.4 44.5 Lua error in package.lua at line 80: module 'strict' not found.
  45. Lua error in package.lua at line 80: module 'strict' not found.
  46. http://service.nso.go.th/nso/nso_center/project/table/files/C-pop/2553/000/00_C-pop_2553_000_010000_00100.xls
  47. Lua error in package.lua at line 80: module 'strict' not found.
  48. Lua error in package.lua at line 80: module 'strict' not found.
  49. Lua error in package.lua at line 80: module 'strict' not found.
  50. Lua error in package.lua at line 80: module 'strict' not found.
  51. Lua error in package.lua at line 80: module 'strict' not found.
  52. Lua error in package.lua at line 80: module 'strict' not found.
  53. Lua error in package.lua at line 80: module 'strict' not found.
  54. Lua error in package.lua at line 80: module 'strict' not found.
  55. 55.0 55.1 Lua error in package.lua at line 80: module 'strict' not found.
  56. Lua error in package.lua at line 80: module 'strict' not found.
  57. Lua error in package.lua at line 80: module 'strict' not found.
  58. Lua error in package.lua at line 80: module 'strict' not found.
  59. Lua error in package.lua at line 80: module 'strict' not found.
  60. Lua error in package.lua at line 80: module 'strict' not found.
  61. Lua error in package.lua at line 80: module 'strict' not found.
  62. Bangladesh Bureau of Statistics - Community Report
  63. Lua error in package.lua at line 80: module 'strict' not found.
  64. Lua error in package.lua at line 80: module 'strict' not found.
  65. http://phonebookoftheworld.com/faisalabad/
  66. Lua error in package.lua at line 80: module 'strict' not found.
  67. Lua error in package.lua at line 80: module 'strict' not found.
  68. Districts of Changcheng, Nanhai, Shunde; see Foshan#Administration
  69. Lua error in package.lua at line 80: module 'strict' not found.
  70. Lua error in package.lua at line 80: module 'strict' not found.
  71. Lua error in package.lua at line 80: module 'strict' not found.
  72. Lua error in package.lua at line 80: module 'strict' not found.
  73. Lua error in package.lua at line 80: module 'strict' not found.
  74. Lua error in package.lua at line 80: module 'strict' not found.
  75. Rosstat. Оценка численности постоянного населения на 1 января 2015 г. (Russian)
  76. Lua error in package.lua at line 80: module 'strict' not found.
  77. Lua error in package.lua at line 80: module 'strict' not found.
  78. Lua error in package.lua at line 80: module 'strict' not found.
  79. Turkish Statistical Institute - Address Based Population Record System, 2015
  80. Turkish Statistical Institute - Address Based Population Record System, 2015
  81. Turkish Statistical Institute - Address Based Population Record System, 2015
  82. Lua error in package.lua at line 80: module 'strict' not found.
  83. 83.0 83.1 83.2 83.3 Lua error in package.lua at line 80: module 'strict' not found.
  84. Lua error in package.lua at line 80: module 'strict' not found.
  85. Lua error in package.lua at line 80: module 'strict' not found.
  86. Lua error in package.lua at line 80: module 'strict' not found.
  87. All city proper districts except Sōngběi; namely Dàolǐ, Nángǎng, Dàowài, Píngfáng, Xiāngfang; see Harbin#Administrative divisions
  88. Lua error in package.lua at line 80: module 'strict' not found.
  89. Sub-provincial City (Census 2010)
  90. Lua error in package.lua at line 80: module 'strict' not found.
  91. Lua error in package.lua at line 80: module 'strict' not found.
  92. Lua error in package.lua at line 80: module 'strict' not found.
  93. Lua error in package.lua at line 80: module 'strict' not found.
  94. Lua error in package.lua at line 80: module 'strict' not found.
  95. Following sections: Licheng District, Fengze District, Shishi City, Jinjiang City; see Quanzhou#Administrative divisions
  96. Lua error in package.lua at line 80: module 'strict' not found.
  97. Lua error in package.lua at line 80: module 'strict' not found.
  98. http://www.thenews.com.pk/Todays-News-13-13637-Sindh-population-surges-by-81.5-pc,-households-by-83.9-pc
  99. Lua error in package.lua at line 80: module 'strict' not found.
  100. Lua error in package.lua at line 80: module 'strict' not found.
  101. Lua error in package.lua at line 80: module 'strict' not found.
  102. United Nations Statistics Division; Preliminary results of the 2008 Census of Population of the Democratic People’s Republic of Korea conducted on 1–15 October 2008 (pdf-file) Retrieved on 2009-03-01.
  103. Lua error in package.lua at line 80: module 'strict' not found.
  104. Lua error in package.lua at line 80: module 'strict' not found.
  105. http://www.geohive.com/cntry/cn-44.aspx
  106. Lua error in package.lua at line 80: module 'strict' not found.
  107. Lua error in package.lua at line 80: module 'strict' not found.
  108. Lua error in package.lua at line 80: module 'strict' not found.
  109. Lua error in package.lua at line 80: module 'strict' not found.
  110. Lua error in package.lua at line 80: module 'strict' not found.
  111. Lua error in package.lua at line 80: module 'strict' not found.
  112. Turkish Statistical Institute - Address Based Population Record System, 2015
  113. Turkish Statistical Institute - Address Based Population Record System, 2015
  114. Turkish Statistical Institute - Address Based Population Record System, 2015
  115. Lua error in package.lua at line 80: module 'strict' not found.
  116. Lua error in package.lua at line 80: module 'strict' not found.