What is the largest country in the world based on the most suitable land area for human habitation?
Contents
Species distribution modelling (SDM) is widely used to predict suitable habitats of living organisms based on niche conservatism on a global scale.
I used a “Maxent” (machine-learning technique called “maximum entropy modelling”) to model comfortable habitat for Homo sapiens, based on the current location of settlements. Maxent software (version 3.4.1) was downloaded from biodiversityinformatics.amnh.org
Maxent software for modelling species niches and distributions by applying a machine-learning technique called maximum entropy modelling. From a set of environmental (e.g., climatic) grids and georeferenced occurrence localities, the model expresses a probability distribution where each grid cell has predicted suitability of conditions for the species. For the map cells predicted using Maxent, cells with values of 1 had the highest degree of habitat suitability, while cells with values of 0 had the lowest. Habitat suitability was determined based on the climatic similarity to sites where the species already occur. The predictive precision of Maxent was based on the area under the curve (AUC) of the receiver operating characteristic (ROC), which regards each value of the prediction result as a possible threshold; the corresponding sensitivity and specificity were obtained through calculations. AUC ranges from 0.5 (lowest predictive ability or not different from a randomly selected predictive distribution) to 1 (highest predictive ability).
I selected towns and cities in the world with 100, 1000, 10000 and 100000 inhabitants and used 19 bioclimatic variables to model the potentially suitable environmental distribution of Homo sapiens. Bioclimatic variables were downloaded from the global database WorldClim (www.worldclim.org) at a spatial resolution of 30 arcseconds.

The MaxEnt model generated continuous probability values for the presence of Homo sapiens, ranging from 0 to 1. To delineate the presence/absence map of Homo sapiens, those continuous probability values were converted to the binary prediction based on a threshold probability value. This threshold probability was determined according to the ‘maximum training sensitivity plus specificity’ criterion.
The MaxEnt model for Homo sapiens showed a reliable prediction with an AUC of 0.684 (settlements with 100 inhabitants), 0.671 (1000) 0.709 (10,000), 0.778 (settlements with 100,000 inhabitants), higher than the 0.5 of a random model.
The most crucial bioclimatic variable determining the geographical distribution of Homo sapiens is bio 1 (Annual Mean Temperature).
Bioclimatic variables determining the geographical distribution of humans
Variable | Percent contribution | Permutation importance |
---|---|---|
Annual Mean Temperature (bio 1) | 51.5 | 46.3 |
Mean Temperature of Warmest Quarter (bio 10) | 14.5 | 7.8 |
Mean Diurnal Range (bio 2) | 12.1 | 10.5 |
Annual Precipitation (bio 12) | 5.4 | 2.3 |
Precipitation of Wettest Month (bio 13) | 4.2 | 5.2 |
Isothermality (bio 3) | 3.2 | 5.8 |
Precipitation of Wettest Quarter (bio 16) | 1.3 | 0.6 |
Precipitation of Coldest Quarter (bio 19) | 1.2 | 1.8 |
Temperature Seasonality (bio 4) | 1.2 | 2.4 |
Precipitation Seasonality (bio 15) | 1.1 | 2.9 |
Mean Temperature of Wettest Quarter (bio 8) | 1 | 2.2 |
Precipitation of Warmest Quarter (bio 18) | 1 | 0.7 |
Mean Temperature of Coldest Quarter (bio 11) | 0.8 | 3.7 |
Temperature Annual Range (bio7=bio5-bio6) | 0.4 | 2.5 |
Temperature Seasonality (bio 5) | 0.4 | 2.6 |
Min Temperature of Coldest Month( bio 6) | 0.3 | 1 |
Mean Temperature of Driest Quarter (bio 9) | 0.3 | 1.4 |
Precipitation of Driest Quarter (bio 17) | 0.2 | 0.1 |
Precipitation of Driest Month (bio 14) | 0.1 | 0.1 |
The most suitable habitats for Homo sapiens
Brazil is the biggest country in the World
The largest countries in the world by area suitable for a comfortable life
Country | Area, km2 | Density, persons per sq. km. |
---|---|---|
Brazil | 7898248 | 23.65469933 |
The United States | 6991005 | 42.89030075 |
China | 4843361 | 271.0880127 |
Australia | 4776039 | 4.252520084 |
Russia | 4307021 | 33.42290115 |
India | 2944274 | 385.2909851 |
The Democratic Republic of the Congo | 2313982 | 25.38500023 |
Argentina | 2166524 | 17.8845005 |
Mexico | 1833246 | 56.87530136 |
Canada | 1814045 | 17.78930092 |
Kazakhstan | 1705307 | 8.919569969 |
Indonesia | 1574702 | 143.5590057 |
Sudan | 1378900 | 26.76029968 |
Iran (Islamic Republic of) | 1233109 | 56.29719925 |
Angola | 1230781 | 13.07719994 |
South Africa | 1127262 | 42.52659988 |
Ethiopia | 1103404 | 71.58380127 |
Saudi Arabia | 1044361 | 22.6093998 |
Colombia | 1004135 | 4.476069927 |
United Republic of Tanzania | 940153 | 40.92720032 |
Bolivia | 923239 | 9.945440292 |
Peru | 904861 | 30.14189911 |
Venezuela | 858221 | 31.14069939 |
Nigeria | 857719 | 164.8049927 |
Mozambique | 783826 | 26.19540024 |
Turkey | 760249 | 95.98130035 |
Namibia | 748179 | 2.69946003 |
Zambia | 718028 | 15.98589993 |
Burma | 662999 | 72.34889984 |
Ukraine | 596350 | 78.67449951 |
Mali | 590550 | 19.66150093 |
Madagascar | 587809 | 31.7154007 |
Kenya | 578771 | 61.50780106 |
Botswana | 576386 | 3.185260057 |
Central African Republic | 557524 | 7.517930031 |
Somalia | 547183 | 14.97929955 |
France | 538044 | 113.3560028 |
Chad | 520160 | 19.5048008 |
Thailand | 511147 | 123.2580032 |
Spain | 502900 | 86.29450226 |
Chile | 476065 | 34.22869873 |
Cameroon | 464266 | 38.32960129 |
Afghanistan | 444905 | 56.34329987 |
Pakistan | 424016 | 372.8179932 |
Papua New Guinea | 399083 | 15.20919991 |
Paraguay | 398814 | 14.80480003 |
Zimbabwe | 386007 | 33.98820114 |
Japan | 361710 | 353.5889893 |
Germany | 356424 | 231.8930054 |
Congo | 343945 | 10.49540043 |
Turkmenistan | 343449 | 14.07269955 |
Niger | 338183 | 3.922189951 |
Uzbekistan | 335833 | 79.18560028 |
Viet Nam | 323885 | 262.5270081 |
Cote d’Ivoire | 320375 | 58.00920105 |
Morocco | 317475 | 96.05480194 |
Poland | 311412 | 122.6529999 |
Italy | 289100 | 20.28580093 |
Iraq | 286003 | 97.88700104 |
Mauritania | 285533 | 10.37749958 |
Yemen | 282036 | 74.79779816 |
Philippines | 278835 | 303.2839966 |
Malaysia | 273477 | 93.80310059 |
Sweden | 272992 | 33.10739899 |
Burkina Faso | 272333 | 51.1629982 |
Algeria | 261666 | 125.5579987 |
Gabon | 260110 | 4.962100029 |
Egypt | 253863 | 286.9649963 |
Uganda | 241814 | 119.7080002 |
United Kingdom | 239574 | 251.4660034 |
Ghana | 238532 | 9.447369576 |
Romania | 236747 | 91.35299683 |
Lao People’s Democratic Republic | 229923 | 24.63389969 |
New Zealand | 225904 | 18.1364994 |
Libyan Arab Jamahiriya | 213145 | 27.76619911 |
Guyana | 210422 | 3.514230013 |
Finland | 210017 | 24.97890091 |
Belarus | 207724 | 47.15530014 |
Guinea | 207170 | 43.45539856 |
Senegal | 195669 | 6.015429974 |
Syrian Arab Republic | 182108 | 103.7509995 |
Cambodia | 181681 | 76.8132019 |
Uruguay | 177747 | 18.71050072 |
Ecuador | 172098 | 75.89279938 |
Norway | 155983 | 29.73940086 |
Suriname | 144975 | 3.121010065 |
Bangladesh | 134637 | 113.8479996 |
Nicaragua | 127660 | 42.78969955 |
Greece | 127595 | 86.99189758 |
Eritrea | 119257 | 37.95769882 |
Malawi | 118522 | 111.5920029 |
Nepal | 117598 | 230.3919983 |
Benin | 116066 | 73.15059662 |
Honduras | 111721 | 6.117119789 |
Bulgaria | 109725 | 70.58180237 |
Guatemala | 108718 | 116.9039993 |
Cuba | 107517 | 104.7269974 |
Korea, Democratic People’s Republic of | 106665 | 221.3999939 |
Oman | 98887 | 25.3526001 |
Korea, Republic of | 95774 | 499.8210144 |
Hungary | 92989 | 108.4690018 |
Portugal | 90836 | 115.9039993 |
Mongolia | 89590 | 28.8057003 |
Serbia | 87722 | 112.4349976 |
Liberia | 83933 | 41.00650024 |
French Guiana | 83435 | 2.302380085 |
Kyrgyzstan | 82617 | 62.98400116 |
Azerbaijan | 82016 | 101.8339996 |
Tunisia | 80647 | 125.2949982 |
Czech Republic | 78752 | 129.4160004 |
Panama | 73260 | 44.11000061 |
Sierra Leone | 71088 | 78.58429718 |
Austria | 70602 | 117.4469986 |
Western Sahara | 70504 | 6.246850014 |
United Arab Emirates | 69092 | 59.40330124 |
Ireland | 68312 | 60.65250015 |
Sri Lanka | 65517 | 291.8439941 |
Lithuania | 64977 | 52.71210098 |
Latvia | 64420 | 35.73099899 |
Tajikistan | 62602 | 104.6330032 |
Iceland | 61426 | 4.814439774 |
Togo | 57103 | 109.2509995 |
Croatia | 55451 | 8.208129883 |
Jordan | 55218 | 100.4029999 |
Georgia | 53897 | 82.99919891 |
Bosnia and Herzegovina | 51539 | 75.96649933 |
Costa Rica | 49838 | 86.82589722 |
Slovakia | 48648 | 110.7340012 |
Dominican Republic | 47866 | 197.8359985 |
Estonia | 44917 | 29.92880058 |
Denmark | 41588 | 130.253006 |
Taiwan | 35693 | 644.3839722 |
Netherlands | 34599 | 47.19120026 |
Republic of Moldova | 33693 | 115.0579987 |
Guinea-Bissau | 33121 | 48.21500015 |
Switzerland | 30782 | 241.1929932 |
Belgium | 30626 | 339.5169983 |
Lesotho | 30306 | 65.36100006 |
Albania | 28054 | 112.4160004 |
Burundi | 27182 | 289.1170044 |
Haiti | 26680 | 348.4370117 |
Equatorial Guinea | 26649 | 18.16570091 |
Bhutan | 26452 | 24.08180046 |
Rwanda | 25117 | 367.631012 |
The former Yugoslav Republic of Macedonia | 24858 | 81.81089783 |
Solomon Islands | 23992 | 19.69070053 |
Armenia | 23633 | 127.6880035 |
Belize | 21672 | 12.71440029 |
Djibouti | 21225 | 37.88959885 |
El Salvador | 20510 | 325.1270142 |
Slovenia | 20309 | 98.45020294 |
Israel | 20041 | 333.9169922 |
New Caledonia | 18102 | 12.93700027 |
Fiji | 17404 | 47.57789993 |
Swaziland | 17122 | 65.67739868 |
Timor-Leste | 14503 | 73.59059906 |
Montenegro | 13459 | 45.1719017 |
Vanuatu | 11885 | 18.12080002 |
Falkland Islands (Malvinas) | 10963 | 0.271367013 |
Bahamas | 10855 | 29.78300095 |
Qatar | 10732 | 74.18800354 |
Jamaica | 10707 | 250.5339966 |
Gambia | 10596 | 152.6069946 |
Lebanon | 9979 | 40.19179916 |
Kuwait | 9890 | 223.802002 |
Cyprus | 9023 | 92.68769836 |
Puerto Rico | 8830 | 446.973999 |
French Southern and Antarctic Lands | 6881 | 0 |
Palestine | 6255 | 601.4400024 |
Brunei Darussalam | 5606 | 66.68409729 |
Trinidad and Tobago | 4914 | 269.3779907 |
Cape Verde | 3368 | 150.477005 |
Samoa | 2664 | 69.0109024 |
Luxembourg | 2583 | 176.776001 |
Reunion | 2518 | 311.8190002 |
Greenland | 2478 | 23.19409943 |
Mauritius | 1966 | 631.3189697 |
Guadeloupe | 1595 | 274.8609924 |
Comoros | 1580 | 505.0010071 |
French Polynesia | 1475 | 173.3099976 |
Faroe Islands | 1284 | 37.5428009 |
Martinique | 1075 | 368.2749939 |
Sao Tome and Principe | 982 | 155.4199982 |
Hong Kong | 859 | 8215.849609 |
Dominica | 719 | 94.33519745 |
Netherlands Antilles | 714 | 261.053009 |
South Georgia South Sandwich Islands | 709 | 0.042313099 |
Еland Islands | 654 | 44.66970062 |
Saint Lucia | 627 | 25.71610069 |
Micronesia, Federated States of | 567 | 194.1060028 |
Bahrain | 562 | 1289.660034 |
Guam | 549 | 30.70490074 |
Tonga | 545 | 182.3139954 |
Isle of Man | 536 | 146.1880035 |
Singapore | 531 | 8149.660156 |
Barbados | 444 | 657.507019 |
Antigua and Barbuda | 424 | 195.8470001 |
Palau | 404 | 49.81930161 |
Northern Mariana Islands | 387 | 207.3849945 |
Grenada | 376 | 279.8859863 |
Saint Vincent and the Grenadines | 375 | 317.6990051 |
Turks and Caicos Islands | 375 | 65.22399902 |
Andorra | 363 | 202.4329987 |
Mayotte | 343 | 0.620990992 |
Seychelles | 325 | 263.1749878 |
United States Virgin Islands | 316 | 352.5570068 |
Saint Helena | 303 | 21.11879921 |
Malta | 296 | 1360.189941 |
Niue | 244 | 6.688519955 |
Saint Kitts and Nevis | 243 | 202.2140045 |
Cayman Islands | 230 | 198.2220001 |
Saint Pierre and Miquelon | 213 | 29.79339981 |
Heard Island and McDonald Islands | 193 | 0 |
Aruba | 184 | 559.2230225 |
Cook Islands | 179 | 78.12290192 |
American Samoa | 173 | 370.2369995 |
Liechtenstein | 170 | 203.5180054 |
Kiribati | 151 | 609.2910156 |
British Virgin Islands | 109 | 201.9819946 |
Jersey | 109 | 918.1829834 |
Wallis and Futuna Islands | 102 | 147.8329926 |
Population density
Alex Egoshin
www.vividmaps.com
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– Find cities with a similar climate