Vivid Maps

Maps that explain the World

Climate News 

What is the largest country in the world based on the most suitable land area for human habitation?

Alex 0 Comments

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 modeling. 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 the 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. Maxent’s predictive precision 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.

Human Settlements
Settlements with more than 100 inhabitants

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

VariablePercent contributionPermutation importance
Annual Mean Temperature (bio 1)51.546.3
Mean Temperature of Warmest Quarter (bio 10)14.57.8
Mean Diurnal Range (bio 2)12.110.5
Annual Precipitation (bio 12)5.42.3
Precipitation of Wettest Month (bio 13)4.25.2
Isothermality (bio 3)3.25.8
Precipitation of Wettest Quarter (bio 16)1.30.6
Precipitation of Coldest Quarter (bio 19)1.21.8
Temperature Seasonality (bio 4)1.22.4
Precipitation Seasonality (bio 15)1.12.9
Mean Temperature of Wettest Quarter (bio 8)12.2
Precipitation of Warmest Quarter (bio 18)10.7
Mean Temperature of Coldest Quarter (bio 11)0.83.7
Temperature Annual Range (bio7=bio5-bio6)0.42.5
Temperature Seasonality (bio 5)0.42.6
Min Temperature of Coldest Month( bio 6)0.31
Mean Temperature of Driest Quarter (bio 9)0.31.4
Precipitation of Driest Quarter (bio 17)0.20.1
Precipitation of Driest Month (bio 14)0.10.1

The most suitable habitats for Homo sapiens

Suitable habitats for Homo sapiens

In the map above, the pale green color indicates areas suitable for human habitation, obtained as a result of modeling using settlements data with a population of more than 1 million. Subsequent gradations in green color indicate the suitability of the area for Homo Sapiens habitation when using in the modeling of settlements data with a population of 100000, 10000, 1000, and 100 (dark green color).

Brazil is the biggest country in the World

Countries by area

The largest countries in the world by area suitable for a comfortable life

CountryArea, km2Density, persons per sq. km.
Brazil789824823.65469933
The United States699100542.89030075
China4843361271.0880127
Australia47760394.252520084
Russia430702133.42290115
India2944274385.2909851
The Democratic Republic of the Congo231398225.38500023
Argentina216652417.8845005
Mexico183324656.87530136
Canada181404517.78930092
Kazakhstan17053078.919569969
Indonesia1574702143.5590057
Sudan137890026.76029968
Iran (Islamic Republic of)123310956.29719925
Angola123078113.07719994
South Africa112726242.52659988
Ethiopia110340471.58380127
Saudi Arabia104436122.6093998
Colombia10041354.476069927
United Republic of Tanzania94015340.92720032
Bolivia9232399.945440292
Peru90486130.14189911
Venezuela85822131.14069939
Nigeria857719164.8049927
Mozambique78382626.19540024
Turkey76024995.98130035
Namibia7481792.69946003
Zambia71802815.98589993
Burma66299972.34889984
Ukraine59635078.67449951
Mali59055019.66150093
Madagascar58780931.7154007
Kenya57877161.50780106
Botswana5763863.185260057
Central African Republic5575247.517930031
Somalia54718314.97929955
France538044113.3560028
Chad52016019.5048008
Thailand511147123.2580032
Spain50290086.29450226
Chile47606534.22869873
Cameroon46426638.32960129
Afghanistan44490556.34329987
Pakistan424016372.8179932
Papua New Guinea39908315.20919991
Paraguay39881414.80480003
Zimbabwe38600733.98820114
Japan361710353.5889893
Germany356424231.8930054
Congo34394510.49540043
Turkmenistan34344914.07269955
Niger3381833.922189951
Uzbekistan33583379.18560028
Viet Nam323885262.5270081
Cote d’Ivoire32037558.00920105
Morocco31747596.05480194
Poland311412122.6529999
Italy28910020.28580093
Iraq28600397.88700104
Mauritania28553310.37749958
Yemen28203674.79779816
Philippines278835303.2839966
Malaysia27347793.80310059
Sweden27299233.10739899
Burkina Faso27233351.1629982
Algeria261666125.5579987
Gabon2601104.962100029
Egypt253863286.9649963
Uganda241814119.7080002
United Kingdom239574251.4660034
Ghana2385329.447369576
Romania23674791.35299683
Lao People’s Democratic Republic22992324.63389969
New Zealand22590418.1364994
Libyan Arab Jamahiriya21314527.76619911
Guyana2104223.514230013
Finland21001724.97890091
Belarus20772447.15530014
Guinea20717043.45539856
Senegal1956696.015429974
Syrian Arab Republic182108103.7509995
Cambodia18168176.8132019
Uruguay17774718.71050072
Ecuador17209875.89279938
Norway15598329.73940086
Suriname1449753.121010065
Bangladesh134637113.8479996
Nicaragua12766042.78969955
Greece12759586.99189758
Eritrea11925737.95769882
Malawi118522111.5920029
Nepal117598230.3919983
Benin11606673.15059662
Honduras1117216.117119789
Bulgaria10972570.58180237
Guatemala108718116.9039993
Cuba107517104.7269974
Korea, Democratic People’s Republic of106665221.3999939
Oman9888725.3526001
Korea, Republic of95774499.8210144
Hungary92989108.4690018
Portugal90836115.9039993
Mongolia8959028.8057003
Serbia87722112.4349976
Liberia8393341.00650024
French Guiana834352.302380085
Kyrgyzstan8261762.98400116
Azerbaijan82016101.8339996
Tunisia80647125.2949982
Czech Republic78752129.4160004
Panama7326044.11000061
Sierra Leone7108878.58429718
Austria70602117.4469986
Western Sahara705046.246850014
United Arab Emirates6909259.40330124
Ireland6831260.65250015
Sri Lanka65517291.8439941
Lithuania6497752.71210098
Latvia6442035.73099899
Tajikistan62602104.6330032
Iceland614264.814439774
Togo57103109.2509995
Croatia554518.208129883
Jordan55218100.4029999
Georgia5389782.99919891
Bosnia and Herzegovina5153975.96649933
Costa Rica4983886.82589722
Slovakia48648110.7340012
Dominican Republic47866197.8359985
Estonia4491729.92880058
Denmark41588130.253006
Taiwan35693644.3839722
Netherlands3459947.19120026
Republic of Moldova33693115.0579987
Guinea-Bissau3312148.21500015
Switzerland30782241.1929932
Belgium30626339.5169983
Lesotho3030665.36100006
Albania28054112.4160004
Burundi27182289.1170044
Haiti26680348.4370117
Equatorial Guinea2664918.16570091
Bhutan2645224.08180046
Rwanda25117367.631012
The former Yugoslav Republic of Macedonia2485881.81089783
Solomon Islands2399219.69070053
Armenia23633127.6880035
Belize2167212.71440029
Djibouti2122537.88959885
El Salvador20510325.1270142
Slovenia2030998.45020294
Israel20041333.9169922
New Caledonia1810212.93700027
Fiji1740447.57789993
Swaziland1712265.67739868
Timor-Leste1450373.59059906
Montenegro1345945.1719017
Vanuatu1188518.12080002
Falkland Islands (Malvinas)109630.271367013
Bahamas1085529.78300095
Qatar1073274.18800354
Jamaica10707250.5339966
Gambia10596152.6069946
Lebanon997940.19179916
Kuwait9890223.802002
Cyprus902392.68769836
Puerto Rico8830446.973999
French Southern and Antarctic Lands68810
Palestine6255601.4400024
Brunei Darussalam560666.68409729
Trinidad and Tobago4914269.3779907
Cape Verde3368150.477005
Samoa266469.0109024
Luxembourg2583176.776001
Reunion2518311.8190002
Greenland247823.19409943
Mauritius1966631.3189697
Guadeloupe1595274.8609924
Comoros1580505.0010071
French Polynesia1475173.3099976
Faroe Islands128437.5428009
Martinique1075368.2749939
Sao Tome and Principe982155.4199982
Hong Kong8598215.849609
Dominica71994.33519745
Netherlands Antilles714261.053009
South Georgia South Sandwich Islands7090.042313099
Еland Islands65444.66970062
Saint Lucia62725.71610069
Micronesia, Federated States of567194.1060028
Bahrain5621289.660034
Guam54930.70490074
Tonga545182.3139954
Isle of Man536146.1880035
Singapore5318149.660156
Barbados444657.507019
Antigua and Barbuda424195.8470001
Palau40449.81930161
Northern Mariana Islands387207.3849945
Grenada376279.8859863
Saint Vincent and the Grenadines375317.6990051
Turks and Caicos Islands37565.22399902
Andorra363202.4329987
Mayotte3430.620990992
Seychelles325263.1749878
United States Virgin Islands316352.5570068
Saint Helena30321.11879921
Malta2961360.189941
Niue2446.688519955
Saint Kitts and Nevis243202.2140045
Cayman Islands230198.2220001
Saint Pierre and Miquelon21329.79339981
Heard Island and McDonald Islands1930
Aruba184559.2230225
Cook Islands17978.12290192
American Samoa173370.2369995
Liechtenstein170203.5180054
Kiribati151609.2910156
British Virgin Islands109201.9819946
Jersey109918.1829834
Wallis and Futuna Islands102147.8329926

Population density

Population density

Alex Egoshin
www.vividmaps.com

Related post:
– Find cities with a similar climate

1 Star2 Stars (6 votes, average: 4.67 out of 5)
Loading...