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

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When we look at a world map, Russia dominates with its massive territory. But how much of that land is actually comfortable for human living? I wanted to find out which countries have the most livable area, not just total area. The results surprised me.

Using climate data and global settlement patterns, I created maps that show where humans can live most comfortably. The process was straightforward: I looked at where people already live (from villages of 100 people to major cities), analyzed the climate conditions in these places, and then found other areas worldwide with similar conditions.

Here’s what our current settlement pattern looks like:

Looking at the settlement map, it’s clear that humans don’t spread evenly across the planet. Instead, we cluster in certain areas. Using the Species Distribution Modeling approach described in the methodology section below, I analyzed these settlement patterns against climate data. The results showed that temperature, particularly the average annual temperature, is the main factor that determines where we build our communities.

Based on this analysis, I created a map that marks all areas of the world with climatic conditions most comfortable for human habitation, based on spatial data on existing human settlements:

The colors tell an interesting story:

• The palest green shows areas suitable for major cities
• Medium green indicates good conditions for medium-sized towns
• The darkest green highlights areas perfect for smaller communities

Now here’s the surprising part – when we calculate the total habitable area for each country, Brazil comes out on top:

Here are the countries with the most land suitable for comfortable living:

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

This ranking looks quite different from the usual list of largest countries, doesn’t it? While Russia has the most total area, much of its territory lies in climate zones that aren’t ideal for human comfort.

But just because an area is habitable doesn’t mean it’s heavily populated. Look at this population density map:

The differences between where we could live comfortably and where we actually live tell us that climate isn’t everything. Historical events, economic opportunities, and political boundaries have shaped our settlement patterns just as much as comfortable temperatures and rainfall.

Think about it – this means our traditional way of measuring country size might not tell us much about usable territory. A smaller country with a favorable climate might actually offer more livable space than a larger one with extreme weather conditions.

For those interested in the technical details of how I created these maps and verified the findings, I’ve included the full methodology at the end of this post. The analysis used Maximum Entropy Modeling, a common tool in ecological research, and achieved reliable prediction scores well above random chance.

Methodology

For this analysis, I used Species Distribution Modelling (SDM) through MaxEnt software (version 3.4.1) from biodiversityinformatics.amnh.org. The model analyzed 19 bioclimatic variables from WorldClim (30 arcsecond resolution) at the locations of settlements with 100, 1000, 10000, and 100000 inhabitants.

The model generated probability values from 0 (lowest suitability) to 1 (highest suitability), which were converted to binary predictions using the ‘maximum training sensitivity plus specificity’ criterion. Model validation showed good predictive power 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.

Key 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

Maps were created using ArcGIS, incorporating both the MaxEnt results and current population data to show the relationship between potential and actual settlement patterns.

Here is the animated version of these maps.

What do you think about measuring countries this way? Does it change how you view different nations? Share your thoughts in the comments below.