NXS-GRX-BRA · South America · Regions

Mato Grosso

First-level unit, Brazil: people, area, the units inside and neighbours, with risk values when released.

Page GRX-BRA-REdition Baseline Edition 2026Evidence close 2026-09-30ISO BRA / BRStatus UN member stateValues not yet publishedMethod v1.0.0-draft
3,728,865
people (GHSL 2025)
909,630 km²
area
1.7%
of Brazil
142
units inside
01Map

Inside Mato Grosso

The 142 ADM2 units of Mato Grosso.

FIG 1 · 142 units inside Mato Grosso
Loading the map
Units rise with people per km² · GHSL 2025 raster · terrain · ADM1 ADM2Risk values when released
Lowest fifthLow fifthMiddle fifthHigh fifthHighest fifthNo data
Column height and colour show people per km² by unit, in quantile fifths among the units shown (the key on the map gives the breaks); units with no people on the grid are grey, not the lowest class; the raster beneath is the GHSL 2025 population grid. Source observations, not index values. Choose a humanitarian figure from the list to colour and raise the units by it; each figure shows its source on the unit page. Select a unit to drill into the units inside it; the path above the map climbs back.
02Figures

People, area and density

Source observations from open grids summed inside the boundary; not index values.

People · GHSL 2025

3,728,865

1.7% of Brazil.

People · WorldPop 2025

3,917,861

+5% against GHSL; the two grids differ in method.

Area

909,630 km²

4 people per km².

Code

BR-MT

Subdivision code as carried by the boundary source.

03Humanitarian data

Mato Grosso in humanitarian data

Source observations from the Humanitarian Data Exchange, matched to this unit by name, each with its reference date, provider and licence. They are not index values.

Population · 2022-12-31

3,658,649

people. UNFPA · Creative Commons Attribution for Intergovernmental Organisations (CC BY-IGO).

Poverty headcount · 2015-12-31

4.5%

of people in multidimensional poverty. Oxford Poverty & Human Development Initiative · Public Domain / No restrictions (CC0).

04Units

142 units inside Mato Grosso

Each unit has its own page.

Boundary licences: Creative Commons Attribution 2.5 Generic · Creative Commons Attribution 3.0 Intergovernmental Organisations (CC BY 3.0 IGO)

UnitCodePeople (GHSL)People (WorldPop)Area km²Per km²ShareCoast ≤ 10 m
Acorizal–5,7884,5201,015.6160.2%0
Água Boa–27,85232,5817,534.5440.7%0
Alta Floresta–58,65163,2958,988.2371.6%0
Alto Araguaia–26,20922,5735,417.2450.7%0
Alto Boa Vista–8,3456,0032,248.940.2%0
Alto Garças–13,07514,3673,877.7930.3%0
Alto Paraguai–12,4937,1431,852.3770.3%0
Alto Taquari–11,75712,0671,444.5780.3%0
Apiacás–11,0609,06420,576.5110.3%0
Araguaiana–3,8424,1186,448.1210.1%0
Araguainha–133274690.8500%0
Araputanga–18,70214,7361,612.54120.5%0
Arenápolis–13,92413,467416.5330.4%0
Aripuanã–26,67127,13025,207.8210.7%0
Barão de Melgaço–6,3024,46711,464.6110.2%0
Barra do Bugres–38,47128,8636,001.8961%0
Barra do Garças–75,03180,5859,111.682%0
Bom Jesus do Araguaia–7,6317,9914,291.0720.2%0
Brasnorte–21,05218,24816,020.4310.6%0
Cáceres–103,47493,76824,677.9942.7%0
Campinápolis–17,07215,5486,003.3730.5%0
Campo Novo do Parecis–37,57652,8769,467.2241%0
Campo Verde–48,32851,6905,413.2991.3%0
Campos de Júlio–7,03610,2286,812.110.2%0
Canabrava do Norte–5,4454,3213,466.2120.1%0
Canarana–22,50628,64310,926.4920.6%0
Carlinda–12,48610,3142,426.150.3%0
Castanheira–9,9957,4953,925.2730.3%0
Chapada dos Guimarães–21,79419,7456,476.6730.6%0
Cláudia–14,5349,0153,865.3340.4%0
Cocalinho–7,0106,54316,575.8100.2%0
Colíder–37,12432,6263,115.55121%0
Colniza–37,19625,36828,065.0711%0
Comodoro–22,90419,37621,600.7610.6%0
Confresa–33,39838,6905,824.1760.9%0
Conquista D’Oeste–4,0214,0942,692.8410.1%0
Cotriguaçu–21,1149,6539,458.6520.6%0
Cuiabá–667,810756,1753,277.7820417.7%0
Curvelândia–5,7974,986360.14160.2%0
Denise–10,3236,3921,284.0880.3%0
Diamantino–25,35223,2188,222.4130.7%0
Dom Aquino–9,2727,8962,231.6440.2%0
Feliz Natal–15,01910,50011,723.6610.4%0
Figueirópolis D’Oeste–5,0773,394890.8160.1%0
Gaúcha do Norte–9,2459,51416,997.9710.2%0
General Carneiro–5,5025,3123,723.1110.1%0
Glória D’Oeste–3,5902,823836.4240.1%0
Guarantã do Norte–38,83930,9434,752.2681%0
Guiratinga–16,0219,7925,062.130.4%0
Indiavaí–2,8142,060594.4550.1%0
Ipiranga do Norte–7,1238,6873,480.2220.2%0
Itanhangá–7,2088,2362,909.6120.2%0
Itaúba–4,4755,2774,549.5310.1%0
Itiquira–14,22512,5638,690.0920.4%0
Jaciara–32,28630,5502,405.91130.9%0
Jangada–9,8177,5991,303.2980.3%0
Jauru–11,6917,8701,363.4990.3%0
Juara–42,96539,71622,713.0321.1%0
Juína–46,37448,91926,292.6321.2%0
Juruena–16,7309,4912,791.0960.4%0
Juscimeira–12,26611,2682,728.6740.3%0
Lambari D’Oeste–7,4914,5701,772.2340.2%0
Lucas do Rio Verde–67,55592,3173,688.2181.8%0
Luciara–2,5392,6604,260.7710.1%0
Marcelândia–13,29311,07612,323.110.4%0
Matupá–18,08022,4895,240.2530.5%0
Mirassol d’Oeste–31,71028,1401,084.26290.8%0
Nobres–16,96215,7063,925.8640.4%0
Nortelândia–4,8643,3161,358.6540.1%0
Nossa Senhora do Livramento–17,90315,1975,456.2430.5%0
Nova Bandeirantes–16,34614,6609,632.2120.4%0
Nova Brasilândia–4,8953,7173,291.2410.1%0
Nova Canaã do Norte–14,35911,7015,980.0420.4%0
Nova Guarita–5,1814,3321,118.0650.1%0
Nova Lacerda–7,3357,2464,810.2420.2%0
Nova Marilândia–3,7843,9011,945.6520.1%0
Nova Maringá–9,1345,55511,600.6810.2%0
Nova Monte Verde–9,8588,4915,173.2120.3%0
Nova Mutum–48,80164,1019,566.3551.3%0
Nova Nazaré–4,1404,7964,052.710.1%0
Nova Olímpia–21,75116,2351,372.57160.6%0
Nova Santa Helena–4,6974,5452,386.2320.1%0
Nova Ubiratã–12,57212,53312,547.1410.3%0
Nova Xavantina–23,44026,3145,550.8940.6%0
Novo Horizonte do Norte–4,4153,135902.2350.1%0
Novo Mundo–9,6836,2695,812.3920.3%0
Novo Santo Antônio–2,5902,0554,409.5210.1%0
Novo São Joaquim–7,7047,6355,250.2310.2%0
Paranaíta–12,57412,1384,812.4730.3%0
Paranatinga–24,57529,17624,254.4910.7%0
Pedra Preta–19,06219,5214,061.6150.5%0
Peixoto de Azevedo–37,84534,00914,459.3631%0
Planalto da Serra–3,0793,2782,451.3610.1%0
Poconé–36,93231,88817,083.721%0
Pontal do Araguaia–7,6478,7342,746.2630.2%0
Ponte Branca–529613689.0510%0
Pontes e Lacerda–49,27455,6778,597.7561.3%0
Porto Alegre do Norte–13,46415,2043,989.230.4%0
Porto dos Gaúchos–2,6212,4246,889.1300.1%0
Porto Esperidião–12,5559,7705,829.1520.3%0
Porto Estrela–3,6652,9722,064.6220.1%0
Poxoréu–41,29546,9056,899.2761.1%0
Primavera do Leste–45,48274,3895,501.0181.2%0
Querência–18,49031,33217,854.810.5%0
Reserva do Cabaçal–3,1651,9821,348.6220.1%0
Ribeirão Cascalheira–10,39810,58211,398.4510.3%0
Ribeirãozinho–2,7422,818628.0240.1%0
Rio Branco–5,6564,368563.44100.1%0
Rondolândia–5,6413,50112,721.2300.1%0
Rondonópolis–244,962270,3124,703.86526.5%0
Rosário Oeste–20,00514,7697,193.9330.5%0
Salto do Céu–4,2243,5421,760.7620.1%0
Santa Carmem–4,9025,7623,86910.1%0
Santa Cruz do Xingu–2,4182,8915,674.4500.1%0
Santa Rita do Trivelato–3,9593,5704,753.6210.1%0
Santa Terezinha–8,6807,7026,492.6910.2%0
Santo Afonso–3,4482,2721,178.1730.1%0
Santo Antônio do Leste–4,4804,3623,416.110.1%0
Santo Antônio do Leverger–17,73617,1819,475.420.5%0
São Félix do Araguaia–11,80114,73416,78110.3%0
São José do Povo–4,9282,554449.46110.1%0
São José do Rio Claro–22,17213,9834,548.7550.6%0
São José do Xingu–6,4566,4317,489.3410.2%0
São José dos Quatro Marcos–22,27917,7691,293.4170.6%0
São Pedro da Cipa–4,4723,904345.28130.1%0
Sapezal–27,65332,52413,675.420.7%0
Serra Nova Dourada–2,0292,1121,506.4410.1%0
Sinop–151,967224,8653,959.12384%0
Sonora–19,46214,5314,198.8650.5%0
Sorriso–97,650131,6329,383.4102.6%0
Tabaporã–11,41510,1608,479.510.3%0
Tangará da Serra–108,782113,96011,647.7892.9%0
Tapurah–14,92116,2404,507.4730.4%0
Terra Nova do Norte–11,94310,2582,441.1750.3%0
Tesouro–4,9943,4194,300.510.1%0
Torixoréu–4,4994,3432,406.9320.1%0
União do Sul–4,2303,9344,600.4410.1%0
Vale de São Domingos–3,0672,3141,895.0120.1%0
Várzea Grande–254,310265,972946.022696.7%0
Vera–12,46011,8832,96640.3%0
Vila Bela da Santíssima Trindade–17,78218,24713,472.1310.5%0
Vila Rica–27,55519,7687,462.9840.7%0
05Exposure

Open exposure layers

Count of H3 resolution-3 cells whose centre falls in the unit and that carry each Natural Earth layer.

Urban areas
237.2 H3 cells
Ports
None at this resolution
Airports
1 H3 cells
Major roads
9,107.6 H3 cells
Railways
None at this resolution
Rivers and lakes
5,797.7 H3 cells
06Risk

Risk values

Values when released. Subnational risk values for Mato Grosso publish with the edition from The Global Risks Index. Until then, run a scenario on open data for Brazil.
07Neighbours

Neighbouring units

08Sources

Sources, credits and licences

ADM1 boundaries
geoBoundaries (William & Mary geoLab), gbOpen BRA ADM1, source: geoBoundaries, Wikimedia Commons, licence: Creative Commons Attribution 2.5 Generic · source · represents 2006
ADM2 boundaries
geoBoundaries (William & Mary geoLab), gbOpen BRA ADM2, source: Instituto Brasileiro de Geografia e Estatística (IBGE), OCHA ROLAC, licence: Creative Commons Attribution 3.0 Intergovernmental Organisations (CC BY 3.0 IGO) · source · represents 2020
Basemap
OpenFreeMap © OpenMapTiles (CC BY 4.0) · data © OpenStreetMap contributors (ODbL 1.0). Vector tiles requested by the reader’s browser, unmodified; the map falls back to plain land and sea when the host does not answer.
Terrain
Terrain Tiles (Mapzen, AWS Open Data), compiled from SRTM and other public elevation sources (NASA, USGS, ETOPO1, GMTED, EU-DEM under the Copernicus programme, Geoscience Australia, Kartverket, INEGI, LINZ, data.gov.uk). Display relief, not survey data.
People
GHSL 2025 population grid, European Commission Joint Research Centre (CC BY 4.0), shown at 0.05° and summed per unit; WorldPop 2025 (CC BY 4.0) as a second estimate. Units smaller than a grid cell take the density of the cell under them.
Countries
Natural Earth (public domain).
Elevation
GEBCO Compilation Group (2024) GEBCO 2024 Grid (public domain), reduced to 0.05°: the share of each cell’s land at or below 10 m, weighted by GHSL 2025 people for the low coastal zone.
Position
Boundaries are shown for location only and take no position on any boundary, name or status.
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