NXS-GRX-BRA · South America · Regions

Santa Catarina

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
6,594,069
people (GHSL 2025)
94,847 km²
area
3.1%
of Brazil
299
units inside
01Map

Inside Santa Catarina

The 299 ADM2 units of Santa Catarina.

FIG 1 · 299 units inside Santa Catarina
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

6,594,069

3.1% of Brazil.

People · WorldPop 2025

7,031,182

+7% against GHSL; the two grids differ in method.

Area

94,847 km²

70 people per km².

Code

BR-SC

Subdivision code as carried by the boundary source.

Low coastal zone

739,136

people on land at or below 10 m, 11.2% of the unit (GEBCO 2024 and GHSL 2025).

03Humanitarian data

Santa Catarina 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

7,610,361

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

Poverty headcount · 2015-12-31

3%

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

04Units

299 units inside Santa Catarina

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
Abdon Batista–2,8972,547237.86120%0
Abelardo Luz–18,71117,965955.83200.3%0
Agrolândia–11,55712,197207.1560.2%0
Agronômica–4,7575,540129.67370.1%0
Água Doce–8,0946,4941,323.3460.1%0
Águas de Chapecó–8,7008,259139.45620.1%0
Águas Frias–2,8033,22776.96360%0
Águas Mornas–4,7705,742326.95150.1%0
Alfredo Wagner–10,99211,161735.12150.2%0
Alto Bela Vista–3,5883,061103.61350%0
Anchieta–7,6856,346233.29330.1%0
Angelina–6,0706,318500.4120.1%0
Anita Garibaldi–9,4418,527590.3160.1%0
Anitápolis–3,6273,867541.370.1%0
Antônio Carlos–8,04611,767235.18340.1%0
Apiúna–10,0949,518494.77200.1%0
Arabutã–7,4497,486133560.1%0
Araquari–35,43956,903387.58910.5%11,294
Araranguá–69,30676,693302.822291%37,508
Armazém–9,1989,416173.97530.1%0
Arroio Trinta–3,6393,50194.05390.1%0
Arvoredo–2,0642,24990.23230%0
Ascurra–8,1928,215112.99730.1%0
Atalanta–3,0892,91994.11330%0
Aurora–6,5227,526207.75310.1%0
Balneário Arroio do Silva–11,22215,55195.011180.2%9,407
Balneário Barra do Sul–11,37317,796108.991040.2%7,230
Balneário Camboriú–16,03319,21245.483530.2%29,506
Balneário Gaivota–2,4422,602146.55170%1,701
Balneário Piçarras–22,58126,20399.872260.3%8,607
Balneário Rincão–13,75217,14163.312170.2%5,311
Bandeirante–3,2363,222147.95220%0
Barra Bonita–2,1821,80192.25240%0
Barra Velha–7,6746,463139.8550.1%1,039
Bela Vista do Toldo–6,4075,640537.06120.1%0
Belmonte–1,5481,61893.25170%0
Benedito Novo–12,69111,394389.14330.2%0
Biguaçu–95,555118,136366.752611.3%13,717
Blumenau–353,945373,966519.516814.9%0
Bocaina do Sul–3,7263,524511.6170.1%0
Bom Jardim da Serra–5,0663,901939.5350.1%0
Bom Jesus–3,7063,45763.23590.1%0
Bom Jesus do Oeste–2,0991,82567.84310%0
Bom Retiro–10,6428,6941,058.76100.1%0
Bombinhas–14,62020,06534.84200.2%2,752
Botuverá–4,3234,858296.86150.1%0
Braço do Norte–33,35734,942212.041570.5%0
Braço do Trombudo–4,5684,83289.74510.1%0
Brunópolis–3,1542,483336.5490%0
Brusque–157,038161,286285.175512.2%0
Caçador–83,28377,110983.96851.2%0
Caibi–5,1864,443173.24300.1%0
Calmon–4,2693,810637.9970.1%0
Camboriú–115,056165,875210.615461.6%42,576
Campo Alegre–14,86914,953499.63300.2%0
Campo Belo do Sul–8,0347,0701,026.7780.1%0
Campo Erê–6,0964,885480.21130.1%0
Campos Novos–41,00541,8631,720.21240.6%0
Canelinha–13,59515,287151.29900.2%3,607
Canoinhas–61,20658,9461,150.72530.8%0
Capão Alto–3,1112,6731,334.5120%0
Capinzal–15,43216,499245.2630.2%0
Capivari de Baixo–12,42112,46452.932350.2%9,286
Catanduvas–10,57710,257198.89530.1%0
Caxambu do Sul–4,6064,626141.15330.1%0
Celso Ramos–2,9222,749208.44140%0
Cerro Negro–3,6723,139419.4190.1%0
Chapadão do Lageado–3,1113,054124.86250%0
Chapecó–239,179277,452626.773823.3%0
Cocal do Sul–10,04910,51570.971420.1%0
Concórdia–78,89786,102801.63981.1%0
Cordilheira Alta–4,0044,43483.55480.1%0
Coronel Freitas–12,18011,640233.62520.2%0
Coronel Martins–2,6351,961107.88240%0
Correia Pinto–15,71516,731648.9240.2%0
Corupá–16,77116,298407.06410.2%0
Criciúma–181,616210,867235.687712.5%820
Cunha Porã–13,26512,695220.91600.2%0
Cunhataí–2,2322,06355.05410%0
Curitibanos–43,75142,775951.7460.6%0
Descanso–12,27211,953288.07430.2%0
Dionísio Cerqueira–26,36524,964379.22700.4%0
Dona Emma–4,5644,897178.05260.1%0
Doutor Pedrinho–3,2522,962374.6590%0
Entre Rios–2,5252,741104.15240%0
Ermo–1,3501,28965.38210%535
Erval Velho–4,3794,385209.31210.1%0
Faxinal dos Guedes–11,93011,568341.04350.2%0
Flor do Sertão–2,1382,27257.98370%0
Florianópolis–440,252521,206675.716526.1%83,577
Formosa do Sul–2,4372,228100.6240%0
Forquilhinha–39,03949,613183.852120.5%679
Fraiburgo–39,47532,757551.27720.5%0
Frei Rogério–2,3552,074158.55150%0
Galvão–4,1403,404140.27300.1%0
Garopaba–16,53725,404114.51440.2%5,412
Garuva–16,37618,517502.95330.2%1,132
Gaspar–87,46395,170386.82261.2%19,291
Governador Celso Ramos–15,16715,817127.351190.2%3,401
Grão Pará–7,3356,537334.34220.1%0
Gravatal–11,93813,088166.04720.2%1,154
Guabiruba–22,36325,119172.21300.3%0
Guaraciaba–12,88512,358332.13390.2%0
Guaramirim–57,86562,625267.742160.8%124
Guarujá do Sul–7,9877,135101.03790.1%0
Guatambú–5,2649,558206.45250.1%0
Herval d’Oeste–23,77822,819217.341090.3%0
Ibiam–2,0711,942146.36140%0
Ibicaré–3,8343,465155.72250.1%0
Ibirama–24,02025,440247.1970.3%0
Içara–55,80164,615230.542420.8%3,851
Ilhota–16,01122,853252.74630.2%6,001
Imaruí–11,76811,882542.79220.2%1,985
Imbituba–42,23251,398181.812320.6%12,436
Imbuia–6,1576,078118.57520.1%0
Indaial–59,22266,673432.311370.8%0
Iomerê–5,7886,331114510.1%0
Ipira–2,0572,015156.19130%0
Iporã do Oeste–8,7458,958201.59430.1%0
Ipuaçu–8,5198,279261.53330.1%0
Ipumirim–8,1128,135246.32330.1%0
Iraceminha–4,1293,396165.54250.1%0
Irani–11,30410,923326.44350.2%0
Irati–1,2251,03377.85160%0
Irineópolis–8,3876,513590.77140.1%0
Itá–6,7627,182165.9410.1%0
Itaiópolis–23,32123,1021,299.86180.3%0
Itajaí–179,705214,419290.696182.5%108,464
Itapema–53,72377,53758.369210.7%17,679
Itapiranga–19,35118,408282.13690.3%0
Ituporanga–26,33328,466338.07780.4%0
Jaborá–4,0624,097182.7220.1%0
Jacinto Machado–12,68511,658431.63290.2%58
Jaguaruna–18,38515,973327.73560.3%6,947
Jaraguá do Sul–167,257178,818531.963142.3%0
Jardinópolis–2,7462,71668.93400%0
Joaçaba–31,12031,587241.451290.4%0
Joinville–645,901660,4101,130.715718.9%225,921
José Boiteux–5,6416,358406.4140.1%0
Jupiá–2,2392,42491.33250%0
Lacerdópolis–2,4042,30869.38350%0
Lages–156,567174,2482,641.52592.2%0
Laguna–38,69434,860334.741160.5%15,262
Lajeado Grande–1,5281,68065.52230%0
Laurentino–7,2528,96879.28910.1%0
Lauro Müller–16,35714,982271.62600.2%0
Lebon Régis–13,42311,525943.38140.2%0
Leoberto Leal–4,1123,852293.49140.1%0
Lindóia do Sul–5,0644,675189.86270.1%0
Lontras–9,34210,769197.93470.1%0
Luiz Alves–13,85113,953260.74530.2%70
Luzerna–7,9287,404117.37680.1%0
Macieira–1,1021,036261.840%0
Mafra–62,92062,9351,406.37450.9%0
Major Gercino–4,4023,887306.81140.1%0
Major Vieira–8,5137,588521.33160.1%0
Mampituba–2,7552,974157.42180%0
Maracajá–8,5798,86863.061360.1%3,140
Maravilha–27,18130,763170.771590.4%0
Marcelino Ramos–5,3144,473230.04230.1%0
Marema–2,3662,338104.03230%0
Mariano Moro–59760098.5660%0
Massaranduba–19,63719,628375.81520.3%65
Matos Costa–3,3302,955435.8480%0
Meleiro–6,9216,341186.86370.1%964
Mirim Doce–2,9762,797339.0490%0
Modelo–3,9593,53392.43430.1%0
Mondaí–10,4478,470200.42520.1%0
Monte Carlo–10,8559,119191.9570.1%0
Monte Castelo–8,7867,414561.43160.1%0
Morro da Fumaça–16,16216,31183.341940.2%180
Morro Grande–2,5062,511259.93100%0
Navegantes–114,527125,588111.721,0251.6%94,975
Nova Erechim–4,9485,21565.15760.1%0
Nova Itaberaba–5,1495,367137.3380.1%0
Nova Trento–14,13315,034404.1350.2%0
Nova Veneza–10,95810,084295.24370.2%0
Novo Horizonte–3,2692,754151.73220%0
Orleans–23,90425,017551.78430.3%0
Otacílio Costa–19,86118,733849.21230.3%0
Ouro–15,03314,020213.71700.2%0
Ouro Verde–2,0641,885189.07110%0
Paial–1,2181,33985.99140%0
Painel–2,6372,203738.9740%0
Palhoça–166,219231,443395.254212.3%76,577
Palma Sola–9,8909,239331.33300.1%0
Palmeira–2,4712,315290.0490%0
Palmitos–24,75622,212351.2700.3%0
Papanduva–21,27720,148767.18280.3%0
Paraíso–3,7233,602180.28210.1%0
Passo de Torres–29,75338,36693.133190.4%23,474
Passos Maia–3,3332,617618.0550%0
Paulo Lopes–8,74810,590447.27200.1%2,742
Pedras Grandes–3,8593,752161.17240.1%0
Penha–2,4981,14557.59430%519
Peritiba–1,4301,45395.59150%0
Pescaria Brava–27,14425,917106.572550.4%6,794
Petrolândia–7,0447,458307.2230.1%0
Pinhalzinho–21,41324,836129.51650.3%0
Pinheiro Preto–59475261.56100%0
Piratuba–7,7018,281146.45530.1%0
Planalto Alegre–2,7712,73563.57440%0
Pomerode–34,30336,543214.121600.5%0
Ponte Alta–5,9424,540575.19100.1%0
Ponte Alta do Norte–3,7243,087397.7690.1%0
Ponte Serrada–13,17411,227561.72230.2%0
Porto Belo–18,79131,90493.962000.3%3,835
Porto União–27,34921,306850.15320.4%0
Pouso Redondo–17,09717,266356.93480.2%0
Praia Grande–8,1828,894284.52290.1%15
Presidente Castello Branco–2,0772,01265.35320%0
Presidente Getúlio–16,76220,231298.08560.2%0
Presidente Nereu–2,4202,290225.32110%0
Princesa–3,7183,42686.4430.1%0
Quilombo–11,82312,223279.24420.2%0
Rancho Queimado–2,7443,041286.91100%0
Rio das Antas–7,2256,748314.83230.1%0
Rio do Campo–7,1267,045503.06140.1%0
Rio do Oeste–7,4327,593244.88300.1%0
Rio do Sul–75,49779,953261.62891%0
Rio dos Cedros–10,79510,139557.03190.1%0
Rio dos Índios–2,7092,008235.87110%0
Rio Fortuna–5,1765,315303.15170.1%0
Rio Negrinho–44,09239,402908.92490.6%0
Rio Rufino–2,6102,378282.3890%0
Riqueza–5,5024,991191.39290.1%0
Rodeio–14,43016,072128.671120.2%0
Romelândia–5,5444,300223.75250.1%0
Salete–8,3787,704178.16470.1%0
Saltinho–4,3273,589159.27270.1%0
Salto Veloso–6,3595,766104.15610.1%0
Sangão–13,26114,12883.561590.2%3,374
Santa Cecília–18,54216,0531,147.61160.3%0
Santa Helena–2,6252,41081.66320%0
Santa Rosa de Lima–2,1552,032203.96110%0
Santa Rosa do Sul–8,4319,623150.38560.1%1,255
Santa Terezinha–9,6737,719716.77130.1%0
Santa Terezinha do Progresso–3,6643,047119.96310.1%0
Santiago do Sul–1,4651,55373.63200%0
Santo Amaro da Imperatriz–23,10528,148344.83670.3%58
São Bento do Sul–88,32088,480497.041781.2%0
São Bernardino–2,2622,199150.3150%0
São Bonifácio–3,4013,189461.8970%0
São Carlos–10,9009,624162.56670.2%0
São Cristóvão do Sul–5,7986,548346.98170.1%0
São Domingos–10,7259,634368.63290.1%0
São Francisco do Sul–51,18155,506493.661040.7%10,941
São João Batista–33,67135,085200.621680.5%439
São João do Itaperiú–3,5064,279151.88230%278
São João do Oeste–6,2995,971163.57390.1%0

The first 250 of 299 units; the CSV carries all of them, and the map reaches each one.

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
1,044.3 H3 cells
Ports
2 H3 cells
Airports
2 H3 cells
Major roads
2,859.5 H3 cells
Railways
988.2 H3 cells
Rivers and lakes
292.3 H3 cells
06Risk

Risk values

Values when released. Subnational risk values for Santa Catarina 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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