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Global Risks Index

NXS-GRX-BRA · South America · Regions

伯南布哥州

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

Map All 27 first-level units
Page GRX-BRA-REdition Baseline Edition 2026Evidence close 2026-09-30ISO BRA / BRStatus UN member stateValues not yet publishedMethod v1.0.0-draft
10,242,749
人（GHSL 2025）
99,770 km²
面积
4.8%
of Brazil
178
所辖单位

01地图

Inside Pernambuco

The 178 ADM2 units of Pernambuco.

FIG 1 · 178 units inside Pernambuco
正在加载地图

单位高度随每 km² 人口升高 · GHSL 2025 栅格 · 地形 · ADM1 ADM2风险值将在发布时提供
最低五分位较低五分位中间五分位较高五分位最高五分位无数据
柱高和颜色表示各单位每 km² 人口，按所示单位的五分位数分级（地图图例给出分界值）；网格上无人口的单位显示为灰色，不属于最低一级；底层栅格为 GHSL 2025 人口网格。这些是来源观测值，不是指数值。从列表中选择一项人道主义数据，按其为单位着色并抬升；每项数据的来源显示在单位页面上。选择一个单位可深入查看其下辖单位；地图上方的路径可逐级返回。
02数据概览

人口、面积和密度

来自开放网格、在边界内汇总的来源观测值；不是指数值。

人口 · GHSL 2025

10,242,749

4.8% of Brazil.

人口 · WorldPop 2025

9,466,297

-8% against GHSL; the two grids differ in method.

面积

99,770 km²

每 km² 103 人。

代码

BR-PE

边界来源所载的行政区划代码。

低海拔沿海地带

1,199,109

people on land at or below 10 m, 11.7% of the unit (GEBCO 2024 and GHSL 2025).

03人道主义数据

Pernambuco in humanitarian data

来自人道主义数据交换平台（Humanitarian Data Exchange）的来源观测值，按名称与该单位匹配，每项均附有参考日期、提供方和许可协议。它们不是指数值。

人口 · 2022-12-31

9,058,931

人。UNFPA · Creative Commons Attribution for Intergovernmental Organisations (CC BY-IGO)。

Poverty headcount · 2015-12-31

5.6%

的人口处于多维贫困。Oxford Poverty & Human Development Initiative · Public Domain / No restrictions (CC0)。

04单位

178 units inside Pernambuco

每个单位都有自己的页面。

边界许可：Creative Commons Attribution 2.5 Generic · Creative Commons Attribution 3.0 Intergovernmental Organisations (CC BY 3.0 IGO)

单位 代码 人口（GHSL） 人口（WorldPop） 面积 km² 每平方公里 占比 沿海 ≤ 10 m
Abreu e Lima – 95,683 89,271 126.72 755 1% 0
Afogados da Ingazeira – 40,051 43,982 379.22 106 0.4% 0
Afrânio – 23,124 19,881 1,497.81 15 0.2% 0
Agrestina – 23,701 21,912 200.6 118 0.2% 0
Água Preta – 38,782 24,649 535.14 72 0.4% 0
Águas Belas – 41,043 41,193 889.66 46 0.4% 0
Alagoinha – 15,291 14,161 217.72 70 0.2% 0
Aliança – 38,830 33,502 274.02 142 0.4% 0
Altinho – 26,368 23,900 455.56 58 0.3% 0
Amaraji – 26,937 20,717 235.91 114 0.3% 0
Amparo – 2,285 2,422 122.18 19 0% 0
Angelim – 13,865 13,175 117.87 118 0.1% 0
Araçoiaba – 20,573 18,213 96.5 213 0.2% 0
Araripina – 84,642 87,038 2,046 41 0.8% 0
Arcoverde – 75,787 82,313 324.43 234 0.8% 0
Barra de Guabiraba – 15,026 12,126 120.64 125 0.1% 0
Barreiros – 43,456 37,999 234.6 185 0.4% 0
Belém de Maria – 11,876 10,016 76.17 156 0.1% 0
Belém do São Francisco – 23,221 19,476 1,839.45 13 0.2% 0
Belo Jardim – 80,750 86,630 649.8 124 0.8% 0
Betânia – 13,318 11,503 1,248.44 11 0.1% 0
Bezerros – 67,073 66,908 495.11 135 0.7% 0
Bodocó – 37,282 33,628 1,629.58 23 0.4% 0
Bom Conselho – 53,512 46,723 796.49 67 0.5% 0
Bom Jardim – 39,723 40,729 219.61 181 0.4% 0
Bonito – 43,352 39,116 392.59 110 0.4% 0
Brejão – 8,456 8,361 159.88 53 0.1% 0
Brejo da Madre de Deus – 107,021 99,425 765.99 140 1.1% 0
布宜诺斯艾利斯 – 11,113 10,792 94.01 118 0.1% 0
Buíque – 58,811 53,405 1,325.3 44 0.6% 0
Caaporã – 25,306 21,992 151.72 167 0.3% 3,931
Cabo de Santo Agostinho – 160,660 168,241 446.84 360 1.6% 15,138
Cabrobó – 37,985 34,020 1,663.24 23 0.4% 0
Cachoeirinha – 23,304 21,645 180.33 129 0.2% 0
Caetés – 28,412 29,268 296.86 96 0.3% 0
Calçado – 9,667 9,431 123.4 78 0.1% 0
Calumbi – 4,083 3,357 180.11 23 0% 0
Camaragibe – 210,839 210,738 51.46 4,097 2.1% 8,424
Camocim de São Félix – 2,291 4,703 72.47 32 0% 0
Canhotinho – 21,912 21,547 425.44 52 0.2% 0
Capoeiras – 23,363 20,520 337.84 69 0.2% 0
Carnaíba – 18,114 17,615 430.84 42 0.2% 0
Carnaubeira da Penha – 13,051 12,729 1,008.32 13 0.1% 0
Carpina – 69,639 65,424 148.35 469 0.7% 0
Caruaru – 410,547 436,636 925.31 444 4.1% 0
Catende – 39,094 27,861 208.31 188 0.4% 0
Cedro – 10,636 9,496 148.65 72 0.1% 0
Chã de Alegria – 14,889 16,458 48.64 306 0.1% 0
Chã Grande – 17,018 14,201 85.14 200 0.2% 0
Condado – 27,516 26,437 90.03 306 0.3% 0
Correntes – 19,110 18,213 318.95 60 0.2% 0
Cortês – 12,631 8,363 101.18 125 0.1% 0
Cumaru – 13,289 13,071 293.34 45 0.1% 0
Cupira – 6,690 6,477 95.57 70 0.1% 0
Custódia – 38,209 39,586 1,410.43 27 0.4% 0
Dormentes – 22,463 18,110 1,543.55 15 0.2% 0
Escada – 79,113 60,815 343.27 230 0.8% 0
Exu – 34,064 32,705 1,342.1 25 0.3% 0
Feira Nova – 21,018 20,686 108.5 194 0.2% 0
Ferreiros – 7,095 8,067 92.01 77 0.1% 0
Flores – 22,864 18,978 999.4 23 0.2% 0
Floresta – 33,047 32,175 3,660.31 9 0.3% 0
Frei Miguelinho – 21,743 21,414 213.44 102 0.2% 0
Gameleira – 31,966 15,776 256.82 124 0.3% 0
Garanhuns – 142,758 155,199 461.29 309 1.4% 0
Glória do Goitá – 25,919 25,756 232.48 111 0.3% 0
Goiana – 77,379 75,199 446.81 173 0.8% 22,594
Granito – 6,903 7,138 524.47 13 0.1% 0
Gravatá – 84,743 94,505 506.29 167 0.8% 0
Iati – 20,287 17,132 637.77 32 0.2% 0
Ibimirim – 30,242 29,525 1,914.13 16 0.3% 0
Ibirajuba – 9,109 8,243 189.88 48 0.1% 0
Igarassu – 136,814 148,505 306.71 446 1.4% 10,078
Iguaracy – 13,133 12,221 841.6 16 0.1% 0
Ilha de Itamaracá – 16,283 9,040 67.11 243 0.2% 7,216
Inajá – 15,399 16,571 1,172.78 13 0.2% 0
Ingazeira – 4,970 5,242 244.42 20 0% 0
Ipojuca – 80,651 90,852 524.76 154 0.8% 26,049
Itacuruba – 4,928 4,376 430.95 11 0% 0
Itaíba – 33,652 40,772 1,066.57 32 0.3% 0
Itambé – 45,114 40,026 305.79 148 0.4% 0
Itapetim – 14,694 14,849 406.96 36 0.1% 0
Itapissuma – 16,174 19,140 74.38 217 0.2% 2,343
Itaquitinga – 5,157 9,221 164.43 31 0.1% 0
Jaboatão dos Guararapes – 736,666 609,371 259.99 2,833 7.3% 206,343
Jaqueira – 19,781 14,395 87.03 227 0.2% 0
Jatobá – 16,999 15,923 279.3 61 0.2% 0
João Alfredo – 32,171 25,016 141.15 228 0.3% 0
Joaquim Nabuco – 18,877 13,170 122.21 154 0.2% 0
Jucati – 22,663 23,177 120.95 187 0.2% 0
Jupi – 8,324 8,842 105.88 79 0.1% 0
Jurema – 18,332 15,109 149.93 122 0.2% 0
Lagoa de Itaenga – 24,531 19,930 57.51 427 0.2% 0
Lagoa do Carro – 17,881 18,644 69.61 257 0.2% 0
Lagoa do Ouro – 12,349 11,601 198.48 62 0.1% 0
Lagoa dos Gatos – 20,480 18,589 225.88 91 0.2% 0
Lagoa Grande – 26,846 26,323 1,856.89 14 0.3% 0
Lajedo – 38,502 40,097 188.08 205 0.4% 0
Limoeiro – 66,486 63,893 275.69 241 0.7% 0
Machados – 4,180 2,774 60 70 0% 0
Manari – 18,302 22,717 346.52 53 0.2% 0
Maraial – 4,939 3,972 199.95 25 0% 0
Minador do Negrão – 6,417 5,265 167.94 38 0.1% 0
Mirandiba – 16,459 15,448 823.91 20 0.2% 0
Moreilândia – 11,532 10,088 406.21 28 0.1% 0
Moreno – 36,243 28,370 197.08 184 0.4% 0
Nazaré da Mata – 35,185 34,856 130.63 269 0.4% 0
Olinda – 301,048 275,052 41.3 7,289 3% 0
Orocó – 14,111 13,406 556.15 25 0.1% 0
Ouricuri – 71,896 68,580 2,393.41 30 0.7% 0
Ouro Velho – 3,035 2,927 128.49 24 0% 0
Palmares – 64,528 53,764 340.64 189 0.6% 0
Palmeirina – 8,569 6,777 169.96 50 0.1% 0
Panelas – 41,473 33,936 381.57 109 0.4% 0
Paranatama – 11,593 12,775 185.66 62 0.1% 0
Parnamirim – 23,384 18,810 2,619.34 9 0.2% 0
Passira – 28,844 28,074 327.65 88 0.3% 0
Paudalho – 82,023 84,319 275.73 297 0.8% 0
Paulista – 462,431 459,680 97.4 4,748 4.6% 87,168
Pedra – 25,252 24,492 926.1 27 0.3% 0
Pesqueira – 68,765 65,458 985.76 70 0.7% 0
Petrolândia – 36,602 34,568 1,060.4 35 0.4% 0
Petrolina – 401,666 406,684 4,582.41 88 4% 0
Pombos – 28,607 30,668 240.61 119 0.3% 0
Prata – 4,819 4,476 202.35 24 0% 0
Primavera – 13,404 11,704 113.5 118 0.1% 0
Quebrangulo – 10,596 10,245 320.92 33 0.1% 0
Quipapá – 25,910 15,836 231.85 112 0.3% 0
Recife – 1,950,570 1,542,209 219.97 8,867 19.5% 717,057
Riacho das Almas – 19,967 22,429 314.69 63 0.2% 0
Ribeirão – 52,196 31,777 291.46 179 0.5% 0
Rio Formoso – 26,518 20,779 228.97 116 0.3% 843
Sairé – 14,107 15,584 191.17 74 0.1% 0
Salgadinho – 12,417 6,793 86.69 143 0.1% 0
Salgueiro – 60,900 62,763 1,688.24 36 0.6% 0
Saloá – 15,032 12,506 252.64 59 0.1% 0
Sanharó – 25,670 17,278 269.55 95 0.3% 0
圣克鲁斯 – 18,710 14,717 1,252.35 15 0.2% 0
Santa Cruz do Capibaribe – 44,104 49,149 337.01 131 0.4% 0
Santa Filomena – 15,296 10,725 1,008.45 15 0.2% 0
Santa Maria da Boa Vista – 50,230 44,740 3,014.45 17 0.5% 0
Santa Maria do Cambucá – 11,835 12,849 93.18 127 0.1% 0
Santana do Mundaú – 11,941 12,038 233.26 51 0.1% 0
São Benedito do Sul – 15,386 12,065 162.01 95 0.2% 0
São Bento do Una – 58,106 48,112 722.19 80 0.6% 0
São Caitano – 38,122 41,412 384.38 99 0.4% 0
São João – 22,122 24,362 258.67 86 0.2% 0
São Joaquim do Monte – 40,590 34,279 232.34 175 0.4% 0
São José da Laje – 24,953 19,924 257.86 97 0.2% 0
São José do Belmonte – 34,971 36,588 1,481.03 24 0.3% 0
São José do Egito – 36,136 34,478 798.25 45 0.4% 0
São Lourenço da Mata – 169,345 165,726 264.08 641 1.7% 0
Serra Talhada – 92,757 101,457 2,993.04 31 0.9% 0
Serrita – 20,613 19,780 1,543.37 13 0.2% 0
Sertânia – 36,920 34,403 2,431.52 15 0.4% 0
Sirinhaém – 55,395 38,452 375.53 148 0.6% 5,061
Surubim – 61,291 60,724 253.86 241 0.6% 0
Tabira – 27,239 26,173 389.83 70 0.3% 0
Tacaimbó – 14,699 16,798 228.37 64 0.1% 0
Tacaratu – 24,286 24,710 1,270.12 19 0.2% 0
Tamandaré – 14,534 10,132 214.2 68 0.1% 824
Taquaritinga do Norte – 34,302 35,089 477.09 72 0.3% 0
Terezinha – 7,205 6,391 151.83 47 0.1% 0
Terra Nova – 12,223 11,310 319.88 38 0.1% 0
Timbaúba – 67,994 60,098 288.98 235 0.7% 0
Toritama – 6,581 7,889 25.6 257 0.1% 0
Tracunhaém – 13,741 10,760 136.36 101 0.1% 0
Trindade – 30,940 31,787 296.06 105 0.3% 0
Triunfo – 15,127 15,344 191.88 79 0.2% 0
Tupanatinga – 25,577 27,698 956.1 27 0.3% 0
Tuparetama – 8,064 7,380 178.99 45 0.1% 0
Venturosa – 18,502 18,230 336.22 55 0.2% 0
Verdejante – 9,582 10,075 477.92 20 0.1% 0
Vertentes – 28,035 29,210 196.96 142 0.3% 0
Vicência – 29,894 22,772 228.83 131 0.3% 0
Vitória de Santo Antão – 144,009 144,627 337.81 426 1.4% 0
Xexéu – 16,012 10,670 111.11 144 0.2% 0
Zabelê – 2,203 2,283 107.46 21 0% 0
05风险暴露

开放风险暴露图层

中心点落在该单位内且包含各 Natural Earth 图层的 H3 分辨率 3 单元格数量。

城市区域
1,040.1 H3 cells
港口
1 个 H3 单元格
机场
2 个 H3 单元格
主要道路
2,449.2 H3 cells
铁路
723.7 H3 cells
河流和湖泊
390.4 H3 cells
06风险

风险值

Values when released. Subnational risk values for Pernambuco publish with the edition from The Global Risks Index. Until then, run a scenario on open data for Brazil.
运行情景 危害 领域指数
07相邻单位

相邻单位

08来源

来源、致谢与许可协议

ADM1 边界
geoBoundaries (William & Mary geoLab), gbOpen BRA ADM1, source: geoBoundaries, Wikimedia Commons, licence: Creative Commons Attribution 2.5 Generic · source · represents 2006
ADM2 边界
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
底图
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.
地形
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.
人口
GHSL 2025 人口网格，欧盟委员会联合研究中心（CC BY 4.0），以 0.05° 显示并按单位求和；WorldPop 2025（CC BY 4.0）作为第二个估计。小于一个格网单元的单位采用其所在格网单元的密度。
国家
Natural Earth（公有领域）。
高程
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.
立场
边界仅用于标示位置，不对任何边界、名称或地位持立场。

状态

The Global Risks Index 的方法、结构和定义为预备性工作草案（2026），供审阅和评论，不供实施。在从受治理的证据截取中发布版本之前，不会出现任何数值；届时数值将附有区间、类别、来源及其更正途径。模拟器以您选择的数字运行已发布的方法，绝不显示 NXS-GRX 数值。

国家概况解读的是关于某地的公开证据。它不是任何政府的声明，也不是关于任何政府政策的声明；不对任何领土的地位表明立场，也不意味着存在国家计划或参与。名称遵循 UN M49。

NXS-GRX 不是什么

NXS-GRX 是研究和风险分析信息。它不是信用评级或 ESG 评级，不使用任何评级尺度；它不是金融工具的基准，不是官方统计，不是紧急警报或官方分类，也不是建议。不得用于评估自然人。风险等级是已发布尺度上的区间，绝不是对国家或个人的排名。

Pulse 信号和展望概率是供主管当局审查的信息，绝不是公共警报；官方警报只由获授权的当局发布。

机构与来源

The Nexus Consortium is stewarded by three independent not-for-profit institutions: The Global Centre for Risk and Innovation (GCRI), through GCRI US in Washington, DC and GCRI Canada in Ontario, with GCRI Canada as Lead Institution, Consortium Secretariat and lead contracting organisation; The Global Risks Forum (GRF); and The Global Risks Alliance (GRA). Technology, infrastructure and service providers work with the Consortium at arm’s length under written agreements, like every other external party in the public-private-planet model, and hold no role in its stewardship.

每个数值均附有其来源的署名，这些来源保留各自的许可。外部名称仅为互操作性而引用。Nexus 撰写的文本拟在发布时采用 CC BY 4.0。

Avis en français

La méthodologie et les définitions du NXS-GRX sont un projet de travail préparatoire (2026). Le NXS-GRX est une information de recherche et d’analyse des risques : ni notation, ni indice de référence financier, ni statistique officielle, ni alerte, ni conseil. Les classes de risque sont des bandes sur une échelle publiée, non des classements.