NXS-GRX-CHN · Eastern Asia · Regions

Hubei Province

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

Page GRX-CHN-REdition Baseline Edition 2026Evidence close 2026-09-30ISO CHN / CNStatus UN member stateValues not yet publishedMethod v1.0.0-draft
55,282,054
people (GHSL 2025)
186,897 km²
area
3.9%
of China
73
units inside
01Map

Inside Hubei Province

The 73 ADM2 units of Hubei Province.

FIG 1 · 73 units inside Hubei Province
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. 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

55,282,054

3.9% of China.

People · WorldPop 2025

56,050,184

+1% against GHSL; the two grids differ in method.

Area

186,897 km²

296 people per km².

Code

CHN

Subdivision code as carried by the boundary source.

Low coastal zone

56,144

people on land at or below 10 m, 0.1% of the unit (GEBCO 2024 and GHSL 2025).

03Units

73 units inside Hubei Province

Each unit has its own page.

Boundary licences: Public Domain · Open Data Commons Public Domain Dedication and License (PDDL) v1.0.

UnitCodePeople (GHSL)People (WorldPop)Area km²Per km²ShareCoast ≤ 10 m
Anlushi–612,687386,0461,334.944591.1%0
Badongxian–355,447364,2333,454.471030.7%0
Baokangxian–217,836181,4833,218.11680.4%0
Changyangtujiazuzizhixian–330,991223,5093,587.53920.6%0
Chongyangxian–344,089444,0012,060.161670.6%0
Dangyangshi–374,712303,6452,0111860.7%0
Danjiangkoushi–401,888389,7303,033.051330.8%0
Dawuxian–524,868357,2941,891.312781%0
Dazhishi–752,737815,7551,538.624891.4%345
Enshishi–1,098,470907,1044,081.142692.1%0
Ezhoushi–747,9731,009,8631,474.75071.4%753
Fangxian–351,292338,6675,164.3680.7%0
Gonganxian–638,978464,3722,212.882891.2%0
Guangshuishi–650,916659,5332,644.972461.2%0
Guchengxian–400,784375,3172,454.021630.7%0
Hanchuanxian–1,140,889690,0031,595.337152.1%0
Hefengxian–160,993138,8212,877.35560.3%0
Honganxian–489,924419,0321,734.872820.9%0
Honghushi–668,532550,9692,531.392641.2%0
Huangmeixian–999,029981,5901,686.975921.9%32,973
Huangpixian–951,1611,571,3092,408.013951.8%0
Huangshishi–398,591421,090160.222,4880.7%0
Huangzhoushi–773,188813,8421,299.425951.4%6,674
Jianglingxian–795,7731,175,9962,408.473301.5%0
Jianshixian–342,059395,0172,714.341260.6%0
Jiayuxian–265,325239,293879.063020.5%0
Jingmenshi–985,1941,045,0454,382.242251.8%0
Jingshanxian–507,259431,1643,515.271440.9%0
Laifengxian–204,972298,0311,328.131540.4%0
Laohekoushi–342,487337,251882.783880.6%0
Lichuanshi–555,641823,0764,862.881141%0
Luotianxian–396,070343,6452,017.141960.7%0
Machengshi–655,278894,8263,484.71881.2%0
Nanzhangxian–435,997350,4883,810.051140.8%0
Puxishi–453,409490,6651,856.242440.8%0
Qianjiangshi–739,285848,0012,009.193681.4%0
Qichunxian–620,114889,5642,413.292571.2%10,681
Shashi–447,747415,659229.611,9500.8%0
Shennongjialinqu–60,90354,5093,235.88190.1%0
Shiyanshi–1,229,7831,156,3371,195.141,0292.3%0
Shuizhoushi–1,080,0211,208,7046,764.831602%0
Songzixian–582,512511,6462,173.122681.1%0
Susongxian–575,009674,0782,608.662201.1%21,424
Tianmenshi–1,896,9291,288,7002,892.266563.5%0
Tongboxian–424,960379,1962,140.581990.8%0
Tongshanxian–304,255421,8132,379.891280.6%0
Wuhanshi–9,555,03011,433,0334,803.871,98917.9%0
Wuxueshi–636,895762,3611,426.684461.2%3,155
Xiangfanshi–728,4371,018,020204.53,5621.4%0
Xiangyangxian–1,209,9071,367,6883,449.223512.3%0
Xianningshi–469,745762,3101,576.692980.9%0
Xiantaoshi–843,7371,030,8362,514.093361.6%0
Xiaoganshi–1,761,5971,501,3282,443.027213.3%0
Xingshanxian–145,73098,2112,271.25640.3%0
Xinzhouxian–786,355917,0121,511.955201.5%0
Xishuixian–1,026,491907,2242,024.925071.9%19,108
Xuanenxian–253,044246,5602,735.25930.5%0
Yangxinxian–627,997821,8882,571.052441.2%0
Yichangshi–1,293,367911,589203.996,3402.4%0
Yichangxian–836,297633,1593,964.322111.6%0
Yichengshi–437,223426,1472,098.132080.8%0
Yingchengshi–496,546328,7311,143.654340.9%0
Yingshanxian–291,133252,7271,352.452150.5%0
Yuananxian–166,779146,2081,825.49910.3%0
Yunmengxian–543,319399,785686.967911%0
Yunxian–535,914258,9443,770.631421%0
Yunxixian–459,499343,8933,671.661250.9%0
Zhaoyangshi–805,341725,6123,100.292601.5%0
Zhichengshi–355,351338,9811,392.442550.7%0
Zhiguixian–308,162227,8032,249.591370.6%0
Zhijiangxian–432,191341,6401,375.823140.8%0
Zhongxiangshi–881,159691,7704,455.351981.6%0
Zhushanxian–350,206269,1523,520.68990.7%0
04Exposure

Open exposure layers

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

Urban areas
3,979.7 H3 cells
Ports
1 H3 cells
Airports
1 H3 cells
Major roads
10,625.9 H3 cells
Railways
1,675.7 H3 cells
Rivers and lakes
1,943.4 H3 cells
05Risk

Risk values

Values when released. Subnational risk values for Hubei Province publish with the edition from The Global Risks Index. Until then, run a scenario on open data for China.
07Sources

Sources, credits and licences

ADM1 boundaries
geoBoundaries (William & Mary geoLab), gbOpen CHN ADM1, source: geoBoundaries, Wikimedia Commons, licence: Public Domain · source · represents 2019
ADM2 boundaries
geoBoundaries (William & Mary geoLab), gbOpen CHN ADM2, source: National Administration of Surveying, Mapping and Geoinformation of China, Revolutionary GIS, licence: Open Data Commons Public Domain Dedication and License (PDDL) v1.0 · source · represents 2017
ADM3 boundaries
geoBoundaries (William & Mary geoLab), gbOpen CHN ADM3, source: Lee Beryman, OpenStreetMap © OpenStreetMap contributors, licence: Open Data Commons Open Database License 1.0 (share-alike: this boundary layer is offered under the same licence) · source · represents 2017. Offered under the same licence (Open Data Commons Open Database License 1.0), kept as its own layer and not merged into other data.
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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