NXS-GRX-CHN · Eastern Asia · Regions

Jiangsu 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
90,924,562
people (GHSL 2025)
97,863 km²
area
6.3%
of China
73
units inside
01Map

Inside Jiangsu Province

The 73 ADM2 units of Jiangsu Province.

FIG 1 · 73 units inside Jiangsu 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

90,924,562

6.3% of China.

People · WorldPop 2025

84,013,501

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

Area

97,863 km²

929 people per km².

Code

CHN

Subdivision code as carried by the boundary source.

Low coastal zone

61,884,501

people on land at or below 10 m, 68.1% of the unit (GEBCO 2024 and GHSL 2025).

03Units

73 units inside Jiangsu 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
Baoyingxian–687,415578,7551,512.664540.8%621,690
Binhaixian–869,893662,7131,849.954701%525,330
Changshushi–1,477,3861,704,9161,108.211,3331.6%1,392,805
Changzhoushi–1,531,7601,438,390197.057,7731.7%1,511,142
Dafengxian–686,680584,2972,423.412830.8%572,106
Dantuxian–438,542717,428835.965250.5%117,434
Danyangshi–966,6451,014,8981,059.989121.1%793,022
Donghaixian–1,017,7631,214,0672,347.984331.1%350,557
Dongtaishi–1,309,015786,0092,289.365721.5%1,299,193
Fengxian–922,287902,7801,478.486241%0
Funingxian–830,187716,5981,510.695500.9%509,791
Ganyuxian–1,019,922893,2791,489.366851.1%536,506
Gaochunxian–472,438451,167901.245240.5%273,277
Gaoyoushi–954,546613,7811,909.415001.1%929,828
Guannanxian–598,750558,0731,094.995470.7%583,501
Guanyunxian–920,424714,6521,829.095031%837,361
Haianxian–851,782855,5901,143.777450.9%851,398
Haimenshi–1,147,3101,042,530980.831,1701.3%1,124,434
Hongzexian–354,265278,1521,513.82340.4%230,981
Huaianshi–1,724,782707,0041,434.421,2021.9%1,680,154
Huaiyinshi–1,078,581749,582391.52,7551.2%515,456
Huaiyinxian–1,218,595907,1171,345.149061.4%204,249
Jiangdushi–894,332831,3571,393.826421%870,925
Jiangningxian–1,940,9332,788,7251,665.81,1652.2%784,833
Jiangyanshi–822,931937,6941,211.256790.9%814,169
Jiangyinshi–1,662,0171,855,527915.111,8161.8%1,376,354
Jianhuxian–704,596471,7701,112.316330.8%490,818
Jingjiangshi–985,254623,973638.91,5421.1%956,262
Jintanshi–506,328558,348958.45280.6%438,071
Jurongxian–557,914572,6811,283.494350.6%84,291
Kunshanshi–1,836,2402,391,461941.751,9502%1,804,829
Lianshuixian–835,597784,1421,668.085010.9%754,779
Lianyungangshi–1,445,8941,119,731785.231,8411.6%1,122,033
Lishuixian–413,351512,6891,027.924020.5%57,268
Liyangshi–891,423786,8501,602.875561%638,086
Nanjingshi–6,699,3254,812,422995.776,7287.5%2,628,823
Nantongshi–1,154,367858,270175.46,5811.3%1,053,711
Peixian–910,919788,5441,146.787941%0
Pizhoushi–2,061,6621,294,7182,003.131,0292.3%0
Qidongshi–959,988789,3051,139.218431.1%936,009
Rudongxian–924,817712,7441,761.415251%927,696
Rugaoshi–1,131,4331,126,8371,528.877401.3%1,102,738
Sheyangxian–938,341682,0062,736.413431%356,731
Shuqianshi–1,892,2521,431,0901,720.41,1002.1%3,379
Shuyangxian–1,352,6601,690,0072,223.936081.5%1,195,870
Shuzhoushi–323,752352,6652,532.121280.4%121,897
Shuzhoushi–2,866,9451,720,085166.8517,1833.2%2,642,928
Sihongxian–1,022,138896,6073,349.953051.1%28,069
Siyangxian–1,270,0011,057,0001,775.257151.4%68,367
Suqianxian–326,243250,8601,292.842520.4%277,188
Taichangxian–754,264833,461619.431,2180.8%752,383
Taixingxian–1,536,3491,082,2841,408.751,0911.7%1,504,911
Taizhoushi–290,116536,278103.732,7970.3%290,116
Tongshanxian–1,582,2482,530,4582,909.785441.8%0
Tongzhoushi–2,011,8462,068,6091,605.611,2532.2%1,982,888
Weishanxian–833,454814,4602,064.714040.9%0
Wujiangshi–2,278,3891,664,1141,090.432,0892.5%2,208,998
Wujinxian–2,174,6412,767,4711,629.471,3352.4%2,174,314
Wuxianshi–4,712,3053,943,8271,539.353,0615.2%4,137,623
Wuxishi–1,541,2221,802,793199.887,7111.7%1,302,947
Wuxixian–1,939,0612,884,0521,112.951,7422.2%2,003,228
Xiangshuixian–490,991461,0941,425.753440.5%389,886
Xinghuashi–1,529,423910,9002,363.996471.7%1,427,194
Xinyixian–781,1641,005,0291,628.664800.9%0
Xuyuxian–393,869399,7951,616.912440.4%8,827
Xuzhoushi–1,096,6651,264,572189.75,7811.2%0
Yanchengshi–2,097,0041,679,7731,695.251,2372.3%1,883,229
Yangzhong–344,148326,017312.221,1020.4%308,416
Yangzhoushi–1,110,0171,874,6841,076.411,0311.2%758,944
Yixingshi–1,402,4051,267,9351,699.138251.6%1,110,625
Yizhengshi–577,631522,409883.996530.6%277,814
Zhangjiagangshi–1,253,6241,535,461774.651,6181.4%1,184,356
Zhenjiangshi–773,029527,588129.755,9580.9%394,258
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
8,507 H3 cells
Ports
3 H3 cells
Airports
2 H3 cells
Major roads
8,983.4 H3 cells
Railways
980.2 H3 cells
Rivers and lakes
507.1 H3 cells
05Risk

Risk values

Values when released. Subnational risk values for Jiangsu 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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