NXS-GRX-CHN · Eastern Asia · Regions

Zhejiang 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
59,394,999
people (GHSL 2025)
100,438 km²
area
4.1%
of China
71
units inside
01Map

Inside Zhejiang Province

The 71 ADM2 units of Zhejiang Province.

FIG 1 · 71 units inside Zhejiang 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

59,394,999

4.1% of China.

People · WorldPop 2025

68,976,510

+16% against GHSL; the two grids differ in method.

Area

100,438 km²

591 people per km².

Code

CHN

Subdivision code as carried by the boundary source.

Low coastal zone

27,405,896

people on land at or below 10 m, 46.1% of the unit (GEBCO 2024 and GHSL 2025).

03Units

71 units inside Zhejiang 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
Anjixian–525,216653,5541,984.092650.9%46,354
Changshanxian–249,000262,6911,088.232290.4%0
Changxingxian–655,376602,9041,489.214401.2%422,110
Cixishi–1,750,2951,959,966752.722,3253.1%1,639,064
Cunanxian–396,622310,5824,628.09860.7%0
Daishanxian–38,14841,690107.493550.1%12,409
Deqingxian–532,666589,387927.725740.9%401,229
Dongyangshi–971,9231,230,3421,815.035351.7%0
Fenghuashi–531,942550,6781,137.374680.9%199,074
Fuyangshi–831,279826,2481,817.894571.5%118,181
Hainingshi–781,5841,107,057731.181,0691.4%849,102
Haiyanxian–427,961405,193464.069220.8%398,567
Hangzhoushi–2,287,4283,147,641434.565,2644%622,992
Huzhoushi–1,205,9341,531,4891,511.517982.1%1,098,351
Jiandeshi–513,751448,5302,289.712240.9%0
Jiashanxian–738,069732,339550.121,3421.3%737,705
Jiaxingshi–1,603,7781,803,0851,019.161,5742.8%1,581,765
Jingningshezuzizhixian–86,817100,7531,493.81580.2%0
Jinhuashi–1,767,9511,622,2842,293.067713.1%0
Jinyunxian–369,680398,3831,493.582480.6%0
Kaihuaxian–272,289258,3112,369.251150.5%0
Lanxishi–686,331616,2961,377.34981.2%0
Leqingxian–1,401,5971,314,3481,117.71,2542.5%742,958
Linanxian–642,785633,8443,208.752001.1%0
Linhaishi–1,163,5511,259,4272,148.655422%460,373
Lishuishi–672,719634,1111,458.234611.2%0
Longquanshi–214,957249,9683,003.82720.4%0
Longyouxian–336,160295,000915.53670.6%0
Ningboshi–1,172,4431,468,649949.761,2342.1%916,870
Ninghaixian–624,029618,5281,699.373671.1%50,560
Ouhaixian–928,0651,010,653645.681,4371.6%545,679
Pananxian–148,407148,4781,086.381370.3%0
Pinghushi–689,022605,342559.831,2311.2%673,093
Pingyangxian–1,006,5631,048,876891.171,1291.8%594,817
Pujiangxian–478,435443,374909.675260.8%0
Qingpuxian–1,075,514931,206715.541,5031.9%1,017,018
Qingtianxian–353,088567,1612,727.251290.6%6,266
Qingyuanxian–130,765137,6191,951.98670.2%0
Quxian–613,116473,7482,348.562611.1%0
Quxian–776,742522,053145.285,3471.4%0
Ruianshi–1,833,5991,843,2051,335.661,3733.2%1,131,239
Sanmenxian–324,050365,690924.543500.6%43,102
Shangyushi–817,941828,0321,150.757111.4%483,880
Shaoxingshi–574,040536,032100.035,7391%388,235
Shaoxingxian–1,326,1551,657,1711,320.971,0042.3%911,119
Shengxian–926,321852,8571,853.295001.6%231
Songyangxian–188,835207,4951,406.081340.3%0
Taishunxian–267,628289,3941,797.561490.5%0
Taizhoushi–2,012,6972,305,8891,479.961,3603.5%1,349,280
Tiantaixian–418,593505,6541,392.313010.7%0
Tongluxian–447,139463,0051,853.392410.8%8,824
Tongxiangshi–929,2951,134,594696.921,3331.6%925,037
Wenchengxian–233,626319,5811,229.861900.4%0
Wenlingshi–1,127,2271,199,767852.971,3222%617,172
Wenzhoushi–762,716611,699121.576,2741.3%466,783
Wuyixian–386,546500,2301,528.862530.7%0
Xiangshanxian–458,428499,000926.524950.8%155,984
Xianjuxian–400,394491,6932,085.431920.7%0
Xiaoshanshi–1,806,2633,210,1131,206.741,4973.2%1,102,333
Xinchangxian–298,641242,6781,207.782470.5%0
Yingxian–2,790,3513,074,8191,392.292,0044.9%2,417,327
Yiwushi–1,377,7662,341,7811,187.411,1602.4%0
Yongjiaxian–1,271,6161,498,0562,604.194882.2%329,671
Yongkangshi–808,6371,150,5431,030.877841.4%0
Yuhangxian–1,720,1904,372,8501,380.411,2463%1,237,357
Yuhuanxian–485,230475,313314.951,5410.9%126,469
Yunhexian–117,583142,5731,016.591160.2%0
Yuyaoshi–1,232,3411,325,5841,409.618742.2%883,150
Zhoushanshi–481,387481,431426.761,1280.8%132,724
Zhujishi–1,302,5091,233,9882,444.45332.3%143,123
Zuichangxian–201,401199,0352,442.17820.4%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
5,077.8 H3 cells
Ports
3 H3 cells
Airports
2 H3 cells
Major roads
5,351.8 H3 cells
Railways
919.9 H3 cells
Rivers and lakes
452 H3 cells
05Risk

Risk values

Values when released. Subnational risk values for Zhejiang 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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