NXS-GRX-CHN · Eastern Asia · Regions

Shandong 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
91,168,514
people (GHSL 2025)
151,120 km²
area
6.4%
of China
109
units inside
01Map

Inside Shandong Province

The 109 ADM2 units of Shandong Province.

FIG 1 · 109 units inside Shandong 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

91,168,514

6.4% of China.

People · WorldPop 2025

95,443,358

+5% against GHSL; the two grids differ in method.

Area

151,120 km²

603 people per km².

Code

CHN

Subdivision code as carried by the boundary source.

Low coastal zone

8,256,525

people on land at or below 10 m, 9.1% of the unit (GEBCO 2024 and GHSL 2025).

03Units

109 units inside Shandong 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
Anqiushi–1,586,289838,8812,044.457761.7%0
Binzhoushi–1,087,809854,791843.751,2891.2%474,113
Boxingxian–622,464590,2331,040.15980.7%544,439
Changlexian–493,477478,2721,036.574760.5%0
Changqingxian–595,276603,3751,272.334680.6%0
Changshangxian–1,098,1151,003,0631,768.466211.2%0
Changyishi–1,055,224614,2961,690.496241.1%654,951
Chengwuxian–630,685586,7211,004.996280.7%0
Chepingxian–621,747668,9651,200.665180.7%0
Danxian–992,140941,9781,653.236001.1%0
Dezhoushi–517,385877,055331.991,5580.5%0
Dingtaoxian–546,371605,450785.986950.6%0
Dongerxian–360,654349,560740.664870.4%0
Dongmingxian–710,740771,5291,393.415100.8%0
Dongpingxian–540,736483,152943.475730.6%0
Dongyingshi–193,110200,5081,650.561170.2%170,950
Dongyingshi–327,899354,835585.395600.3%327,619
Feichengxian–923,065799,4551,273.727251%0
Feixian–824,111849,1481,810.054550.9%0
Gaomishi–1,264,722855,2241,574.738031.3%37,116
Gaoqingxian–410,047327,493928.294420.4%142,716
Gaotangixan–467,188431,538935.864990.5%0
Guangraoxian–532,953541,3701,151.34630.6%250,567
Guanxian–791,539700,7751,207.46560.8%0
Haiyangxian–564,109469,5691,784.043160.6%61,945
Hezheshi–1,328,5971,762,3271,423.639331.4%0
Huantanxian–571,852624,683577.259910.6%68,376
Huiminxian–592,646512,0701,351.174390.6%57,815
Jiaonanshi–750,4601,113,9341,691.724440.8%230,851
Jiaozhoushi–953,6791,118,4241,337.757131%278,880
Jiaxiangxian–860,008847,469991.288680.9%0
Jimoshi–1,378,8851,800,3271,735.597941.5%201,210
Jinanshi–3,976,9755,079,3121,853.932,1454.2%0
Jiningshi–1,285,2641,446,867882.881,4561.4%0
Jinxiangxian–612,390639,012917.616670.7%0
Jiyangxian–539,863515,8131,168.434620.6%0
Junanxian–820,198764,4311,729.94740.9%0
Juxian–974,756948,0561,878.475191%0
Juyexian–808,582950,6361,263.776400.9%0
Kenlixian–802,870956,5931,728.074650.9%748,243
Laiwushi–1,194,1221,164,5922,108.045661.3%0
Laixishi–784,981668,0251,611.484870.8%0
Laiyangshi–909,731684,1601,629.845581%29,004
Laizhoushi–948,911752,1981,951.184861%164,428
Leningshi–632,799441,5241,132.355590.7%24,498
Liangshanxian–856,365808,1781,311.176530.9%0
Liaochengshi–1,148,2811,447,8591,222.129401.2%0
Lijinxian–312,169201,4201,087.142870.3%298,250
Lingxian–628,158701,2501,379.294550.7%0
Linjuxian–801,153743,2461,974.554060.9%0
Linqingshi–753,588811,384956.27880.8%0
Linshuxian–563,906564,062970.985810.6%0
Linyishi–2,088,9893,958,6311,737.941,2022.2%0
Linyixian–491,714427,2211,052.374670.5%0
Longkoushi–650,176764,213957.916790.7%129,737
Mengyinxian–477,687458,1701,665.342870.5%0
Mupingxian–653,724566,4401,754.273730.7%88,101
Ningjinxian–528,736523,673957.145520.6%0
Ningyangxian–709,974582,6341,117.776350.8%0
Penglaixian–412,943405,8901,341.433080.4%15,057
Pingdushi–1,430,284968,1503,211.084451.5%209,257
Pingyinxian–396,068341,594801.324940.4%0
Pingyixian–848,485826,5471,699.34990.9%0
Pingyuanxian–434,832402,8681,081.794020.5%0
Qihexian–846,143904,9491,580.695350.9%0
Qingdaoshi–3,177,7373,864,9211,025.313,0993.4%537,384
Qingdaoshi–467,937682,028151.263,0940.5%137,678
Qingyunxian–347,486372,897594.25850.4%280,280
Qingzhoushi–873,888913,2361,539.185680.9%0
Qixiashi–533,127498,1661,975.382700.6%0
Qufushi–680,869644,682884.497700.7%0
Rizhaoshi–1,019,2701,483,1301,726.925901.1%162,619
Rongchengshi–658,116598,0991,592.414130.7%85,018
Rushanshi–535,424309,9151,548.073460.6%53,863
Shanghexian–538,912453,7791,102.134890.6%272
Shouguangshi–1,312,1551,339,3052,112.776211.4%429,881
Sishuixian–522,629544,6611,089.884800.6%0
Taianshi–1,733,3902,014,0462,094.128281.8%0
Tanchengxian–956,495941,6971,275.727501%0
Tengzhoushi–2,632,5701,792,0202,098.061,2552.8%0
Weifangshi–1,485,7322,423,6151,487.839991.6%108,920
Weihaishi–431,020865,693453.639500.5%68,162
Wendengshi–640,105528,0491,818.983520.7%58,069
Wenshangxian–631,877670,732912.616920.7%0
Wuchengxian–441,598365,712814.335420.5%0
Wulianxian–459,464380,4011,492.323080.5%0
Wulixian–441,062526,1341,713.732570.5%440,891
Wuqiaoxian–253,177179,467529.394780.3%0
Xiajinxian–496,610434,371865.835740.5%0
Xintaishi–1,211,4771,367,4322,043.535931.3%0
Yangguxian–757,183625,915996.167600.8%0
Yangxinxian–414,079384,813789.655240.4%323,299
Yantaishi–805,3621,566,444863.769320.9%224,178
Yanzhoushi–565,583711,147551.581,0250.6%0
Yinanxian–763,013777,1261,736.064400.8%0
Yishuixian–965,948899,5522,406.834011%0
Yiyuanxian–587,778479,3331,606.423660.6%0
Yuchengxian–466,139438,005961.964850.5%0
Yunchengxian–1,023,6721,184,8641,667.386141.1%0
Yutaixian–471,140420,214666.097070.5%0
Zhangqiushi–1,127,1451,177,0431,690.626671.2%0
Zhanhuaxian–352,915309,8841,495.552360.4%352,873
Zhaoyuanshi–539,017488,0451,490.073620.6%10,158
Zhaozhuangshi–1,799,1462,049,4992,346.747671.9%0
Zhenchengxian–744,973781,9931,080.626890.8%0
Zhouchengshi–1,189,7431,218,7051,646.397231.3%0
Zhoupingxian–759,165745,2871,289.045890.8%525
Zhuchengshi–1,584,0581,031,4142,185.717251.7%0
Ziboshi–3,196,9963,277,5922,965.691,0783.4%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
8,783.9 H3 cells
Ports
None at this resolution
Airports
None at this resolution
Major roads
10,107.2 H3 cells
Railways
2,138.1 H3 cells
Rivers and lakes
551.4 H3 cells
05Risk

Risk values

Values when released. Subnational risk values for Shandong Province publish with the edition from The Global Risks Index. Until then, run a scenario on open data for China.
06Neighbours

Neighbouring units

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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