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NXS-GRX-CHN · Eastern Asia · Regions

Liaoning 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
44,404,512
people (GHSL 2025)
149,017 km²
area
3.1%
of China
65
units inside

01Ramani

Inside Liaoning Province

The 65 ADM2 units of Liaoning Province.

FIG 1 · 65 units inside Liaoning Province
Inapakia ramani

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.

Watu · GHSL 2025

44,404,512

3.1% of China.

Watu · WorldPop 2025

38,319,691

-14% against GHSL; the two grids differ in method.

Area

149,017 km²

298 people per km².

Code

CHN

Subdivision code as carried by the boundary source.

Ukanda wa pwani ulio chini

5,365,694

people on land at or below 10 m, 12.1% of the unit (GEBCO 2024 and GHSL 2025).

03Units

65 units inside Liaoning Province

Each unit has its own page.

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

Unit Code People (GHSL) People (WorldPop) Area km² Per km² Share Coast ≤ 10 m
Anshanshi – 1,433,391 1,362,403 588.03 2,438 3.2% 0
Beipiaoshi – 492,946 435,749 4,778.04 103 1.1% 0
Beizhenmanzuzizhixian – 485,914 327,618 1,624.72 299 1.1% 136,110
Benximanzuzizhixian – 301,440 181,297 3,397.29 89 0.7% 0
Benxishi – 1,212,399 639,787 1,317.06 921 2.7% 0
Changhaixian – 5,309 4,193 31.01 171 0% 569
Changhaixian – 1,890 864 31.83 59 0% 89
Changhaixian – 6,289 7,272 26.36 239 0% 359
Changhaixian – 2,853 1,981 39.65 72 0% 213
Changhaixian – 168 41 29.91 6 0% 0
Changtuxian – 814,828 572,190 4,527.43 180 1.8% 0
Chaoyangshi – 584,814 676,666 824.46 709 1.3% 0
Chaoyangxian – 458,101 327,935 4,218.5 109 1% 0
Dalianshi – 4,336,260 4,739,035 2,396.62 1,809 9.6% 356,523
Dandongshi – 413,800 203,772 504.92 820 0.9% 5,734
Dawaxian – 299,907 271,066 1,096.31 274 0.7% 287,030
Dengtaxian – 544,949 347,257 1,395.84 390 1.2% 147
Donggangshi – 470,676 394,902 1,857.79 253 1% 314,142
Fakuxian – 449,490 344,435 2,301.29 195 1% 0
Fenchengmanzuzizhixian – 547,190 403,214 5,743.33 95 1.2% 13,411
Fushunshi – 978,914 728,201 421.13 2,324 2.2% 928
Fushunxian – 577,759 464,871 2,577.32 224 1.3% 0
Fuxinmengguzuzizhixian – 875,385 686,168 6,481.74 135 1.9% 0
Fuxinshi – 514,812 457,140 351.03 1,467 1.1% 0
Gaizhoushi – 1,088,058 1,040,568 3,328.24 327 2.4% 186,374
Haichengshi – 1,223,551 650,125 2,954.59 414 2.7% 247,471
Heishanxian – 580,069 303,966 2,333.9 249 1.3% 12,639
Huanrenmanzuzizhixian – 294,448 150,600 3,439.02 86 0.7% 0
Huludaoishi – 877,863 757,250 2,099.66 418 1.9% 44,823
Jianchangshi – 475,647 355,472 3,183.95 149 1.1% 0
Jianpingxian – 563,801 499,663 5,070.57 111 1.3% 0
Jinzhoushi – 951,461 916,037 366.71 2,595 2.1% 532
Kaiyuanshi – 595,845 444,545 3,375.29 177 1.3% 0
Kalaqinzuoqimengguzuzizhixian – 353,682 320,988 2,197.31 161 0.8% 0
Kangpingxian – 315,573 230,160 2,173.26 145 0.7% 0
Kuandianmanzuzizhixian – 398,134 270,028 5,897.91 68 0.9% 3,129
Liaoyangshi – 601,398 644,230 256.24 2,347 1.3% 0
Liaoyangxian – 736,460 520,495 1,125.3 654 1.6% 161,003
Liaoyangxian – 251,589 161,082 2,165.78 116 0.6% 33
Liaozhongxian – 416,444 364,993 1,432.42 291 0.9% 40,398
Lingyuanshi – 558,929 515,139 3,597.4 155 1.2% 0
Linhaishi – 567,639 455,036 2,534.25 224 1.3% 122,249
Panjinshi – 1,086,944 1,003,164 1,910.81 569 2.4% 1,095,842
Qinghemenqu – 35,706 18,003 144.5 247 0.1% 0
Qingyuanmanzuzizhixian – 274,239 200,161 3,843.91 71 0.6% 0
Qinhuangdaoshi – 516,236 683,689 323.03 1,598 1.1% 251,426
Shenyangshi – 7,182,751 8,021,957 3,395.24 2,116 15.9% 0
Sipingshi – 557,198 536,367 386.85 1,440 1.2% 0
Suizhongxian – 410,174 379,320 2,528.55 162 0.9% 72,990
Taianxian – 328,783 264,768 1,418.6 232 0.7% 312,061
Tiefashi – 161,150 96,286 311.36 518 0.4% 0
Tielingshi – 208,112 311,658 221.56 939 0.5% 0
Tielingxian – 396,519 352,796 1,979.34 200 0.9% 0
Wafangdianshi – 925,976 787,584 3,418.5 271 2.1% 52,542
Xifengxian – 265,485 160,323 2,610.12 102 0.6% 0
Xinbinmanzuzizhixian – 232,368 157,771 4,476.75 52 0.5% 0
Xingchengshi – 551,046 439,074 1,881.72 293 1.2% 78,079
Xinjinxian – 690,773 491,784 2,608.26 265 1.5% 75,021
Xinminxian – 795,176 484,370 3,443.82 231 1.8% 0
Yingkoushi – 771,779 545,721 1,584.67 487 1.7% 304,926
Yingkoushi – 1,076,422 570,824 547.03 1,968 2.4% 918,734
Yixian – 348,257 207,471 2,440.74 143 0.8% 0
Youyanmanzuzizhixian – 459,559 341,027 4,449 103 1% 0
Zhangwuxian – 361,539 303,208 3,763.53 96 0.8% 0
Zhuangheshi – 753,733 587,983 3,583.77 210 1.7% 162,809
04Mfiduo

Open exposure layers

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

Urban areas
3,825.8 H3 cells
Bandari
None at this resolution
Viwanja vya ndege
1 H3 cells
Major roads
5,920.1 H3 cells
Reli
3,775.2 H3 cells
Rivers and lakes
670.3 H3 cells
05Hatari

Risk values

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

Neighbouring units

07Vyanzo

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.
Nchi
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.