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Global Risks Index

NXS-GRX-JPN · Eastern Asia · Regions

Aichi Prefecture

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

Map All 47 first-level units
Page GRX-JPN-REdition Baseline Edition 2026Evidence close 2026-09-30ISO JPN / JPStatus UN member stateValues not yet publishedMethod v1.0.0-draft
7,319,061
people (GHSL 2025)
5,171 km²
area
6.3%
of Japan
54
units inside

01Ramani

Inside Aichi Prefecture

The 54 ADM2 units of Aichi Prefecture.

FIG 1 · 54 units inside Aichi Prefecture
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

7,319,061

6.3% of Japan.

Watu · WorldPop 2025

7,286,342

0% against GHSL; the two grids differ in method.

Area

5,171 km²

1,415 people per km².

Code

JP-23

Subdivision code as carried by the boundary source.

Ukanda wa pwani ulio chini

2,184,104

people on land at or below 10 m, 29.8% of the unit (GEBCO 2024 and GHSL 2025).

03Units

54 units inside Aichi Prefecture

Each unit has its own page.

Boundary licences: Open Data Commons Open Database License 1.0 · Creative Commons Attribution-ShareAlike 2.0.

Unit Code People (GHSL) People (WorldPop) Area km² Per km² Share Coast ≤ 10 m
Agui – 52,283 52,283 23.65 2,211 0.7% 13,122
Ama – 74,116 64,724 27.46 2,699 1% 0
Anjo – 208,368 214,182 86.02 2,422 2.7% 15,242
Ansai – 6,222 4,529 66.91 93 0.1% 293
Chiryu – 38,561 35,230 16.36 2,357 0.5% 0
Chita – 45,629 52,251 46.08 990 0.6% 7,873
Fuso – 30,418 31,824 11.27 2,699 0.4% 0
Gamagori – 72,230 69,305 56.23 1,285 0.9% 11,380
Handa – 78,554 82,183 47.46 1,655 1% 36,042
Hekinan – 38,109 38,109 37.6 1,014 0.5% 34,074
Higashiura – 101,894 104,286 31.04 3,283 1.3% 24,142
Ichinomiya – 410,742 407,409 113.53 3,618 5.3% 326,741
Inazawa – 152,934 139,185 79.44 1,925 2% 139,383
Inuyama – 132,650 131,693 74.82 1,773 1.7% 0
Iwakura – 97,973 93,647 10.49 9,340 1.3% 59,168
Kanie – 59,724 54,565 11.14 5,361 0.8% 0
Kariya – 164,281 171,698 50.46 3,256 2.1% 77,973
Kasugai – 347,174 348,500 92.55 3,751 4.5% 1,008
Kita Nagoya – 106,551 111,473 18.32 5,816 1.4% 0
Kiyosu – 53,654 51,285 17.36 3,091 0.7% 0
Komaki – 85,559 93,647 62.89 1,360 1.1% 9,059
Kounan – 89,457 81,731 30.16 2,966 1.2% 0
Kouta – 48,750 51,626 56.8 858 0.6% 6,028
Mihama – 8,983 8,205 46.28 194 0.1% 1,198
Minami Chita – 6,546 4,765 36.3 180 0.1% 231
Miyoshi – 49,883 49,883 32.2 1,549 0.6% 0
Nagakute – 25,298 25,298 21.5 1,177 0.3% 0
Nagoya – 2,294,809 2,289,429 329.64 6,962 29.8% 896,088
Nishio – 182,480 184,408 160.58 1,136 2.4% 110,579
Nisshin – 144,299 147,205 34.93 4,131 1.9% 0
Oguchi – 62,330 56,946 13.52 4,610 0.8% 0
Oharu – 117,515 117,515 6.59 17,832 1.5% 71,891
Okazaki – 353,176 373,085 386.94 913 4.6% 25,452
Oobu – 85,823 93,935 33.65 2,550 1.1% 29,954
Owariasahi – 89,567 89,567 21.11 4,243 1.2% 0
Seto – 141,701 133,257 111.38 1,272 1.8% 0
Shinshiro – 50,900 40,027 498.84 102 0.7% 0
Shitara – 5,651 3,448 274.43 21 0.1% 0
Tahara – 48,364 39,273 190 255 0.6% 10,916
Takahama – 36,681 35,061 12.99 2,824 0.5% 0
Taketoyo – 18,515 17,697 26.07 710 0.2% 3,630
Tobishima – 18,459 10,252 24.01 769 0.2% 3,330
Tokai – 112,473 113,185 43.38 2,593 1.5% 37,506
Tokoname – 65,943 66,931 55.72 1,183 0.9% 8,043
Touei – 3,991 2,289 123.26 32 0.1% 0
Tougou – 29,510 28,207 17.97 1,642 0.4% 0
Toyoake – 71,594 65,411 23.47 3,050 0.9% 5,334
Toyohashi – 352,135 373,272 260.49 1,352 4.6% 111,098
Toyokawa – 190,032 192,737 160.11 1,187 2.5% 56,107
Toyone – 1,057 598 156.03 7 0% 0
Toyota – 444,412 431,063 918.68 484 5.8% 5,862
Toyoyama – 20,805 22,771 6.15 3,383 0.3% 0
Tsushima – 128,036 114,219 25.01 5,119 1.7% 21,221
Yatomi – 52,555 51,611 48.64 1,080 0.7% 513
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
None at this resolution
Bandari
None at this resolution
Viwanja vya ndege
None at this resolution
Major roads
None at this resolution
Reli
None at this resolution
Rivers and lakes
None at this resolution
05Hatari

Risk values

Values when released. Subnational risk values for Aichi Prefecture publish with the edition from The Global Risks Index. Until then, run a scenario on open data for Japan.
Run a scenario Hazards Domain indices
06Neighbours

Neighbouring units

07Vyanzo

Sources, credits and licences

ADM1 boundaries
geoBoundaries (William & Mary geoLab), gbOpen JPN ADM1, source: OpenStreetMap, Wambacher © 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.
ADM2 boundaries
geoBoundaries (William & Mary geoLab), gbOpen JPN ADM2, source: OpenStreetMap, Wambacher © OpenStreetMap contributors, licence: Creative Commons Attribution-ShareAlike 2.0 (share-alike: this boundary layer is offered under the same licence) · source · represents 2017. Offered under the same licence (Creative Commons Attribution-ShareAlike 2.0), 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.

Hali

Mbinu, muundo na fasili za The Global Risks Index ni rasimu ya kazi ya maandalizi (2026), inayosambazwa kwa mapitio na maoni na si kwa utekelezaji. Hakuna thamani itakayoonekana hadi toleo litakapotolewa kutoka kato la ushahidi linalosimamiwa; kisha thamani zitakuwa na vipindi, madaraja, vyanzo na njia yake ya masahihisho. Viigaji huendesha mbinu zilizochapishwa kwa namba unazochagua na kamwe havionyeshi thamani ya NXS-GRX.

A country profile reads public evidence about a place. It is not a statement by or about the policy of any government, takes no position on the status of any territory, and does not imply a national programme or participation. Names follow UN M49.

NXS-GRX si nini

NXS-GRX ni taarifa ya utafiti na uchambuzi wa hatari. Si daraja la mikopo wala la ESG na haitumii kipimo chochote cha daraja, si kigezo cha vyombo vya fedha, si takwimu rasmi, si onyo la dharura wala uainishaji rasmi, na si ushauri. Haipaswi kutumiwa kutathmini watu binafsi. Madaraja ya hatari ni mikanda kwenye kipimo kilichochapishwa, kamwe si mpangilio wa nchi au watu.

Ishara za Pulse na uwezekano wa mtazamo ni taarifa za kukaguliwa na mamlaka husika, kamwe si maonyo ya umma; maonyo rasmi hutoka tu kwa mamlaka zilizopewa jukumu.

Taasisi na vyanzo

Nexus Consortium inasimamiwa na taasisi tatu huru zisizo za faida: The Global Centre for Risk and Innovation (GCRI), kupitia GCRI US huko Washington, DC na GCRI Canada huko Ontario, huku GCRI Canada ikiwa Taasisi Kiongozi, Sekretarieti ya Muungano na shirika kiongozi la mikataba; The Global Risks Forum (GRF); na The Global Risks Alliance (GRA). Watoa huduma za teknolojia, miundombinu na huduma hufanya kazi na Muungano kwa umbali chini ya makubaliano ya maandishi, kama kila mhusika mwingine wa nje katika muundo wa umma, sekta binafsi na sayari, na hawana jukumu lolote katika usimamizi wake.

Kila thamani ina utajo wa vyanzo vyake, ambavyo hubaki na leseni zao. Majina ya nje yanatajwa kwa ajili ya mwingiliano tu. Maandishi yaliyoandikwa na Nexus yanakusudiwa kuwa chini ya CC BY 4.0 yatakapotolewa.

Avis en français

La méthodologie et les définitions du NXS-GRX sont un projet de travail préparatoire (2026). Le NXS-GRX est une information de recherche et d’analyse des risques : ni notation, ni indice de référence financier, ni statistique officielle, ni alerte, ni conseil. Les classes de risque sont des bandes sur une échelle publiée, non des classements.