Argentina vs Myanmar: Forest area, 1000 Hectares

Argentina
28,246
in 2023
Myanmar
27,675
in 2023
Argentina rank
20th
Myanmar rank
22nd

Forest area, 1000 Hectares over time

  • Argentina
  • Myanmar
010.0k20.0k30.0k40.0k199220072023

How they compare

Argentina currently reports 28,246 against 27,675 in Myanmar, a difference of 571.

The two have swapped places 1 time across 32 shared years of data; in 1992 it was Myanmar ahead.

Argentina ranks 20th and Myanmar ranks 22nd of 225 countries.

Across the 4 decades both report, Argentina averaged higher in 1 and Myanmar in 3.

Head to head by decade

Decade Argentina Myanmar Difference Ahead
1990s 34,200 36,826 2,626 Myanmar
2000s 31,954 33,326 1,372 Myanmar
2010s 29,331 30,137 805.9 Myanmar
2020s 28,410 28,109 300.2 Argentina

Averages of every year both report within each decade.

Frequently asked questions

Which has higher forest area, 1000 hectares, Argentina or Myanmar?
Argentina, at 28,246 against 27,675 in Myanmar as of 2023.
What is the difference in forest area, 1000 hectares between Argentina and Myanmar?
571, with Argentina ahead.
How many years of comparable data are there for Argentina and Myanmar?
32 years are reported by both, from 1992 to 2023.
How do Argentina and Myanmar rank globally for forest area, 1000 hectares?
Argentina ranks 20th and Myanmar ranks 22nd of 225 countries.
Where does this data come from?
International Monetary Fund, published as Forest area, 1000 Hectares (Not Applicable). Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Argentina vs Myanmar: Forest area, 1000 Hectares. Statizoid, drawing on International Monetary Fund. Retrieved 18 August 2026, from https://climate.statizoid.com/compare/forest-area-1000-hectares-not-applicable/argentina/myanmar/

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About this data

Indicator
Forest area, 1000 Hectares (Not Applicable)
Source
International Monetary Fund
Licence
IMF Terms and Conditions (attribution required)
Coverage
236 places, 7,520 data points, 1992–2023
Last refreshed

This dataset provides information on global climate and weather patterns, providing insights into temperature variations, land cover accounts, and shifts in mean sea levels.