Eswatini vs Romania: Index of forest extent, Index

Eswatini
108.12
in 2023
Romania
108.78
in 2023
Eswatini rank
50th
Romania rank
47th

Index of forest extent, Index over time

  • Eswatini
  • Romania
0255075100199220072023

How they compare

Romania currently reports 108.78 against 108.12 in Eswatini, a difference of 0.66.

The two have swapped places 2 times across 32 shared years of data; in 1992 it was Romania ahead.

Eswatini ranks 50th and Romania ranks 47th of 223 countries.

Across the 4 decades both report, Eswatini averaged higher in 2 and Romania in 2.

Head to head by decade

Decade Eswatini Romania Difference Ahead
1990s 100.92 99.97 0.9441 Eswatini
2000s 103.27 100.99 2.28 Eswatini
2010s 105.89 106.69 0.7992 Romania
2020s 107.72 108.78 1.05 Romania

Averages of every year both report within each decade.

Frequently asked questions

Which has higher index of forest extent, index, Eswatini or Romania?
Romania, at 108.78 against 108.12 in Eswatini as of 2023.
What is the difference in index of forest extent, index between Eswatini and Romania?
0.66, with Romania ahead.
How many years of comparable data are there for Eswatini and Romania?
32 years are reported by both, from 1992 to 2023.
How do Eswatini and Romania rank globally for index of forest extent, index?
Eswatini ranks 50th and Romania ranks 47th of 223 countries.
Where does this data come from?
International Monetary Fund, published as Index of forest extent, Index (Not Applicable). Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Eswatini vs Romania: Index of forest extent, Index. Statizoid, drawing on International Monetary Fund. Retrieved 22 August 2026, from https://climate.statizoid.com/compare/index-of-forest-extent-index-not-applicable/eswatini/romania/

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About this data

Indicator
Index of forest extent, Index (Not Applicable)
Source
International Monetary Fund
Licence
IMF Terms and Conditions (attribution required)
Coverage
235 places, 7,488 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.