Iran vs Moldova: Index of forest extent, Index

Iran
118.22
in 2023
Moldova
117.41
in 2023
Iran rank
25th
Moldova rank
28th

Index of forest extent, Index over time

  • Iran
  • Moldova
0255075100125199220072023

How they compare

Iran currently reports 118.22 against 117.41 in Moldova, a difference of 0.81.

The two have swapped places 3 times across 32 shared years of data; in 1992 it was Moldova ahead.

Iran ranks 25th and Moldova ranks 28th of 223 countries.

Across the 4 decades both report, Iran averaged higher in 3 and Moldova in 1.

Head to head by decade

Decade Iran Moldova Difference Ahead
1990s 100.96 102.02 1.06 Moldova
2000s 108.93 108.73 0.1935 Iran
2010s 117.29 116.3 0.9828 Iran
2020s 118.02 117.41 0.615 Iran

Averages of every year both report within each decade.

Frequently asked questions

Which has higher index of forest extent, index, Iran or Moldova?
Iran, at 118.22 against 117.41 in Moldova as of 2023.
What is the difference in index of forest extent, index between Iran and Moldova?
0.81, with Iran ahead.
How many years of comparable data are there for Iran and Moldova?
32 years are reported by both, from 1992 to 2023.
How do Iran and Moldova rank globally for index of forest extent, index?
Iran ranks 25th and Moldova ranks 28th 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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Iran vs Moldova: Index of forest extent, Index. Statizoid, drawing on International Monetary Fund. Retrieved 03 October 2026, from https://climate.statizoid.com/compare/index-of-forest-extent-index-not-applicable/iran-islamic-rep/moldova/

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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.