Italy vs Montenegro: Index of forest extent, Index

Italy
125.59
in 2023
Montenegro
125.32
in 2023
Italy rank
16th
Montenegro rank
17th

Index of forest extent, Index over time

  • Italy
  • Montenegro
050100150199220072023

How they compare

Italy currently reports 125.59 against 125.32 in Montenegro, a difference of 0.27.

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

Italy ranks 16th and Montenegro ranks 17th of 223 countries.

Across the 4 decades both report, Italy averaged higher in 2 and Montenegro in 2.

Head to head by decade

Decade Italy Montenegro Difference Ahead
1990s 103.52 101.73 1.79 Italy
2000s 111.88 111.75 0.1243 Italy
2010s 119.68 125.32 5.64 Montenegro
2020s 124.55 125.32 0.7768 Montenegro

Averages of every year both report within each decade.

Frequently asked questions

Which has higher index of forest extent, index, Italy or Montenegro?
Italy, at 125.59 against 125.32 in Montenegro as of 2023.
What is the difference in index of forest extent, index between Italy and Montenegro?
0.27, with Italy ahead.
How many years of comparable data are there for Italy and Montenegro?
32 years are reported by both, from 1992 to 2023.
How do Italy and Montenegro rank globally for index of forest extent, index?
Italy ranks 16th and Montenegro ranks 17th 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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Italy vs Montenegro: 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/italy/montenegro/

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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.