Eritrea vs Sri Lanka: Index of forest extent, Index

Eritrea
91.34
in 2023
Sri Lanka
90.92
in 2023
Eritrea rank
165th
Sri Lanka rank
166th

Index of forest extent, Index over time

  • Eritrea
  • Sri Lanka
020406080100199220072023

How they compare

Eritrea currently reports 91.34 against 90.92 in Sri Lanka, a difference of 0.42.

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

Eritrea ranks 165th and Sri Lanka ranks 166th of 223 countries.

Eritrea has averaged higher in every one of the 4 decades both report.

Head to head by decade

Decade Eritrea Sri Lanka Difference Ahead
1990s 98.95 97.22 1.73 Eritrea
2000s 96.45 92.42 4.03 Eritrea
2010s 93.69 91.55 2.14 Eritrea
2020s 91.76 91.13 0.6301 Eritrea

Averages of every year both report within each decade.

Frequently asked questions

Which has higher index of forest extent, index, Eritrea or Sri Lanka?
Eritrea, at 91.34 against 90.92 in Sri Lanka as of 2023.
What is the difference in index of forest extent, index between Eritrea and Sri Lanka?
0.42, with Eritrea ahead.
How many years of comparable data are there for Eritrea and Sri Lanka?
32 years are reported by both, from 1992 to 2023.
How do Eritrea and Sri Lanka rank globally for index of forest extent, index?
Eritrea ranks 165th and Sri Lanka ranks 166th 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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Eritrea vs Sri Lanka: 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/eritrea/sri-lanka/

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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.