China vs Malta: Index of forest extent, Index

China
140.04
in 2023
Malta
131.43
in 2023
China rank
11th
Malta rank
13th

Index of forest extent, Index over time

  • China
  • Malta
050100150199220072023

How they compare

China currently reports 140.04 against 131.43 in Malta, a difference of 8.61.

That makes China's figure about 1.1 times Malta's.

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

China ranks 11th and Malta ranks 13th of 223 countries.

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

Head to head by decade

Decade China Malta Difference Ahead
1990s 104.31 100 4.31 China
2000s 116.46 100 16.46 China
2010s 129.96 109.14 20.82 China
2020s 138.29 131.43 6.86 China

Averages of every year both report within each decade.

Frequently asked questions

Which has higher index of forest extent, index, China or Malta?
China, at 140.04 against 131.43 in Malta as of 2023.
What is the difference in index of forest extent, index between China and Malta?
8.61, with China ahead.
How many years of comparable data are there for China and Malta?
32 years are reported by both, from 1992 to 2023.
How do China and Malta rank globally for index of forest extent, index?
China ranks 11th and Malta ranks 13th 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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China vs Malta: 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/china/malta/

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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.