Forests
Is India losing forest?
Both statements are true, and the reason is the definition. India's official assessment reports a net increase in forest cover, because forest cover counts canopy of any kind. The satellite series reports cumulative tree-cover loss, because it counts canopy disappearing whatever it was. A natural forest replaced by a plantation of the same density is no change to the first measure and a loss to the second.
The disagreement, stated exactly
Neither number is wrong. They are answers to different questions and they are quoted as though they were answers to the same one.
The India State of Forest Report 2023 records a net increase of 156.41 km² in national forest cover against its own revised 2021 figure. That is arithmetic on the report's own table and it is not in dispute.
The Hansen series, published by Global Forest Watch, records cumulative tree-cover loss across India since 2001 at a 30 per cent canopy threshold. That is a measurement from imagery and it is also not in dispute.
The conflict is definitional. Forest cover counts canopy above 10 per cent density on land over a hectare, whatever species and whoever owns it. Tree-cover loss counts canopy disappearing, including a plantation harvested on schedule. Convert forest to plantation and the first measure records nothing while the second records a loss — and later a gain.
- Net change
- Gains minus losses. It conceals both, which is why the components matter more than the total.
- Revised base
- ISFR restates its previous figure when methods change. A change is only meaningful against the revised base the report itself publishes.
- Gross loss
- What the satellite series reports. Not netted against regrowth.
The number that survives either definition
This is division on two figures in the same table of the same report. It needs no second source and it survives any argument about definitions.
National net change in forest cover, 2021 to 2023
156.41 km²
FSI, ISFR 2023, Table 2.2
Largest single-state loss — Madhya Pradesh
371.54 km²
FSI, ISFR 2023, Table 2.2
Largest single-state gain — Mizoram
241.73 km²
FSI, ISFR 2023, Table 2.2
National forest cover, 2023
7,15,342.61 km²
FSI, ISFR 2023, Table 2.3
Cumulative tree-cover loss, satellite series
2.43 million hectares
Hansen / UMD via Global Forest Watch, 30% threshold
Madhya Pradesh alone lost more than twice the entire national net gain. Mizoram alone gained more than the whole national net. Both sentences are arithmetic on the report's own published numbers, and neither is an interpretation.
And the scale is worth holding: 156.41 km² on a base of 715,342.61 km² is a change of about two hundredths of one per cent — well inside what a mapping method can produce by changing nothing on the ground.
How to read the two series together
They can be read together. They cannot be reconciled into one number.
Use ISFR for the legal and administrative picture: what the Government of India assesses, reports to FAO, and manages against. It is the authoritative national number.
Use the satellite series for change detection: where canopy went, in which year, at a stated threshold. It sees things a biennial national assessment cannot.
Do not average them, and do not treat one as a correction of the other. Where a claim needs a single number, state which definition it is using and why — that sentence is the finding, not an aside.
What this number cannot tell you
- Neither series measures forest quality, biodiversity or carbon.
- Neither can attribute a change to a cause. A loss pixel does not say what happened on it.
- A national net figure cannot describe any state, and most states move against the national direction.
- A two-year change inside a two-hundredths-of-a-per-cent band cannot support a claim about trend.
Where this comes from
Every figure above is read out of one of these, at the address printed beside it.
- India State of Forest Report 2023, Volume 1 Forest Survey of India, Ministry of Environment, Forest and Climate Change · Tables 2.2 and 2.3, and the paragraph following 2.2
- Global Forest Watch — India World Resources Institute, using Hansen / University of Maryland data · The cumulative loss series and its threshold
Reuse freely — CC BY 4.0. The grant covers this page. Each source above keeps its own terms, which is why every one of them is named.
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