Global dataset reveals Indian deforestation drivers

A new global dataset developed by the World Resources Institute (WRI), Google Deep Mind and The Sustainability Consortium determines the reasons for forest loss at one-kilometre spatial resolution, as highlighted by a Mongabay-India (MI) report. For Asia, the analysis reveals that wildfires were the dominant drivers at 65.4% followed by logging at 26.3% and permanent agriculture at 2.5%.

The WRI Global Forest Watch (GFW) interactive map reveals that between 2001 and 2024, 29% of tree cover loss in India resulted in deforestation, with permanent agriculture, hard commodities, and settlements and infrastructure being the dominant drivers. The map also reveals that the resulting emissions were about 15 million metric tonnes of carbon dioxide equivalent per year. When zoomed in, similar results can also be obtained for forests at the state and district-level.

However, for India, researchers point out that satellite-based mapping tools must be used along with additional field observations and biophysical data for a comprehensive understanding of deforestation drivers. They warn that this data must be used with caution and that in India the one km spatial resolution is not sufficient for a thorough analysis as India has several small patches of forest land. Therefore, satellite-based mapping tools must be used along with additional field observations and biophysical data for a comprehensive understanding of deforestation drivers.

Experts say that the definition of what constitutes a forest plays a crucial role in analysing the results of satellite imagery-based mapping tools, according to the MI report. India defines forest cover as – all land, more than one hectare in area, with a tree canopy cover of more than 10%, irrespective of ownership and legal status. Along with a multi-pronged approach, as per the MI report, experts also emphasized the need for long-term monitoring of forests for effective intervention strategies and that even small-scale forest degradation can have various impacts in the longer term that can change the nature of the ecosystem.

The study, published in Environmental Research Letters, says in its Abstract that forests are in decline worldwide due to human activities such as agricultural expansion, urbanization, and mineral extraction. Forest loss due to generally temporary causes, such as wildfire and logging, is important to distinguish from permanent land use conversion due to the differing ecological and climate impacts of these disturbances and for the purposes of developing effective policies and management strategies. Existing global maps of the drivers of forest loss that are widely used are not spatially or thematically detailed enough for decision makers at local-to-regional scales, such as governments, land managers, or companies.

The year 2024 was a record-breaking year for tropical forests globally. The world lost 18 football fields worth of tropical primary forests per minute in 2024, according to data gathered by the University of Maryland’s Global Land Analysis and Discovery (GLAD) Lab and shared on the GFW platform. Along with greenhouse gas emissions of 3.1 gigatonnes, the deforestation also resulted in significant losses to biodiversity, ecosystem services and livelihoods, globally. The data revealed that forest fires were responsible for 49.5% of this loss.

The MI report adds that understanding the drivers of forest loss is vital to devise strategies for forest conservation and restoration. Such data can also shed light on whether these factors contribute to forest loss or degradation, thus differentiating between permanent changes to forest land (forest loss) and a reduction in tree canopy or density (forest degradation).

The dataset was built by training the AI model to identify drivers of forest loss. The training samples (high-resolution 1 km grid cells with at least 0.5% tree cover loss) were visually interpreted by experts. These labelled samples provided the basis for the model to analyse and interpret satellite imagery along with relevant population and biophysical data inputs, thus associating the pattern with a driver class.

The report highlights a 2024 study by the Institute of Wood Science and Technology (ICFRE-IWST), the National Institute of Advanced Studies (NIAS) and the Indian Institute of Science (IISC), that analysed the ecological impacts of landslide-driven deforestation in and around the Kali Tiger Reserve (KTR), Karnataka. The study shows that gaining a true understanding of the drivers and impacts of deforestation requires a multi-source, multi-temporal data approach.