A basic question with no consensus: Where are the forests?

A deceptively simple question underlies many global environmental policies: where, exactly, are the world’s forests? A new study suggests the answer depends heavily on which map one consults—and that the differences are large enough to reshape climate targets, conservation priorities, and development spending.

Researchers Sarah Castle, Peter Newton, Johan Oldekop, Kathy Baylis, and Daniel Miller compared ten widely used global forest datasets derived from satellite imagery. These products underpin everything from carbon accounting to biodiversity assessments. Yet they rarely agree. Across areas identified as forest by at least one dataset, only about 26% was classified as forest by all of them. Even after adjusting maps to a common spatial scale, agreement improved only modestly.

The divergence stems partly from definitions. Some datasets treat sparsely wooded landscapes as forest, while others require dense canopy. A 10% canopy threshold, for instance, includes savannas and open woodlands; a 70% threshold captures only closed forest. Resolution also matters: high-resolution imagery can detect narrow riparian strips or small fragments that coarser data overlook. Differences in sensors, algorithms, and training data introduce further variation.

Patterns of disagreement are uneven. Moist tropical forests, where tree cover is continuous, show relatively high consistency. Dry forests and fragmented landscapes show far less, with some biomes reaching consensus on as little as 12% of forested area—often where conservation decisions are most contested.

Case studies illustrate the practical consequences. In Kenya, estimates of forest carbon ranged from roughly 2% to 37% of national biomass carbon depending on the dataset used. Maps that produced similar totals did not necessarily agree on where carbon was stored, complicating mitigation planning. In India, estimates of forest-proximate people living in poverty ranged from about 23 million to more than 250 million using identical socioeconomic data but different forest maps. In Brazil, even datasets tracking forest loss overlapped on less than half of mapped deforestation affecting habitat for the endangered white-cheeked spider monkey.

Satellite-derived maps now form the empirical backbone of environmental governance. Governments use them to report climate progress, NGOs to target interventions, and investors to assess nature-related risk. The study does not identify a single “correct” dataset. Instead, it urges treating forest estimates as ranges, testing results across multiple products, and improving standardization. Before deciding how to manage forests, policymakers may first need to agree on where they are.

The full piece: news.mongabay.com/2026/…