Forecasting the future of forests with AI: From counting losses to predicting risk

Nature underpins our climate, our economies, and our very lives. And within nature, forests stand as one of the most powerful pillars — storing carbon, regulating rainfall, mitigating floods, and harboring the majority of the planet’s terrestrial biodiversity.

Yet, despite their critical importance, the world continues to lose forests at an alarming rate. Last year alone, we lost the equivalent of 18 soccer fields of tropical forest every minute, totaling 6.7 million hectares — a record high and double the amount lost the year before. Today, habitat conversion is the greatest threat to biodiversity on land.

For years, satellite data has been our essential tool for measuring this loss. More recently, in collaboration with the World Resources Institute, we helped map the underlying drivers of that loss — from agriculture and logging to mining and fire — for the years 2000–2024. These maps, which are at an unprecedented 1km² resolution, provide a basis for a wide range of forest protection measures. However those insights, critical as they are, only look backward. Now, it's time to look ahead.

Why predicting deforestation is so difficult

Deforestation is fundamentally a human process driven by a complex web of economic, political, and environmental factors. It's fueled by commodity-driven expansion for products like cattle, palm oil, and soy, but also by wildfires, logging, the expansion of settlements and infrastructure, and the extraction of hard minerals and energy. Predicting the location and timing of future loss is therefore incredibly hard.

A scalable satellite approach

The pure satellite approach provides consistency, in that we can apply the exact same method anywhere on Earth, allowing for meaningful comparisons between different regions. It also makes our model future proof — these satellite data streams will continue for years to come, so we can repeat the method to give updated predictions of risk and examine how risk is changing through time.