FAO issues forest monitoring good practices for tree crop commodities and smallholders

Rome – The Food and Agriculture Organization of the United Nations (FAO) today published new guidance on forest monitoring, including on how to map and monitor tree-based agricultural commodities such as those produced in agroforestry systems. Launched today at the GeoField 2026 Convening, the Forest monitoring good practices: mapping tree crop commodities provides a comprehensive framework for using earth observation and geospatial data to identify the presence of crops like cocoa, coffee, rubber and palm oil.

From satellite images, a shaded cocoa plantation or a coffee agroforestry system can look nearly identical to a natural forest. The new guidance, intended for use by a broad range of actors, including national governments, private sector operators, civil society and researchers, sets out a methodology for gathering accurate data that reliably distinguishes between natural forests and farms cultivating tree crops.

“This technical publication comes at an important moment as international markets increasingly seek assurance that agricultural products are not linked to forest loss,” said Zhimin Wu, FAO Assistant Director-General and Director of the Forestry Division.

Why mapping tree crop commodities matters

While cereal crops such as wheat, maize and rice form the backbone of the global food trade, tree crops like cocoa, coffee and palm oil are among the highest value agricultural products traded globally.

Tree crop commodities are mostly grown in tropical countries and smallholder family farmers produce 80 per cent of the world’s coffee. In countries like Ghana and Côte d’Ivoire, cocoa is a primary source of income for most smallholder families.

Yet smallholders often manage small, irregularly shaped plots hidden under dense forest canopies, and without accurate mapping data, these producers are at risk of being excluded from global markets that are increasingly requesting transparent and responsible sourcing information.

Key recommendations

The good practices outline a sophisticated multi-step process for generating reliable commodity maps. Rather than relying on a single data source, the FAO recommends a "convergence of evidence" approach that integrates satellite imagery with ground-level intelligence.

Key recommendations include moving beyond traditional optical satellite images, which are often blocked by clouds in tropical regions and instead combining optical data with other sensors to "see through" weather patterns and measure the physical structure and height of vegetation.

The framework highlights the use of advanced algorithms and artificial intelligence to identify complex patterns in how crops are planted, helping to differentiate between the random growth of a forest and the managed rows or clusters of a farm.

It recommends verifying mapping produced with satellite imagery and radar by comparing it with reference data such as high-resolution drone imagery, field data and input from local experts.

It advocates for the use of standardised definitions for land cover, land use and forests so that all data is globally compatible and, for transparency, providing metadata with every map to explain how it was made, what the limitations may be and ensuring data sharing complies with privacy laws.

The publication, co-authored by a large span of actors from the public and private sector, makes the case for publicly available open data to support transparent and sustainable supply chains.

Good practices on forest monitoring: inclusive smallholder data governance

A second new FAO publication, Forest monitoring good practices: inclusive smallholder data governance, was also launched today at the GeoField 2026 Convening.

The publication provides an overview of the smallholder data landscape, including what, why and how data is collected, gathered and managed.

The publication explains the main risks and inequalities smallholder farmers face in how their data is collected and used, and recommends fairer data practices, shared standards, farmer-focused digital systems and better support to help farmers understand and manage their data.