This publication reviews existing approaches to assessing the spatial extent of agroforestry and explores the potential of the FRA Remote Sensing Survey (FRA RSS) as a consistent framework for large-scale monitoring. Current methods, including expert estimates, remote-sensing proxies and national surveys, remain fragmented due to differences in definitions, data sources and observation scales, limiting comparability across countries and over time. A Central America case study applying the FRA 2025 RSS methodology to 2 905 sample plots across seven countries identified three main agroforestry-related landscape types: silvopasture, agrosilviculture and agrosilvopasture. Together, these covered approximately 60 percent of the regional territory, with silvopasture being the most widespread.

While the results represent indications based on observable land-use and land-cover characteristics rather than direct measurements of agroforestry management systems, the study demonstrates the potential of FRA RSS to provide a standardized, operational and cost-efficient basis for identifying agroforestry-related landscapes. Further methodological refinement, particularly of sampling designs, interpretation protocols and integration with agricultural data, will be needed to strengthen future assessments and support more consistent evidence for land-use planning, reporting and sustainable agrifood systems.