Statistical Capacity Development
One of the key missions of FAO is to support member countries develop the capacity of their statistical systems and enable them to collect, analyze, disseminate and use relevant, reliable and timely data. By strengthening countries’ capacity in this area, FAO contributes to make available key analytical and decision-making support tools for national, regional and global evidence-based actions.
How can national governments request capacity development assistance?
National governments should discuss on an ongoing basis their statistical capacity development needs and priorities directly with their FAO country office. These needs and priorities will usually be reflected in the Country programming framework (CPF) and support will be planned in consultation with the relevant technical units and regional or sub-regional statisticians. If assistance requests are raised, the FAO country office will contact the relevant technical divisions and regional or sub-regional statisticians to analyze how the support can be provided.
FAO statistical capacity development activities are funded through:
- Technical Cooperation Programme (TCP)
- Regular programme funds allocated to technical divisions
- Extra-budgetary programmes that support statistical development.
For specific information and inquiries on FAO capacity development programmes, national governments are also encouraged to contact these programmes directly.
Statistical capacity development programmes
AI4SmallFarms and AI4Biochar
The project, 'Developing a Geodatabase in Support of Agricultural Planning', is funded by the Ministry of Agriculture, Forestry and Fisheries (MAFF) of Japan. It aims to enhance the capacity of countries in the preparation of databases of ffarmland by developing a spatial layer of rice field boundaries using freely available satellite imagery (Sentinel-2).
To this end, FAO has partnered with the University of Twente, on the development of cutting-edge methods for the delineation of agricultural field boundaries using satellite imagery and machine learning techniques in diverse types of agricultural settings.
The suitability of the geospatial layers of rice fields boundaries were also tested to support data collection of agricultural information in the context of SDG 2.4.1, one of the indicators for which FAO is custodian.
In addition, the field boundary recognition prototype was successfully tested in selected areas of Cambodia and Vietnam. Moreover, thanks to additional support from the FAO Elevate Programme, the prototype combined with the FAO BEFS Tools resulting in a new tool (AI4biochar) to assess and guide the development of a biochar market. The AI4biochar tool was then applied to biochar production from rice in Cambodia and Viet Nam. Specific training courses were provided to stakeholders in both countries on how to use the tools.
Related capacity development resources
- AI prototype for field boundaries recognition
- A prototype for automated crop boundary delineation with a focus on rice paddy fields – Technical Report
- A prototype for automated crop boundary delineation with a focus on rice paddy fields – Training Guide
- AI4Biochar calculator (.xls) AI prototype manual
- AI4Biochar leaflet
- AI4SmallFarms: A Dataset for Crop Field Delineation in Southeast Asian Smallholder Farms (journal paper)
- Expert Training | AI-based Boundary Recognition and the AI4Biochar tool (12 September 2025)
- AI4Biochar: applying AI-driven field boundary recognition to the biochar sector. FAO Statistics Working Paper Series / 25-49 (News release)
- Overview of the biochar sector in Viet Nam and the AI4Biochar tool. Technical report