Global Strategy to Improve Agricultural and Rural Statistics

Workshop on Master Sampling Frames in Guinea Fosters Advanced Sampling and Data Analysis Skills

23/11/2023

A training workshop on Master Sampling Frames (MSF) has recently concluded in Conakry, marking a crucial step forward in the development of Guinea's agricultural statistics capabilities. The training, which was held from October 23 to 27, 2023 - part of the second phase of the Global Strategy to Improve Agricultural and Rural Statistics (GSARS II)- was facilitated by Audrier Sanou and Elisée Tchana and has laid a robust foundation for enhanced sampling strategies for agricultural surveys. 

Central to the workshop were considerations on the structure and type of the master sampling frame (MSF), a pivotal component for the country's agricultural statistics. These discussions focused on reaching a consensus among national institutions on a sampling frame that can accommodate different existing and planned agricultural surveys in Guinea. The results were notable, leading up to the pinpointing of five key surveys: 

  1. National Census of Agriculture and Livestock (RNAE) 
  2. Agricultural Surveys (the CORE module of the initiative 50X2030) 
  3. Agricultural Losses Surveys 
  4. Market Information Systems 
  5. Surveys on Non-standard Units 

The workshop sought to improve the development and utilization of MSF for the country, focusing on the practical application of the FAO's SEPAL system and CAPI-CSPro procedures. Participants from various national institutions actively engaged in discussions on the structure and type of MSF appropriate for Guinea, laying the foundation for more accurate and comprehensive sampling strategy for agricultural surveys in the country. 

Over five days, participants were immersed in intensive training sessions that included supervised land classification, zonal statistics on land use maps, and hands-on SEPAL estimations. The workshop also included a practical field test in the Ratoma district, where participants georeferenced rice plots, collecting data that will be instrumental in refining crop area mapping models using machine learning and high-resolution spatial data. 

The workshop was well-received, with participants showing great enthusiasm and active engagement throughout the sessions. The hands-on approach not only strengthened their technical skills but also fostered a collaborative atmosphere, leading to a shared commitment to apply these new capabilities within their respective roles. 

Notably, the FAO's Representative in Guinea, Mr. Gualbert Gbehounou, played a significant role in facilitating the workshop. The FAO Guinea office was also commended for its support in organizing the training, ensuring its smooth execution. The workshop was made possible through the financial support of the European Union and the Bill & Melinda Gates Foundation, whose contributions continue to empower agricultural development initiatives across the globe.