Over the last decade, food security has become one of the world’s greatest challenges. It is ranked second among the 17 Sustainable Goals in the United National 2030 Development Agenda and other SDGs are also directly related to the agriculture impact on health, poverty, water and climate. To effectively address this challenge, a wide range of timely data and information on food production, agricultural practices and natural ressources is required to be available, analyzed and understood. The requirements for agriculture information are quite specific because of the strategic importance and the dynamic nature of food production, food availability and food prices in any country.

Agricultural monitoring at national scale is a prerequisite for assessing and analyzing the agricultural resources by mandated authorities, usually the agricultural National Statistical Offices (NSOs). In general NSO collect national agricultural monitoring data using farm and household surveys. Recognizing the limitations of the current agricultural data collection in developing, emerging as well as in industrialized countries, key international bodies and UN agencies aim to improve and enhance the current practices in agriculture data collection and have referred to the potential of satellite Earth Observation for agricultural statistics.

The objective of the Sen4Stat project is to facilitate the uptake of EO information by the NSOs supporting the agricultural statistics. Special attention will be given developing and demonstrating EO products and best practices for agriculture monitoring relevant for SDG reporting and to monitore their progress at national scale.

For a successful uptake of EO information by agricultural NSO, specific steps in remote sensing have to be achieved in terms of additional information products, methodological development and support for effective integration in their operational workflows and reporting obligations. To raise the awareness of NSO about EO and to lower the technical entry barrier a set of activities are identified:

  • Engage with NSOs and develop together dedicated applications and workflows to integrate EO agricultural information in their operations;
  • Identify and specify EO products and services suitable to increase the efficiency and temporal-spatial coverage of national agricultural statistics;
  • Develop data analytical tools for combining national statistical data sets, including household surveys, with satellite observations and derived EO information;
  • Develop Algorithm Theoretical Basis Documents (ATBDs) along with open source code for agricultural EO products based on Sentinel-1 & -2 responding to the user requirements;
  • Demonstrate and validate the developed products for agricultural statistics at national scale;
  • Prepare and facilitate the transfer of developed EO products and services to the NSO including capacity building and demonstrating cloud computing capabilities.