Sucess Stories

Supporting agricultural and food security decisions

For correct agricultural and food security decisions, there is a need for accurate information throughout the growing season. In several countries there is a large contribution of EO data in this decision process. Two examples of a good integration of EO data in this process are provided in Senegal and Brazil.

Service provider: VITO nv
User/Customer: Centre Suivi Ecologique, Senegal and CONAB, Brazil
EOservice: Supporting agricultural and food security decisions
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Source: Vito

Food security is a major issue for the people in the Sahelian countries like Senegal. Their agriculture is primarily based on rainā€fed crops and as such is the impact of the climatic variability in their region very high. The start of the growing season is especially crucial since decision on resowing of failed crops need to be made, this period is therefore closely monitored by national and regional early warning systems for food security. In fact, a significant delay in crops installation, as well as biotic or abiotic stress that may adversely affect the productive performance of crops, might cause a rapid increase of food prices in the consumer markets, limiting the access to food by the poorest fringes of population.

The case of Brazil is slightly different, since Brazil is known as a leading producer of e.g. grains, sugarcane and coffee. In this case the focus is less on food security for the population but more on overall production which will also result in food prices.

Accurate and timely information on the growing season is of the utmost importance for decision making. In Senegal the GTP gathers every ten days to discuss the ongoing growing season. This means that the remote sensing data needs to be ready at the latest 2 days after the decade for the experts to use and discuss this during the meeting. In Brazil there is the same need to provide accurate and timely information for the Brazilian agencies dealing with agriculture at national level and local farmers throughout the country.

With the offered EO data and indicators Brazilian and Senegalese remote sensing experts from CONAB and CSE are able to show decision makers the effects on crop growth of the current climatic / environmental situation. Indicators like VPI, (Vegetation Productivity Indicator) make a comparison of the current situation with what can historically be expected in the region. Linking the 10 daily archive of these EO data indicators allows the local experts to already evaluate the ongoing season much earlier than the field surveys which are traditionally scheduled near the end of the growing season.

Experts from the Ministries in Senegal and the CSE assure us that the products delivered by GMFS enable them to compare and validate their own products, which enables them to develop further tools for faster and more adequate decisions.

Traditionally the agricultural and food security information are collected by field teams which means that; the data could be subject to bias (survey route dependant, interpretation,..), collecting the data is time consuming, that this collection can only be done once or twice per growing season. EO data supports these activities. Remote sensing data gives the agricultural experts a timely (10 daily), accurate and independent overview of the complete country. This information in combination with meteo data and field observation supports the decision makers in making the right choices.

In 2007 the beginning of the crop season was characterized by a strong irregularity in the installation of the rainy season on western coastal region of the Sahel. In Senegal, in particular, the delay of rainfall at the end of June determined the sowings failure. During that period the local experts of the CSE made use of EO data for the follow up of the growing season and despite the good reprise of the rains in August and September their EO based tool predicted in September a reduced production in the rain fed agriculture. This was much later confirmed during the national agricultural survey. In other words the EO data provided substantial support in decision making for the implementation of appropriate interventions aimed to manage the risk of food insecurity in time.