The JRC (Joint Research Center), internal scientific service of the European Commission and the OSS, in collaboration with GMES & Africa and the North Africa Consortium are organizing a training session which will be dedicated to the use of the statistical tool CST for crop yield forecasting.
This session will be secured by the JRC experts and will aim to:
- Train national task leaders (especially Earth Observation experts from national mapping centers and space agencies) as well as experts from ministries of agriculture in the area of remote sensing yield forecasting.
- Stimulate exchanges between national task leaders, end users interested in crop production forecast and international experts.
- Capitalize the experiences of national task leaders and agricultural managers.
Members of other GMES consortia will be given 6 seats. Interested persons are requested to send their CV to the OSS North Africa Consortium at the following address: email@example.com, before June 6, 2021.
The workshop program will be delivered in English and French. The remote training will take place via the Zoom videoconference platform. A workshop kit, including a set of documents and working tools, will be handed over to participants before the start of the workshop. The training sessions will be streamed live on social media and their video recordings, as well as the educational material used during the workshop will be posted free of charge after the training.
The training materials will be shared after the training and will be available and accessible for free on the GMES & Africa digital training platform.
CST stands for Crop growth monitoring system (CGMS) Statistical Tool. CGMS is the system developed by the MARS project of the European Commission to simulate crop growth spatially (on a regular grid) over the European Union.
It is based on the WOFOST crop model which produces crop indicators (e.g. biomass) at grid and administrative unit levels for about 10 crops during the season. CST is the statistical module that relates crop yield indicators i.e. the output of CGMS, weather or EO variables, to yield statistics through either regression analysis or the so-called scenario analysis. The principle of regression analysis is to analyse the relationship between past indicators and yield statistics at a given time in the season to predict yield for the current crop season whereas the scenario analysis searches for past years that are similar to the current season in terms of indicators and combines their yields to make a forecast.
Note that countries that do not have a CGMS like system can still access weather and EO indicators as these are available at administrative unit level on several platforms (e.g. ASAP, the JRC early warning system, but also FAO GIEWS or WFP seasonal explorer.