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Introduction
Chapter 1. The raison d'être of the crop forecasting and crop forecasting methods.
Chapter 2. Overview of FAO food security work. The crop forecasting philosophy adopted by FAO.
Chapter 3. The principles of crop modelling and their implementation in the CMBox.
Chapter 4. Potential Evapotranspiration (PET) and the calculation of crop water budgets.
Chapter 6. Introduction to GIS and data formats.
Gathering data and getting them right.
Chapter 7. The two basic modelling options: grid-based and station-based monitoring
Chapter 8. Setting up a monitoring network.
Chapter 9. Selection of reference periods.
Chapter 10. Entering and importing weather data.
Chapter 11. Development of ET0 computation procedure.
Chapter 12. Preparation of ten-daily rainfall and ET0 records for crop forecasting
Chapter 13. Introduction to Geostatistics and the spatial interpolation of agroclimatic and other variables. (includes LocClim) ....
Chapter 14. Analysis of time series of climate and crops to identify trends, if they are present. Construction of detrended crop yield time series.
Chapter 15. Preparation of polygons for main crop growing areas in the country and define cropping practices and conditions.
Running the FAO water balance model
Chapter 16. Understanding the FAO Water Balance Model. Description of crops that can be monitored, including specific crops like irrigated crops.
Chapter 17. Read all data prepared above into the AgroMetShell crop simulation software (AMS)
Chapter 18. Run Water Balance model for both historical and current seasons. Understanding the output of the model.
Chapter 19. Practical introduction to multiple regression techniques and the selection of variables through a principal components analysis
Chapter 20. Calibrate crop yields against water balance outputs and other variables against and validate the coefficients.
Chapter 21. Using equations derived under 19) above, compute crop yield maps and derive tables of agricultural statistics from the maps (the forecasts).
Using satellite imagery
Chapter 5. Introduction to Remote Sensing (CCD and NDVI) and its role in crop forecasting.
Chapter 22. Development of a standard procedure to define actual phenology (in particular crop planting date), based on local practice and satellite imagery
Chapter 23. Extract Normalised Difference Vegetation Index (NDVI) images for the country from the global data
Data and information dissemination
Chapter 24. Using other monitoring products in crop forecasting
Chapter 25. Prepare write-up of the products above as inputs to national crop monitoring bulletins
Setting up a crop monitoring system
Chapter 26. Introduction
Chapter 27. Resources required
Chapter 28. Where to get assistance