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Contents
Introduction
Chapter 1. The "raison d'être" of the crop forecasting.
Chapter 2. Overview of FAO food security work. Presentation of the overall crop forecasting philosophy adopted by FAO
Chapter 3. Introduction into the principles of crop modelling and their implementation in the CMBox. The principle of indicators like ETa and the WSI index.
Chapter 4. Potential Evapotranspiration (PET) and its role in the calculation of crop water budgets and crop forecasting
Chapter 5. Introduction to Remote Sensing (CCD and NDVI) and its role in crop forecasting
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. Introduction to Geostatistics and the spatial interpolation of agroclimatic and other variables. (includes LocClim and SEDI) ....
Chapter 11. Development of simplified PET and radiation computation procedure.
Chapter 12. Preparation of ten-daily PET maps
Chapter 13. Preparation of ten-daily rainfall maps
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.
Using satellite imagery
Chapter 16. Development of a standard procedure to define actual phenology (in particular crop planting date), based on local practice and satellite imagery
Chapter 17. Extract Normalised Difference Vegetation Index (NDVI) images for the country from the global data
Running the FAO water balance model
Chapter 18. Crops that can be monitored, including specific crops like irrigated crops.
Chapter 19. Read all data prepared above into the AgroMetShell crop simulation software (AMS)
Chapter 20. Run AMS for the historical time period, extract average water balance parameters over main crop growing areas
Chapter 21. Practical introduction to multiple regression techniques and the selection of variables through a principal components analysis
Chapter 22. Calibrate crop yields against water balance outputs and other variables against and validate the coefficients.
Chapter 23. Using equations derived under 19) above, compute crop yield maps and derive tables of agricultural statistics from the maps (the forecasts).
Data and information dissemination
Chapter 23. Using other monitoring products in crop forecasting
Chapter 24. Prepare write-up of the products above as inputs to national crop monitoring bulletins
Setting up a crop monitoring system
Chapter 25. Resources required
Chapter 26. Where to get assistance