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='''Gathering data and getting them right. '''= ='''Gathering data and getting them right. '''=
-'''[[Chapter6|Chapter 6]].''' The two basic modelling options: gridding before modelling, and modelling before gridding. Advantages and disadvantages in terms of errors, labour and accuracy of forecasts. +'''[[Chapter6|Chapter 7]].''' The two basic modelling options: grid-based and station-based monitoring
'''[[Chapter7|Chapter 7]].''' Setting up a monitoring network. '''[[Chapter7|Chapter 7]].''' Setting up a monitoring network.

Revision as of 14:36, 27 July 2006

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 7. Setting up a monitoring network.

Chapter 8. Selection of reference periods: a compromise between statistical significance and agronomic significance.

Chapter 9. Practical introduction to Geostatistics and the spatial interpolation of agroclimatic and other variables. This contains a description of LocClim and SEDI

Chapter 10. Development of practical and simplified PET and radiation computation procedure.

Chapter 11. Preparation of ten-daily PET maps (36 dekads per calibration year)

Chapter 12. Preparation of ten-daily rainfall maps (36 dekads/year). If necessary, develop a technique to derive/interpolate rainfall based on Global Telecommunications System (GTS of WMO) and Japanese meteorological satellite images

Chapter 13. Analysis of time series of climate and crops to identify trends, if they are present. Construction of detrended crop yield time series

Chapter 14. Preparation of polygons for main crop growing areas in the country and define cropping practices and conditions (planting/transplanting, soil features, irrigation water amounts...)

Using satellite imagery

Chapter 15. Development of a standard procedure to define actual phenology (in particular crop planting date), based on local practice and satellite imagery

Chapter 16. Extract Normalised Difference Vegetation Index (NDVI) images for the country from the global data

Running the FAO water balance model

Chapter 17. 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 AMS for the historical time period, extract average water balance parameters over main crop growing areas

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).

Data and information dissemination

Chapter 21. Using other monitoring products in the forecast

Chapter 22. Prepare write-up of the products above as inputs to national crop monitoring bulletins

Setting up a crop monitoring system

Chapter 23. Resources required

Chapter 24. Where to get assistance


Glossary


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