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| - | [[Chapter13|5.1.]]. Introduction to Geostatistics and the spatial interpolation of weather and crop data. | + | [[Chapter13|5.1]]. Introduction to Geostatistics and the spatial interpolation of weather and crop data. |
| - | [[Chapter13|5.2.]]. How to fill gaps in data records | + | [[Chapter13|5.2]]. How to fill gaps in data records |
| ===6. The FAO water balance model and its crop forecasting indicators=== | ===6. The FAO water balance model and its crop forecasting indicators=== | ||
Revision as of 13:14, 22 September 2006
Welcome to the Crop Monitoring Box documentation
1. Introduction
1.1. General introduction to crop forecasting and its methods.
1.2. Crop forecasting philosophy of FAO, an overview.
1.3. The principles of crop modelling and their implementation in the CMBox.
1.4. Crop forecasting with water budget calculations.
1.5. Introduction to CMBox software, data formats and GIS.
2. Setting up a crop monitoring network
2.1.. The two basic modelling options: grid-based and station-based
2.2.. Setting up a monitoring network.
2.3.. Selection of a reference period.
3. Gathering and calculating weather data
3.1. Entering and importing normal and actual weather data.
3.2. Computing the ET0.
3.3. Preparation of a ten-daily rainfall and ET0 database for crop forecasting
4. Gathering and calculating crop data
4.1. Analysis of time series of climate and crops to identify trends, if they are present. Construction of detrended crop yield time series.
4.2. Preparation of polygons for main crop growing areas in the country and define cropping practices and conditions.
5. Techniques to use when data are unavailable
5.1. Introduction to Geostatistics and the spatial interpolation of weather and crop data.
5.2. How to fill gaps in data records
6. The FAO water balance model and its crop forecasting indicators
6.1.. Understanding the FAO Water Balance Model. Crops that can be monitored, including irrigated crops.
6.2.. Gathering all into the FAO AgroMetShell (AMS) crop simulation software.
6.3.. Run Water Balance model for both historical and current seasons. Understanding the output of the model.
From water balance indicators to yield estimates
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.
Chapter 21. Computing crop yield maps create forecasts.
Independent indicators derived from 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. The use of Normalised Difference Vegetation Index (NDVI) images.
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