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-'''Introduction'''+<blockquote>
-Quick overview of FAO food security work, the raison d'être of the crop forecasting and presentation of the overall crop forecasting philosophy adopted by FAO +__NOTOC__
 +==Welcome to the Crop Monitoring Box documentation==
 +------------------------------------
 +===1. Introduction===
-Introduction into the principles of crop modelling (including basic crop model overview) and their implementation in AgroMetShell and the CMBox. The principle of indicators like ETa and the WSI index. +[[Chapter1|1.1.]] General introduction to crop forecasting and its methods.
-Presentation of Potential Evapotranspiration (PET) and its role in the calculation of crop water budgets and crop forecasting +[[Chapter2|1.2.]] Crop forecasting philosophy of FAO, an overview.
-Introduction to Remote Sensing (CCD and NDVI) and its role in crop forecasting +[[Chapter3|1.3.]] The principles of crop modelling and their implementation in the CMBox.
-5) Introduction to data formats and GIS.+[[Chapter5|1.4.]] Crop yield forecasting with water balance calculations.
-Gathering data and getting them right. +[[Chapter6|1.5.]] Introduction to CMBox software, data formats and GIS.
-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. +===2. A crop monitoring network ===
-7) Selection of reference periods: a compromise between statistical significance and agronomic significance. +[[Chapter7|2.1.]] The two basic modelling options: grid-based and station-based
-8) Practical introduction to Geostatistics and the spatial interpolation of agroclimatic and other variables. This contains a description of LocClim and SEDI +[[Chapter8|2.2.]] Setting up a monitoring network.
-9) Development of practical and simplified PET and radiation computation procedure. +[[Chapter9|2.3.]] Selection of a reference period.
-10) Preparation of ten-daily PET maps (36 dekads per calibration year) +===3. Gathering and calculating weather data ===
-11) 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 +[[Chapter10|3.1]]. Entering and importing normal and actual weather data.
-12) Analysis of time series of climate and crops to identify trends, if they are present. Construction of detrended crop yield time series +[[Chapter11|3.2]]. Computing the reference evapotranspiration ET<sub>0</sub>.
-13) Preparation of polygons for main crop growing areas in the country and define cropping practices and conditions (planting/transplanting, soil features, irrigation water amounts...)+[[Chapter12|3.3]]. Preparing and using the dekadal rainfall and ET<sub>0</sub> database for crop monitoring
-Using satellite imagery+===4. Gathering and calculating crop data ===
-14) Development of a standard procedure to define actual phenology (in particular crop planting date), based on local practice and satellite imagery +[[Chapter15|4.1]]. Defining cropping practices and conditions and preparation of polygons for main crop growing areas in the country.
-15) Extract Normalised Difference Vegetation Index (NDVI) images for the country from the global data +[[Chapter14|4.2]]. Analysis of time series of climate and crops to identify trends. Detrending yield.
-Running the FAO water balance model +===5. Techniques to use when data are unavailable===
-16) Read all data prepared above into the AgroMetShell crop simulation software (AMS) +[[Chapter13|5.1]]. Introduction to Geostatistics and the spatial interpolation of weather and crop data.
-17) Run AMS for the historical time period, extract average water balance parameters over main crop growing areas+[[Chapter33|5.2]]. Filling gaps in agricultural statistics.
-18) Prcatical introduction to multiple regression techniques and the selection of variables through a principal components analysis+
-19) Calibrate crop yields against water balance outputs and other variables against and validate the coefficients. +
-Forecasting Yield+===6. The FAO water balance model and its crop forecasting indicators===
-20) Using equations derived under 19) above, compute crop yield maps and derive tables of agricultural statistics from the maps (the forecasts) +[[Chapter18|6.1.]] The FAO Water Balance Model. Monitoring crops.
-21) Prepare write-up of the products above as inputs to national crop monitoring bulletins+[[Chapter19|6.2.]] Gathering all data into the FAO AgroMetShell crop simulation software.
 + 
 +[[Chapter20|6.3.]] Run the Water Balance model. Understanding the output of the model.
 + 
 +===7. From water balance indicators to yield estimates===
 + 
 +[[Chapter22|7.1]]. Calibrate crop yields against water balance outputs and other variables.
 + 
 +[[Chapter23|7.2]]. Considerations when computing crop yield maps and create forecasts.
 + 
 +===8. Independent indicators===
 + 
 +[[Chapter21|8.1]]. Examples of other weather based indicators.
 + 
 +[[Chapter4|8.2.]] Remote Sensing and its role in crop forecasting.
 + 
 +===9. Data and information dissemination===
 + 
 +[[Chapter24|9.1]]. Prepare write-up of products for crop monitoring bulletins
 + 
 +[[Chapter44|9.2]]. Outline of a Weather Impact Bulletin
 + 
 +===10. Setting up a crop monitoring system===
 + 
 +[[Chapter27|10.1]]. Introduction
 + 
 +[[Chapter25|10.2]]. Resources required
 + 
 +[[Chapter26|10.3]]. How to get assistance
 + 
 + 
 +[[Glossary|Glossary]]
 + 
 + 
 + 
 +------------------------------------
 +</blockquote>

Current revision

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 yield forecasting with water balance calculations.

1.5. Introduction to CMBox software, data formats and GIS.

2. 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 reference evapotranspiration ET0.

3.3. Preparing and using the dekadal rainfall and ET0 database for crop monitoring

4. Gathering and calculating crop data

4.1. Defining cropping practices and conditions and preparation of polygons for main crop growing areas in the country.

4.2. Analysis of time series of climate and crops to identify trends. Detrending yield.

5. Techniques to use when data are unavailable

5.1. Introduction to Geostatistics and the spatial interpolation of weather and crop data.

5.2. Filling gaps in agricultural statistics.

6. The FAO water balance model and its crop forecasting indicators

6.1. The FAO Water Balance Model. Monitoring crops.

6.2. Gathering all data into the FAO AgroMetShell crop simulation software.

6.3. Run the Water Balance model. Understanding the output of the model.

7. From water balance indicators to yield estimates

7.1. Calibrate crop yields against water balance outputs and other variables.

7.2. Considerations when computing crop yield maps and create forecasts.

8. Independent indicators

8.1. Examples of other weather based indicators.

8.2. Remote Sensing and its role in crop forecasting.

9. Data and information dissemination

9.1. Prepare write-up of products for crop monitoring bulletins

9.2. Outline of a Weather Impact Bulletin

10. Setting up a crop monitoring system

10.1. Introduction

10.2. Resources required

10.3. How to get assistance


Glossary




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