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Agrometshell

Agrometshell. Workshop 15-17 September Rome. Peter Hoefsloot?. Dutch National Married, 2 children, 7 sheep Msc. In Agronomy/Meteorology/Comp. Science in Wageningen, The Netherlands Do management of geo-info projects for Dutch consultancy firm (Haskoning)

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Agrometshell

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  1. Agrometshell Workshop 15-17 September Rome

  2. Peter Hoefsloot? • Dutch National • Married, 2 children, 7 sheep • Msc. In Agronomy/Meteorology/Comp. Science in Wageningen, The Netherlands • Do management of geo-info projects for Dutch consultancy firm (Haskoning) • Have my own (little) company working for FAO and Dutch ministries writing software • 1989 – 1991 : Agrhymet, Niger • 1991 – 1994 : RRSU, Harare, Zimbabwe • Many missions (most SADC and CILSS countries, Djibouti)

  3. Parts of this demo • A bit of history • Objectives of AMS • AMS seen from different perspectives • General structure and functions • Demonstration

  4. A bit of history • Drought sub-Sahara Africa (mid-seventies) : desertification • 1974 - CILSS founded Agrhymet in Niamey (West Africa) • 1986 - Intergovernmental Authority on Development (IGAD) formed Intergovernmental Authority on Drought and Development (IGADD) for East Africa in Djibouti • Mid-eighties SADC – (Southern Africa) founded the Regional Early Warning Unit in Harare • Now - New frontiers : Afghanistan, IRAQ, Bangladesh

  5. Assisting “early warning” • FAO (United Nations) • GIEWS (Global Information and Early Warning System) and support for national and regional EW units • ARTEMIS (Africa Real Time Environmental Monitoring Information System) • USAID (United States) • FEWS - Famine Early Warning System • European Union • Many institutes • University of Venice , Italy • University of Reading, UK (TAMSAT) • ITC, The Netherlands • USGS, United States • (…)

  6. What do you need for EW? • Data and information • Methods and models • Software • Facilities (computers, communication) • Skilled staff

  7. Data for early warning • Stocks on staple foods • Pricing of foods on markets • Crop Yields • Weather data (e.g. rainfall) through GTS (worldwide) and Met Services (national) • Satellite data (mainly METEOSAT and NOAA) • “Static” support data : maps, census data, agro-ecological zones, soil maps

  8. Where do we get data from? • Ministries and other government institutions • Met Services • Many internet sources • ARTEMIS and AGROMET data information http://metart.fao.org/ • Africa Data Dissemination Service http://edcw2ks21.cr.usgs.gov/adds/

  9. Methods and models • NDVI (Vegetation Greenness Monitoring); 1x1 km and 7x7 km • Cold Cloud Duration (CCD) • Rainfall estimates (RFE) • Water Balance Models • Statistics • Interpolation

  10. Software • IDA- Windisp • Agman – Priceman – Spaceman (USGS) • FAOINDEX, FAOMET and others • ADDAPIX • spatial and temporal analysis of satellite imagery • MADAM • generation of multi-image statistics • IGT • GIS and interpolation tools for IDA • FAOCLIM • software and large agro-climatic database

  11. Why write EW software? • License free • Moderate computing requirements • Ease of use (WB in Excel is possible..) • Possibility to create new analysis methods (SEDI, ADDAPIX) • GIS systems require a lot of training, use large and complex data models, are not license free, use heavy computers

  12. AgrometShell

  13. AMS History • 1989 : Niamey Niger : SUIVI • 1992 : Harare Zimbabwe : SEDI and IGT • 1995 – 2000 : SEDI updates • From 2001 : AMS • Promotors and sponsors : FAO Rome, Aghrymet, REWU Harare, IGADD

  14. AgrometShell objectives • Facilitate monitoring of growing season • For national and regional EW units and international bodies like FAO • Available license free • Easy to use and well-documented • Bridging the gap between agromet, remote sensing and socio-economic datasets • Flexible toolbox to which others can contribute with code (e.g. Univ. of Louvain; interpol.) • Exchange with other relevant software • Windows rewrite of DOS software • AMS will not provide functions other packages offer

  15. AgrometShell in a nutshell • FAO Crop Water Balance model • Database for Agromet point data (SUIVI) • Interpolation (SEDI, Inverse distance, Co-Kriging etc…) • Statistics useful for Agromet • Provide conversion functions between data files • Viewer (every function ends with viewing results) • Automation • Some functions are in because unavailable in other EW software

  16. AMS technically • Programmed in Delphi (Pascal) • Contributions by others in form of DLL’s • Access database (through ADO) • Executable that does not require any other software • Share database on network

  17. Main Window

  18. DEMO 1 The agromet database

  19. SUIVI : Database for agromet data • Daily, Dekadal and Monthly weather station (point) data • Every operation through flexible stationlist • Add parameters easily • Flexible ASCII import

  20. Database technically • Database in Microsoft ACCESS 2000 format • Accessible from outside AMS • Very common database format • Query generator in Access • Database can be placed on network • Exchange of data with large database (Oracle SQL Server etc.) • Early versions had Paradox tables

  21. Demo • Inventory • Lists and base list • Parameters • Data entry • View data on map, graph, report • Formulas and calculation • Aggregation • Import from image and ASCII file

  22. DEMO 2 Calculating a Water Balance

  23. Water Balance • Model based on the work of Frere/Popov and Rene Gommes • Improvements so far: • Irrigation (amount at planting or dekad by dekad) • Phenological stages : initial, vegetative, flowering, ripening • Crop coefficients based on 9 rather than 4 graph points Daily Time Steps • More sets of crop coefficients per crop • “Run file” approach

  24. Water Balance (2) • AMS does not operate directly on database, but on ASCII files. • ASCII files are first exported from the database • Two possibilities: • 1. Monitoring (1 year; many stations) • 2. Risk Analysis (1 stations; many years)

  25. DEMO • Close look at crops • Dekadal and daily time steps • With and without irrigation • View results • Make images from results • Automation

  26. DEMO 3 Integrating and analyzing data

  27. Data integration (1) • Technically data come as: • Points • Areas • Images (or grids) • Images are best for analysis • Very visual (easy to check results) • A picture tells more than a 1000 words • Easy arithmetic with pixels

  28. Demo • Integrate Water Balance results with Yield data • WB results : point data • Yields : From ministry (area aggregated) • Turn both into images • Study the relation between Yield and Water Satisfaction Index geographically

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