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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

Agrometshell

Workshop 15-17 September Rome

peter hoefsloot
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)
parts of this demo
Parts of this demo
  • A bit of history
  • Objectives of AMS
  • AMS seen from different perspectives
  • General structure and functions
  • Demonstration
a bit of history
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
assisting early warning
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
    • (…)
what do you need for ew
What do you need for EW?
  • Data and information
  • Methods and models
  • Software
  • Facilities (computers, communication)
  • Skilled staff
data for early warning
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
where do we get data from
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/

methods and models
Methods and models
  • NDVI (Vegetation Greenness Monitoring); 1x1 km and 7x7 km
  • Cold Cloud Duration (CCD)
  • Rainfall estimates (RFE)
  • Water Balance Models
  • Statistics
  • Interpolation
software
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
why write ew software
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
ams history
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
agrometshell objectives
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
agrometshell in a nutshell
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
ams technically
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
demo 1

DEMO 1

The agromet database

suivi database for agromet data
SUIVI : Database for agromet data
  • Daily, Dekadal and Monthly weather station (point) data
  • Every operation through flexible stationlist
  • Add parameters easily
  • Flexible ASCII import
database technically
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
slide21
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
demo 2

DEMO 2

Calculating a Water Balance

water balance
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
water balance 2
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)
slide25
DEMO
  • Close look at crops
  • Dekadal and daily time steps
  • With and without irrigation
  • View results
  • Make images from results
  • Automation
demo 3

DEMO 3

Integrating and analyzing data

data integration 1
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
slide28
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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