1. Global Monitoring for Food Security Stage II WMO/FAO/SADC Workshop, 14-18 November 2005 Food Security Information services in Africa Paolo Ragni Paolo.ragni@snamprogetti.eni.it

2. http://www.gmfs.info 2 GMESGMES –Global Monitoring for Environment and Security –Joint EC and ESA initiative –Stage II: Scaling Up Consolidated GMES Services GMFSGMFS –Global Monitoring for Food Security –Operational delivery of user-driven services –2 phases 2003-2004: Startup, consolidation & definition2003-2004: Startup, consolidation & definition 2005: transition year2005: transition year 2005-2008: Implementation2005-2008: Implementation GMFS Project - Context

3. http://www.gmfs.info 3Summary Call ESRIN/AO/1-4704/05/I-LG came out early February GMFS II Proposal submitted end march 29th. Negotiation since 14/6 Project Kick-off meeting 6/10 (Baseline). Partners KO meeting 14/10 Current proposed activities (Baseline): –Continental level: LR indicators (METEOSAT, SPOT-VGT, MSG) –National level: MR-HR crop status, area & dates, AMM, ground reference data WA: Senegal, EA: Sudan, Ethiopia, SA: Malawi, Zimbabwe (2005-06), –Support to FAO/WFP Crop & Food Suppy Assessment missions (CFSAM) Extensions (KO unknown) –2 more countries (Kenia, Mauritania, Burkina-Faso, Zambia) –Pasture/rangeland monitoring –Rainfall estimates, seasonal forecasts

4. http://www.gmfs.info 4 Users / Partners (SADC area) SADC-Regional Remote Sensing Unit (RRSU) MoAIFS, Malawi WFP FAO EC JRC MARS-FOOD FEWS Net CIMMYT ….

5. http://www.gmfs.info 5 Continental, regional and national services Work package A/B/C.1000 User Federation & strategic planning WP A/B/C.4000-08 Service portfolio evolution SP1, SP2, SP3, SP5, SP13 WP A/B/C.1100 User requirements – continental SP1 WP A/B/C.1200 National/regional User liaison SP3, SP9, SP6 WP A/B/C.1400 Promotion & sustainability SP1 WP A/B/C.1300 Training SP3, SP2, SP5, SP1, SP11 WP A.2200 Geonetwork setup SP5 WP A.2300 SLA’s and common access conditions SP1 WP A/B/C.2000 Service network coordination. SP1 SP1, SP5 WP A.2100 Common Service infrastructure SP4 WP A/B/C.3100 Continental scale WP A/B/C.3110 Crop state indicators: SPOT-VGT SP1 WP A/B/C.3120 FAST service SP13 WP A/B/C.323X Yield estimates SP11 SP11, SP3, SP12, SP9 WP A/B/C.324X SAR agricultural monitoring products SP2 WP A/B/C.325X Opt. agricultural monitoring products SP1 WP A.321X GIS ancillary data collection SP6 SP3, SP9, SP6 WP A/B/C.322X Fieldwork organization & execution SP3 SP3, SP9, SP11 WP A/B/C.326X Product Integration-validation SP3 SP3, SP9, SP6 WP A/B/C.3400 User monitoring & evaluation SP7, SP8 WP A/B/C.3300 CFSAM support & geonetwork database population SP13, SP5, SP1 WP A/B/C. 3000 Service Provision & qualification SP1 SP1, SP2, SP3, SP6, SP7, SP9, SP10, SP11, SP12, SP13 WP A/B/C.5000 Project Management SP1 WP A/B/C.320X Regional & national scale WP A/B/C.3130 Crop state indicators: MSG SP1 WP A/B/C.3140 Crop state indicators: MERIS SP1

6. http://www.gmfs.info 6 Regional & national EAST WEST SOUTH (EFTAS) (FMA) (ITA) LocalEFTAS MRVITO HRSARMAP LocalFMA Synoptics, ULG MRVITO HRSARMAP LocalITA (Synoptics*) MRVITO HRSARMAP * AMM first year Responsibilities by regional and national service

7. http://www.gmfs.info 7 WP A/B/C.3234 Yield estimates SP3 WP A/B/C.3244 SAR HR agricultural monitoring products SP2 WP A/B/C.3254 Opt. agricultural monitoring products SP1 WP A.3214 GIS ancillary data collection SP3 WP A/B/C.3224 Fieldwork organization & execution SP3 WP A/B/C.3264 Product validation SP3 SOUTHERN AFRICA: MALAWI WP A/B/C.1204 National/regional user liaison: MoAIFS, SADC-RRSU SP3 WP A.3245 SAR MR agricultural monitoring products SP2 WP A.3255 Opt. agricultural monitoring products SP1 WP A.3215 GIS ancillary data collection SP3 WP A.3265 Product validation SP3 WP A.1205 National/regional user liaison: FAO/WFP, SADC-RRSU SOUTHERN AFRICA: ZIMBABWE SP3 Specific tasks: national services

8. http://www.gmfs.info 8 GMFS - Products ProductsScaleData Resolution RainfallcontinentalMSG 5 km, AU Relative EvapotranspirationcontinentalMSG 5 km, AU Crop Yield ForecastcontinentalMSG 5 km, AU Vegetation Productivity IndicatorcontinentalSPOT VGT 1 km, AU Dry Matter Productivitynational MERIS FR (or MODIS) 250-300m AU Crop Extent at Emergence and Harvest Time national MERIS FR (or MODIS) ASAR WS Fieldwork 100 m 250-300m AU Crop Acreage at Emergence and Harvest Time sub-national ASAR AP Fieldwork 20m AU Crop Yield sub-national to national Field Work Meteo AMM Geodatabase AU CFSAM reports 20 countries combined

9. http://www.gmfs.info 9 Meteosat 7 Meteosat 8-9 30 Minutes 15 Minutes 3 Channels 12 Channels 2500 x 2500 pixels 5 km 3712 x 3712 pixels 3 km UK MET OFFICE New capabilities with MSG

10. http://www.gmfs.info 10 LoRes-INDICATORS: Vegetation Productivity Index - Every 10 days - Difference of vegetation growth with Historical year (Sannier et al.)

11. http://www.gmfs.info 11 Medium Resolution: Input data Envisat ASAR SARSynthetic Aperture Radar AgencyEuropean Space Agency Resolution150 m Swath400 Km Envisat MERIS MERISMedium Resolution Imaging Spectrometer AgencyEuropean Space Agency Resolution300 m Bands15 bands Swath1150 km MODIS MODISModerate Resolution Imaging Spectroradiometer AgencyNASA Swath2230 Km Resolution250 m

12. http://www.gmfs.info 12MeRes-INDICATORS: Dry Matter Productivity - Every 10 days (MERIS) / 16 days (MODIS) - ≈ Net Primary Productivity (measure of standing biomass)

13. http://www.gmfs.info 13 MeRes: Classification Green = agriculture Fieldwork Crop ‘probability’ map / hard classification Classes fairly well distinguishable Classification

14. http://www.gmfs.info 14 MR-optical / MR-ASAR integrated products Multitemporal MODIS 16-days DMP Multitemporal ASAR WS σ° product MODIS-ASAR Crop extent/acreage MODIS DMP coarse discrimination of cropped area ASAR WS better spatial resolution sensitivity to early crop stages Total crop extent/acreage at emergence

15. http://www.gmfs.info 15 Malawi, Temporal changes in planted areas Cropped area 10 December 27 January 26 December ASAR AP High spatial resolution. High sentivity to roughness changes. Planting/emergence/harvest

16. http://www.gmfs.info 16 Area Estimates: Input data - ENVISAT ASAR  15m, 150m resolution (AP & WS) - ENVISAT MERIS FR  15 bands  300 m - MODIS  250 m bands - Landsat TM / other - Fieldwork

17. http://www.gmfs.info 17 Area Estimates Crop Calendar Land practices High resolution Ground data, Meteo, Agro-meteorological Model Acreage and Yield at ar sub- national level Agro-ecological zones

18. http://www.gmfs.info 18 Acreage and Yield at 3rd level End member identification Agro-ecological zones Yield estimation at national level Trends Analysis Medium/Low resolution Area Estimates

19. http://www.gmfs.info 19 Yield Forecast: Agro-meteorological model

20. http://www.gmfs.info 20 Yield Forecast : Agro-meteorological model Millet yield forecasts 2003 relative to 10-year average Peanut yield forecasts 2003 relative to 10-year average Average = + 5% Average = - 6% Senegal - results 2003

21. http://www.gmfs.info 21 FAO – WFP GMFS Support to Crop and Food Supply Assessment missions - Provide remote sensing based maps to - cross-check information provide by the gov. departments - assess crop status - Provide bulletins / reports on - Crop forecasts - Evapotranspiration - Estimation of cropped areas

22. http://www.gmfs.info 22 FAO – WFP GMFS Support to Crop and Food Supply Assessment missions - Relative evapotranspiration maps & statistics - measure of crop water availability and crop growth rate. - Regional statistics & graphs - comparison of current, last years and 5 yr average

23. http://www.gmfs.info 23 FAO – WFP GMFS Support to Crop and Food Supply Assessment missions - Yield forecasts - Sorghum - Millet - Overall assessment & sub national analysis

24. http://www.gmfs.info 24 Collection of data, or useful information? LR, MR, HR, Optical, SAR data, AMM, ground data, historical statistics, Are all of them coherent? Interpretation of data requires time, knowledge, experience and can bring to misleading conclusions. END Users = Decision Makers End Users need: - Simple, straightforward products. No matter how complex is the technology behind them. - A good assessment of how much products are reliable

25. http://www.gmfs.info 25 Ground reference data Goals Calibration/validation of GMFS products Provide reference data to GMFS users for other applications Requirements Statistically sounded sampling methodology. Observe a well spatially distributed representative sample. Reduce as much as possible subjective choice of sampling units. All land covers included in a balanced proportion (cropland, pasture, shrubs, forest, artificial) Clear separation between training and validation datasets. Both in terms of selection and field survey methodology. Land cover/use nomenclature coherent with EO processing requirements, but also with national/international standards

26. http://www.gmfs.info 26 Spatial sampling frame definition sampling units: POINTS Systematic grid: representative and well distributed samples for any kind of application Clustering: reduced travelling time and costs Parameters : - distance between clusters - number of points per cluster - distance between points within a cluster Survey coverage full country / selected districts (HR products) Ground reference data

27. http://www.gmfs.info 27 Ground reference data Cropland-> field survey Mixed/dubious -> field survey Other land covers (Forest) -> no field survey Photointerpretation of HR imagery (e.g: Landsat) allows to classify most of not agricultural points Ground survey limited to cropped/mixed areas Optimisation by photointerpretation

28. http://www.gmfs.info 28 “A representative point is chosen typically at the corner of an agricultural field and ideally surrounded by other agricultural fields. The point should be at least 200m away from houses, roads, trees and other obstacles……. It is important that the non crop points are a bit away from any agricultural fields, when possible within a radius of 500-1000m there should be no agricultural activities” This approach of acquisition field data is optimised for the training of RS classifications, but it gives an optimistic assessment of the classification accuracy. It gives: the classification accuracy of fields that can be easily classified. If training dataset has specific requisites, they should not be applied to the validation dataset Ground reference data Selection criteria for training & validation are different.

29. http://www.gmfs.info 29 Data acquisitionPreprocessingproductsAnalysis & validation - ground reference data - statistical/trend analysis - Convergence of evidence Definitive product & Reporting ordering planning modes … atm., geo, Correction acreages veg. indicators … Feedback RS single service production-validation line Improve product integration/validation

30. http://www.gmfs.info 30 Data acquisitionPreprocessingproductsAnalysis, validation integration - ground reference data - statistical/trend analysis - tematic coherence - Spatial coherence - Convergence of evidence Single line products Assessment of products coherence and reliability 1 Integrated product ? Definitive product & Reporting Multiple service production-validation line Improve product integration/validation

31. http://www.gmfs.info 31 GMFS / Geonetwork Products Catalogue -Allows to catalogue data according to ISO standards - GMFS products not yet catalogued, to be implemented

32. http://www.gmfs.info 32 receive GMFS data products for food security collect GIS base data for the region, created by themselves and other organizations => further share/disseminate all data to other relevant organizations in their region and to GMFS partners => need for a catalog to realize this data dissemination function Role of regional centres for data sharing

33. http://www.gmfs.info 33 Spatial data management Share Common Base Maps Facilitate Access Share Information Quicker among Agencies Know the Data Source, Maintainer, Owner Why using a Catalog?

34. http://www.gmfs.info 34 Provide Information on Quality, Validity etc… Maintain Institutional Memory (Archive) Save Money and Time Make Better Decisions Why using a Catalog?

35. http://www.gmfs.info 35 standardised and decentralised spatial information management environment => web based Geographic Metadata Catalog System developed by FAO, WFP, UNEP, WHO, OCHA and CGIAR (GeoNetwork consortium) purpose to easily share geographically referenced thematic information between different FAO Units, other UN Agencies, NGO's and other institutions Open Source project GeoNetwork - described

36. http://www.gmfs.info 36 have a catalog at hand they can use for three purposes: –to manage the GMFS products, to search for particular products and access them in an easy way –to catalog in a systematic way the ancillary (GIS) data sets –to make own products available to other users within or outside their own organisation => being a GeoNetwork Node will allow the Regional Centres a better management of data resources and offer an improved facility for data sharing have a direct node to WFP-VAM, FAO and GMFS GeoNetwork regional nodes - benefits for the centres

37. http://www.gmfs.info 37 Set up jointly with WFP-VAM development, installation, training and support by GMFS and VAM financial and manpower contributions by all implementation partners close collaboration with the centres GeoNetwork regional nodes - implementation plan

38. http://www.gmfs.info 38 Schedule –identification of (external) local/regional GIS expert for the centre (due end of 2005) –close involvement of the centres’ leading staff to define installation and training schedule (due end of 2005) –purchase of HW/SW (due early 2006) installation and training foreseen in first half of 2006, carried out jointly by GMFS and VAM –IT staff and GIS expert by VAM, GIS expert by GMFS –share installation and training sessions –total duration of 10 days at each centre GeoNetwork regional nodes - implementation plan

39. http://www.gmfs.info 39 MeRes: Classification Statistics MODIS compared to Historical Stats (1990 – 1999) - Higher figures for MODIS compared to official statistics - Similar trends

40. http://www.gmfs.info 40 Project management (VITO) ServicesSupporting tasks Service delivery (VITO, EARS, UK Met, Sarmap, ITA, EFTAS, FMA, Synoptics, ULG) Service validation (ITA, EFTAS, FMA, users) Service evaluation (AVIA-GIS, ESYS, users) Geonetwork & infrastructure (GIM, TRASYS) Promotion (VITO, ITA, EFTAS, FMA) Information packaging (EARS, VITO, GIM) Advisory panel (user exec body, service strategy group) Consortium composition