[Day3] Agcommons Quickwin: Seeing is Believing


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Presented by Pierre C.S. Traore (ICRISAT) at the CGIAR-CSI Annual Meeting 2009: Mapping Our Future. March 31 - April 4, 2009, ILRI Campus, Nairobi, Kenya

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[Day3] Agcommons Quickwin: Seeing is Believing

  1. 1. yenko ye foko bo be be wule bibile wob e seeing is believing: unlocking precision agriculture in West African smallholder communities with very high resolution imagery nif yaab la sida gani ya kori ji AMEDD, Fuma Gaskiya, ICRISAT, IER, INERA, INRAN, KMG, SARI, UACT, UPN SIBWA – CSI – Nairobi, 02APR09
  2. 2. The idea • Precision ag. irrelevant to smallholders? FALSE • West African farmers = PA pioneers • Why would they want VHRI then? – We’re not sure, but they want it for sure – Field acreages, reveal less visible patterns of change – Map hotspots, bright spots, other spots – Field-level metrics for rainwater management – The “conscious” (and ambitious) side: decision support for productivity enhancement technology (field level) SIBWA – CSI – Nairobi, 02APR09
  3. 3. More ideas • The “unconscious” (or safe) side: discussion support for agricultural landscape design (community level) • Land tenure, community arbitration, decentralization • The urban analogy – why should VHRI concentrate on urban areas? At such a low cost, shouldn’t rural communities equally benefit from it? YES, THEY SHOULD • VHR mapping = precursor of land security & SLM (when you realize that you should own and invest) • VHR mapping = precursor of intensification (when space is limited and resources need better organization) • VHR mapping = precursor of demystification (when climate gets back into Pandora’s box) SIBWA – CSI – Nairobi, 02APR09
  4. 4. Objective(s) • Demonstrate the value of VHRI to help scale up a few quick-win productivity enhancement technologies in 6 smallholder communities across Burkina Faso, Ghana, Mali and Niger – Focus on the last 8 km – Candidate technologies: spatially optimized soil and water management practices – Show a variety of value-added products – Demonstrate real-world deployability and potential impact – Upload GIS datasets to shared online AgCommons repository – Publish metadata on GeoNetwork SIBWA – CSI – Nairobi, 02APR09
  5. 5. 4 phases, 7 tasks • 1: Organize resources: human, methods, tools • VHRIbox • VHRIex2 • 2: Share information at sites • ROLLout (x 6) • 3: CRT support functions • CRTtopo (x 5) • CRTverif (x 2) • 4: FEED and CAP • FEEDback (x 6) • FASTfwd (x 6) SIBWA – CSI – Nairobi, 02APR09
  6. 6. Task 1: Build site-specific VHR information containers and proto-maps (VHRIbox) • 1 information container and 1 set of proto-maps per site • Containers: geodatabase shells with initial matching ingredients. Will later host project generated information • Laminated printouts will crystallize initial VHRIbox content into proto-maps to engage VHR information exchange with farmers • Proto-maps: field boundaries overlaid on i/ VHR color composites, ii/ VHR NDVI, iii/ toposequence, slope class, iv/ hotspots (field-level NDVI anomaly), v/ field- level CRT potential • Deliverables: 6 containers, 6x5 proto-maps SIBWA – CSI – Nairobi, 02APR09
  7. 7. Task 2: Build a human interface for VHR information extraction and exchange (VHRIex2) • Assemble, train team of VHRI-conversant staff including 1 gender-aware quintet per site: junior local extension specialist literate in local languages, junior field GIS technician or student , farmer representative, senior local NGO or extension personnel, a scientist/backstopper • Equip team with standard interfacing tools and procedures to interact with different stakeholders • Deliverables: 6 quintets, 1-week crash retreat held for training on VHRIex2, 6 experimental protocols with toolkits, procedures, etc. uploaded SIBWA – CSI – Nairobi, 02APR09
  8. 8. Task 3: Roll out VHRI to farmer fields (ROLLout) • Sequential site exposure from wet to dry • proto-maps presented to FOs through focus groups following a stratified sampling protocol (tbd): i/ farmers exposed to proto-maps and productivity enhancement technologies and ii/ farmers exposed to productivity enhancement technologies only (control group) • Movies and on-site demos on productivity enhancement technologies • IER and AMEDD to lead • Deliverables: 6 sites covered from 01MAY-11JUN (1 week/site) SIBWA – CSI – Nairobi, 02APR09
  9. 9. Task 4: Derive field-level topography metrics to assess potential (CRTtopo) • develop semi-automated VHRI analysis method to extract dominant furrow azimuth in cattle plowed fields • Drape results on DEM to estimate average departure from the dominant field slope • Interpreted in terms of local priority for infiltration or drainage (function of field position on the toposequence) • only applies to sites with significant cattle plowing: all but Serkin Hawsa • Deliverables: 1 report on VHRI processing methods to assess field-level CRT potential, 5 field-level suitability maps (1 per site) SIBWA – CSI – Nairobi, 02APR09
  10. 10. Task 5: Test VHRI as an objective verification tool (CRTverif) • test the potential of VHRI for CRT impact assessment using historical measures of biomass productivity (NDVI- based) as an alternative to detailed household and field surveys • Compare 30 CRT-equipped farmer fields in Fansirakoro and Sukumba to control fields that lie in the same toposequence class • Deliverables: 1 report on VHRI processing methods to assess CRT impact in 2 sites SIBWA – CSI – Nairobi, 02APR09
  11. 11. Task 6: Collect user feedback on site (FEEDback) • deploy team in 6 sites to update, for all collaborating farmers: field boundaries, field ownership, cropping histories (field level), information resource allocation and management of abiotic stresses (household level). • For best tradeoff between crop differentiation and farmer time constraints, will take place towards peak biomass (September) • will involve collection of farmer feedback on productivity enhancement technologies they may have tested (or not), and on VHRI derived maps they may have used for purposes of technology targeting or for other purposes (or not). • largest concurrent deployment of human resources. • Deliverables: 6 sites covered concurrently (on-site presence: 1 month/site) SIBWA – CSI – Nairobi, 02APR09
  12. 12. Task 7: Forward maps of farmer screened technology to sites (FASTfwd) • Collate user feedback and encode information into site geodatabases, update proto-maps and ship back to FOs, LGAs, community leaders • Laminate individual A4 farm maps for collaborating farmers, synthesizing key learnings, recommendations for technology deployment • Elements of fine tuned information that will be forwarded: field acreage, intra-field hotspots of abiotic stress for targeting of (organic) fertilizer inputs, field fitness for CRT implementation (or other promising technology indentified during the course of the project). • Deliverables: 6x5 laminated maps finalized and forwarded to local communities. 6xn individual farmer maps finalized and forwarded to local recipients, All geospatial material generated during project lifetime uploaded for online serving. SIBWA – CSI – Nairobi, 02APR09
  13. 13. 2 productivity enhancement technologies in mind… or more? • Water management: CRT (+20%!) • ISFM: fertilizer micro-doses? Composting/manure? (+20%!) • Flexibility built-in for game time decisions depending on local experts, farmers SIBWA – CSI – Nairobi, 02APR09
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  23. 23. • Top: 2003 and cover (crop type) on pan imagery • Bottom: 2003 crop- specific estimates of mean biomass production, in g.m-2 on ASTER digital elevation model SIBWA – CSI – Nairobi, 02APR09
  24. 24. Multispectral false color composite (NIR reflectance appears in red) displaying cotton stand establishment in CRT (left) and non-CRT fields (right) on Diakaria Konaté's farm, 40 days after sowing SIBWA – CSI – Nairobi, 02APR09
  25. 25. Same, with regressed biomass estimates overlayed. Yellowish to greenish colors display field areas with at least 10 g.m-2 of crop dry matter equivalent SIBWA – CSI – Nairobi, 02APR09
  26. 26. Who and how many will be affected • ~3,000 farmers & dependents (est. 50 farms or households per site, 10 people per farm/household) • ~ 6 to 12 farmer organizations (1/site, plus women’s groups) • ~3 to 6 local NGOs • ~30 research personnel (scientists and extension staff included) • ~ 3 to 6 institutions from donor community and policy making arena SIBWA – CSI – Nairobi, 02APR09
  27. 27. Ideas for phase 2 (if 1 works) • Scale up: do the same in more communities – All 703 communes of Mali? ~2M USD – Larger selection in more countries? ~x M USD • Test new applications: – Test SOWO carbon accounting protocol for carbon trade projects – Scale down aflatoxin risk early warning products in Ghana, Mali (in partnership with CCLF-aflatoxin project) • Data-wise: – Get that GeoEye – Get that SRTM-30m SIBWA – CSI – Nairobi, 02APR09
  28. 28. Ideas for phase 2 – carbon accounting SIBWA – CSI – Nairobi, 02APR09
  29. 29. Ideas for phase 2 – carbon accounting SIBWA – CSI – Nairobi, 02APR09
  30. 30. Ideas for phase 2 – aflatoxin risk SIBWA – CSI – Nairobi, 02APR09
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