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RSA: Crop Estimates Overview AfriGEOSS - EOPower -GEOGLAM Southern Africa Agric Workshop

RSA: Crop Estimates Overview AfriGEOSS - EOPower -GEOGLAM Southern Africa Agric Workshop 08 May 2014. Fanie Ferreira. Wiltrud du Rand, Johan Malherbe, Eugene du Preez , George Chirima. National Crop Statistics Consortium. Roles and Responsibilities Agricultural Research Council

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RSA: Crop Estimates Overview AfriGEOSS - EOPower -GEOGLAM Southern Africa Agric Workshop

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  1. RSA: Crop Estimates Overview AfriGEOSS-EOPower-GEOGLAM Southern Africa Agric Workshop 08 May 2014 Fanie Ferreira Wiltrud du Rand, Johan Malherbe, Eugene du Preez, George Chirima

  2. National Crop Statistics Consortium • Roles and Responsibilities • Agricultural Research Council • Institute Soil Climate &Water: • Agro-metereology / Climatic conditoins • Summer Grain Institute: objective yield – maize • Field measurements: • Small Grain Institute: objective yield – wheat • Field measurements • SiQ • PICES (Producer Independent Crop Estimate System) • Statistical processing, surveys & interviews • GeoTerraImage • Satellite image processing • Crop type classifications

  3. Summer Maize Sequence • Area planted x Yield = Production • Maize: 3 M ha x 4 ton/ha = 12 M tons • Mapping update of Field Boundaries • Spot 5 Satellite imagery: complete Nov • Producer Independent Crop Estimate System • February & March – PICES Aerial Survey • Objective Yield Measurement • May – Field Visits • Intentions to plant & Actual Harvested • Oct / Nov – Telephonic survey • Crop Type Classification: July 2013 –May 2014

  4. Umlindi Report - Monthly Various products are derived from ARC-ISCW weather station data and remote sensing data • Data from the Coarse Resolution Imagery Databank (vegetation conditions) and from the National Agro-Climatology Databank (weather/climate conditions). Coarse resolution data received from GeoNetCast • Focus is on periods relevant for agricultural activities and areas important for crop production • Products developed from above-mentioned sources at the ARC-ISCW

  5. Rainfall amount, deviations and other derivatives for periods relevant to crop production

  6. Extreme conditions that may impact crop production

  7. Vegetation conditions as determined from various derivatives of the NDVI • Spatial products • Time series and comparisons with yields and vegetation conditions of previous years for various areas

  8. Use of satellite imagery SPOT5 LANDSAT 7/8, DMC ? In-season 2013/14 Previous seasons 2006/7/8/9/10/11/12/13 Satellite image calibration Field crop boundary PICES survey @ provincial level Satellite image analysis @ field level

  9. Stratification: Mapped Fields

  10. SA coverage: 14 million ha

  11. PICES Infrastructure

  12. PICES: crop verification • Vast improvement: survey efficiency • Support image classification • Statistical calculated of area • Additional points used for image training • Selected fields with identified crop types

  13. Rainfall

  14. Crop Calendar

  15. Freestate Province Winter 2007 Summer 2008

  16. Western Freestate

  17. Maize Comparison: 2007 vs 2008 • Spatial Distribution • Cultivated area • Crop types • District level comparison: • Maize area / district

  18. Maize Comparison: 2009 vs 2010 • Spatial Distribution • Cultivated area • Crop types • District level comparison: • Maize area / district

  19. Maize: Objective Yield • Approx 800 farms visited • Selected from PICES where Maize identified

  20. Maize: Objective Yield • Select 5 random points within field • Sample of 11 cobs harvested and measured

  21. Maize: Objective Yield

  22. Telephonic Survey • Randomlyselected farms • Indentify farmer and confirm location • Telephonic Survey during Oct / Nov • Phone farmer to conduct interview • Previous season • Area ( hectares ) of white maize • Area ( hectares ) of yellow maize • Actual yield harvested • Next season • Intention to plant: hectares for next season

  23. Summary: Crop Estimates #1 • DAFF – Crop Estimates Committee (CEC) • Field Boundaries • Annual updates of Centre Pivot irrigation fields • Stratification layer for PICES & other surveys • Deliver provincial stratification • PICES Survey (Cropped Area Estimate) • Geographic Random Selected Points • Used to calibrate crop type classification • Deliver report to DAFF CEC • Provincial summary of crops planted in ha

  24. Summary: Crop Estimates #2 • Objective Yield Measurement for Maize • Field visits during May (after senescence started) • Deliver report to DAFF CEC: • Yield per province for Maize • Telephonic Survey • Deliver report to DAFF CEC: • White / Yellow Maize split per province • Area (ha) per crop per province • Crop Type Classification • Trends: Cultivation and Crop Rotation Practices • Deliver report: District Crop Area Table

  25. Summary: Crop Estimates #3

  26. Summary: Crop Estimates #4

  27. Conclusion Statistical Geographic Sampling Frame Aircraft Technology Satellite imagery GiS PICES Team

  28. Thank you fanie.ferreira@geoterraimage.com

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