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A Systemic View of Food Security for Early Warning Analysis: How Far Away?


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Gary Eilerts
Using Satellite Imagery for Early Warning of Productivity Constraints
Organized by the Food Security Portal (FSP)
OCT 31, 2019 - 11:00 AM TO 12:30 PM EDT

Published in: Government & Nonprofit
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A Systemic View of Food Security for Early Warning Analysis: How Far Away?

  1. 1. A systemic view of food security, for early warning analysis: how far away? Gary Eilerts Contractor/Consultant FEWS NET and Harvest
  2. 2. … all of these… Local Quality of the local rainy season Water source performance Rainy season labor shortages This seasonal harvest Food availability in the marketplace Market food price behavior Local patterns of conflict Crop and animal disease outbreaks Governance National, Regional, Global Climate modes and trends Sub-regional and national water demand International migration Global trends in food production Regional and global food trade patterns Global food demand and pricing impulses Regional conflicts, global terrorism Pandemics Incentives/penalties for good governance A systemic view of food security requires….
  3. 3. Evolution over time of Early Warning inputs Vacillating between local, national and global applications
  4. 4. Example: Informing the Local with Global Global Datasets helped characterize the Local, Sub-regional, and National
  5. 5. How close are we today? Need more Local-Global integrated datasets
  6. 6. Within the FEWS NET Data Warehouse “Crop” domain, the compilation of a Sub-National Agricultural Statistics Archive has been jointly supported by FEWS NET and Harvest. Sub-national ag statistics are now being compiled from original source documents
  7. 7. What Ag Stat data does it contain? No. of countries w/Ag Stats being uploaded 165 (166 if USA) Total years of data: 3,325 No. of sub-national ag stat reporting units: 14,390 No. of reported crops: 5,372 Final datapoint est. : 3,165,916 (w/o USA) Datapoint = place/season/crop/area/yield/production. Notable missing countries: Tajikistan, Uzbekistan, PDRK, Timor L’este, Gabon
  8. 8. To use ag stats with remote observations, we also need… Time-series ag stat data without accurate shapefiles linked to the actual location of each reporting unit on the earth, for every crop, every year and every season, has limited value. Solution? “Genealogical” profiles of the evolution in shapes/locations of each country’s reporting units over time, are now being completed. They will identify the evolution of “shapes” over time, and the right ones to overlay on the imagery to match with the ag stats. Preliminary research on the genealogies suggests that for ~96% of the historic reporting units, historic shapefiles can be inferred from current shapes, and generated on-the-fly for users as they select ag stats.
  9. 9. Example: A genealogy of reporting unit shapes over time
  10. 10. What will we do with it? Make better ag production estimates Analyze synchronous crop failures due to weather/climate Better understand food prices/production patterns Global yield gap map Inventory of national crop estimation procedures Build global bulk food trade database, merge w/ crop stats
  11. 11. Status? 125 countries loaded; remaining ones being cleaned before loading For access, contact Harvest and/or FEWS NET Data Warehouse
  12. 12. Thank you