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Improving global agricultural cropland though integration and expert elicitation

Improving global agricultural cropland though integration and expert elicitation. Steffen Fritz Linda See Christoph Perger. Activities of IIASA in the wider field of Early warning. Global/regional land use models – impact of certain policies on GHG emissions, impact on food prices

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Improving global agricultural cropland though integration and expert elicitation

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  1. Improving global agricultural cropland though integration and expert elicitation Steffen Fritz Linda See Christoph Perger

  2. Activities of IIASA in the wider field of Early warning • Global/regional land use models – impact of certain policies on GHG emissions, impact on food prices • Crop modeling using crop modelling (e.g. Epic model), comparison of ASCAT Soil Moisture with EPIC soil moisture • Evaluatingthe potential of mobile phones in cropland mapping and Early Warning applications

  3. Current State of maps and possible improvements in data collection • Global Land Cover and cropland maps in particular disagree • Lots of national maps have been produced which can be integrated (e.g. Africover) • Google earth offers enormous potential to cross check and validate maps • Mobile phones allow to collect data – e.g. pictures on the ground

  4. Disagreement between MODIS and GlobCover

  5. Disagreement between GLC-2000 and MODIS

  6. Geo-wiki.org www.geo-wiki.org

  7. Data Shared at the Workshop

  8. One Key Action from the Workshop • IIASA leads new subtask under the GEO Agriculture task, and work with the GEO Agriculture ‘Community of Practice’, Subtask: ‘Global land-use map’ • Cropland irrigated/non-irrigated • Rangelands • Crop Type • First step: Create a hybrid map of current cropland distribution.

  9. How to make a ‘hybrid product’ • Data integration • Kind of ensemble for cropland maps • Use national and sub-national statistics • Use experts via feedback on current maps to improve at certain locations • Integrate validation points collected from very high resolution (e.g. geo-wiki) and ground points/ pictures from mobile phones

  10. Fritz et al., 2011, A new calibrated cropland dataset for sub-saharan Africa, JGR

  11. Invitation to our Geo-wiki training session on:Improving African cropland using integration and expert elicitationThursday afternoon 14.00-17.00Prize: co-authorship

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