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Application of Earth Observation data in Agricultural drought monitoring

Application of Earth Observation data in Agricultural drought monitoring. Farai Kuri University of Zimbabwe. Introduction. Drought traditionally measured using rainfall data Rainfall indices an indirect measure of drought Remote sensing drought indices are plant based

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Application of Earth Observation data in Agricultural drought monitoring

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  1. Application of Earth Observation data in Agricultural drought monitoring Farai Kuri University of Zimbabwe

  2. Introduction • Drought traditionally measured using rainfall data • Rainfall indices an indirect measure of drought • Remote sensing drought indices are plant based • EO is therefore a direct measure of plant performance

  3. Objectives • To test whether and to what extent EO based drought indices can predict maize yield in Zimbabwe

  4. Materials and Methods

  5. Study area • Study was based on the whole of Zimbabwe

  6. Data • Maize yield data courtesy of Ministry of Agriculture Mechanisation and Irrigation Development (2009-2010 & 2011-2012) • SPOT VGT NDVI long-term series AMESD Station at SIRDC and UZ (1998-2012)

  7. Data Analysis • Calculated Vegetation Condition Index (VCI) from SPOT NDVI series • VCI<36%, Dry dekad (1), Not Dry ( 0) • Frequency of dry dekads calculated for 2009-2010 & 2011-2012

  8. Relating Drought to Maize Yield • Regression was used to test whether and to what extent EO based dry dekads can predict maize yield.

  9. In-Situ Maize Yield 2011-12

  10. Frequency of Dry Dekads (2011-12 )

  11. Results

  12. In-Situ Maize Yield 2009-10

  13. Frequency of Dry Dekads (2009-10)

  14. Frequency of Dry Dekads (2009-10) Y=1/(0.25+0.02827*2.3038x R²=0.91 P-Value=0.001

  15. Conclusion • There is a significant relationship between frequency of RS based dry dekads and maize yield • Therefore frequency of RS based dry dekads can be used to evaluate impact of drought on yield or to estimate crop yield

  16. Thank You

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