Remote sensing –Beyond images Mexico 14-15 December 2013 The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)

1. Remote sensing based drought
tolerant maize targeting in SSA
Remote sensing – Beyond Images
Kai Sonder, Jill Cairns, Olaf Erenstein, Girma Tesfahun, Kindie Tesfaye, Victor Hernandez, Dave Hodson
Mexico City, 14-15.12.2013

2. DTMA project: Drought tolerant maize for Africa
Mali
Nigeria
Uganda
Ghana
Benin
Angola
Zambia
Zimbabwe
Ethiopia
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Funded by Bill & Melinda Gates Foundation
3rd phase currently
CIMMYT and IITA and many partners
13 countries in West, East and Southern Africa
Develop drought tolerant maize germplasm
Strengthen small seed companies
Make DT materials available to farmers
Kenya
Tanzania
Mozambique
Malawi

3. WHY do this?
•Ex ante impact assessment
•Recommendations on areas for upscaling
•Fit breeding program to areas not currently covered
HOW to target the areas where DT material would
be most useful to farmers?
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Ideally use high res daily rainfall data but not really available in SSA
Failed seasons probability
Drought indices based on monthly data
Remote sensed data

4. Probability of failed seasons
Developed by Peter Jones
Based on a climate
generator (MARKSIM)
No time series
Doesn’t cover short or mild
droughts
Thornton et al. 2006 Mapping Climate Vulnerability
and Poverty in Africa.

5. Standardized Precipitation Index (SPI)
Based on rainfall only
Can be calculated at different time
scales
McKee et al., 1993
•Calculated for one month and three
month droughts for all of SSA
•Mild, Moderate, Severe, Extreme
droughts classified
•Using monthly CRU 3.1 data 19502010 (in theory 1900-2012)
•Doesn’t capture fully cover short
droughts
•WMO recommended
•Widely used

6. DSI (Drought Severity Index)
•Satellite image (MODIS) based (Mu et al., 2013)
•Mix of MODIS based NDVI and MODIS based ET/PET
•MOD16 ET/PET
MOD13 NDVI
•Annual and monthly and 8 day calculations possible
•Time series available currently 2000 – 2011
•Time series can be expanded

7. DSI Classes
Mu et al. 2013

8. DSI annual time series

9. Frequencies of moderate
and milder droughts in
Eastern Africa
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Applied to SPAM 2000 maize
production areas
Redo with SPAM 2005
Calculate maize areas exposed
to different types of drought
Estimation of number of rural
population in those areas
Estimation of poor in the areas

10. Next steps
•Evaluate 8 day product for short term events
•Validate with ground data from CIMMYT sites
•Relate DTMA on farm trials to drought events
•Compare performance of DT materials in different sites
•Evaluate for climate risk exposure studies with socio economists

11. Future possibilities
•Evaluate more remote sensing sources
•TRMM (Tropical Rainfall Measuring Mission)
•New generation GPM (Global precipitation Measurement)
•Soil moisture (eg ERS/MetOp, Vienna) Soil Water Index (SWI)
•Combine with crop models
http://www.ipf.tuwien.ac.at/radar/index.php?go=home

12. THANK YOU