GIS/RS @ILRI An Notenbaert African Agriculture GIS Week 8-16 June 2010 Nairobi, Kenya
Attention! Attention!!! <ul><li>Index-Based Livestock Insurance </li></ul><ul><li>Down-scaled climate projections </li></u...
Attention! Attention!!! <ul><li>Index-Based Livestock Insurance </li></ul><ul><li>Down-scaled climate projections </li></ul>
IBLI <ul><li>Protecting Pastoralists from the Risk of  </li></ul><ul><li>Drought Related Livestock Mortality: </li></ul><u...
<ul><li>ASAL residents, particularly in Northern Kenya, confront harsh and volatile environments. </li></ul><ul><li>High l...
Impact of Drought on Livelihoods    The Marsabit Pilot <ul><li>Livestock is both the principal asset and source of income ...
<ul><li>Such risk imposes considerable economic and welfare costs </li></ul><ul><li>Sustainable  insurance can prevent thi...
Index Based Insurance <ul><li>New innovation in insurance avoids problems that make traditional insurance unprofitable for...
<ul><li>Need for a measure that is : </li></ul><ul><ul><li>Highly correlated with livestock mortality </li></ul></ul><ul><...
NASA NDVI Image Produced By: USGS-EROS Data Center. Source: Famine Early Warning System Network (FEWS-NET) <ul><li>NDVI Da...
Cumulative  differential NDVI
Derivation of livestock mortality index
Cumulative zNDVI & Temporal structure of IBLI contract Product Design
Attention! Attention!!! <ul><li>Index-Based Livestock Insurance </li></ul><ul><li>Down-scaled climate projections </li></ul>
<ul><li>Climate models (GCMs)    information on future global climate in response to the forcing provided by greenhouse g...
AOGCMs used in the downscaling work Randall et al. (2007)
Scheme of the down-scaling analysis MarkSim stochastic weather generator Observed climate grid at resolution of choice Gen...
Applications <ul><li>Daily data that are characteristic (to some extent) of the climatology of future time slices: </li></...
ILRI’s offering <ul><li>Livestock expertise </li></ul><ul><li>Targeting </li></ul><ul><li>Forward looking perspective </li...
Livestock Expertise <ul><li>Hardly any agriculture without livestock </li></ul><ul><li>ILRI is truly & explicitly integrat...
Targeting and Systems Classification Framework <ul><li>Characteristics: </li></ul><ul><li>Simple and map-able </li></ul><u...
Forward looking perspective <ul><li>Experience from past & current projects, lots of up-coming projects </li></ul><ul><ul>...
ILRI’s offering <ul><li>Livestock as an integral part of agricultural production systems </li></ul><ul><li>Targeting </li>...
Future beauties <ul><li>More collaboration </li></ul><ul><li>Wider application field </li></ul><ul><li>More and more users...
Example services  <ul><li>CGIAR and beyond </li></ul><ul><li>Targeting and priority setting </li></ul><ul><li>Earth Observ...
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10. ilri 9june2010

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  • So many good things going on in ILRI, a hard choice to make. I therefore decided to pick 2 quite contrasting applications: different time and spatial scales, different target audiences &amp; differently positioned on the research-development / output-impact-outcome gradient.
  • More details to be added
  • Some details about these projects to be added
  • 10. ilri 9june2010

    1. 1. GIS/RS @ILRI An Notenbaert African Agriculture GIS Week 8-16 June 2010 Nairobi, Kenya
    2. 2. Attention! Attention!!! <ul><li>Index-Based Livestock Insurance </li></ul><ul><li>Down-scaled climate projections </li></ul>Different (spatial and temporal) scales Different target audiences Different position along research-development gradient
    3. 3. Attention! Attention!!! <ul><li>Index-Based Livestock Insurance </li></ul><ul><li>Down-scaled climate projections </li></ul>
    4. 4. IBLI <ul><li>Protecting Pastoralists from the Risk of </li></ul><ul><li>Drought Related Livestock Mortality: </li></ul><ul><li>Piloting Index-Based Livestock Insurance </li></ul><ul><li>in Northern Kenya </li></ul><ul><li>http:// www.ilri.org/ibli / </li></ul>
    5. 5. <ul><li>ASAL residents, particularly in Northern Kenya, confront harsh and volatile environments. </li></ul><ul><li>High level of risk: </li></ul><ul><ul><li>Droughts, Diseases, Conflict </li></ul></ul><ul><li>Low levels of capacity: </li></ul><ul><ul><li>Infrastructure deficient </li></ul></ul><ul><ul><li>Few alternative livelihood </li></ul></ul><ul><ul><li>opportunities </li></ul></ul><ul><li>= A high degree of vulnerability to risk </li></ul>Managing Risk in the ASALs
    6. 6. Impact of Drought on Livelihoods The Marsabit Pilot <ul><li>Livestock is both the principal asset and source of income for the vast majority of ASAL residents </li></ul><ul><li>Drought is the single greatest cause of livestock mortality </li></ul><ul><li>Most drought related livestock mortality occurs under severe conditions </li></ul>Proportion of total income by source Livestock mortality by cause
    7. 7. <ul><li>Such risk imposes considerable economic and welfare costs </li></ul><ul><li>Sustainable insurance can prevent this </li></ul><ul><li>But can insurance be sustainably offered in the ASAL? </li></ul><ul><li>Conventional (individual) insurance unlikely to work, especially in small scale agro-pastoral sector: </li></ul><ul><ul><li>Transactions costs </li></ul></ul><ul><ul><li>Moral hazard/adverse selection </li></ul></ul>Insurance and Agricultural Development
    8. 8. Index Based Insurance <ul><li>New innovation in insurance avoids problems that make traditional insurance unprofitable for small, remote clients: </li></ul><ul><li>Policy holders paid based on external “index” that triggers payments to all insured clients </li></ul><ul><li>Suited for risks affecting a large number of people simultaneously and for which a suitable index exists. </li></ul><ul><ul><li>No transactions costs of measuring individual losses </li></ul></ul><ul><ul><li>Preserves effort incentives (no moral hazard) as no single individual can influence index. </li></ul></ul><ul><ul><li>Adverse selection does not matter as payouts do not depend on the riskiness of those who buy the insurance </li></ul></ul><ul><ul><li>Problem of “basis” risk (imperfect correlation loss – index) </li></ul></ul>
    9. 9. <ul><li>Need for a measure that is : </li></ul><ul><ul><li>Highly correlated with livestock mortality </li></ul></ul><ul><ul><li>Reliably and cheaply available for wide range of locations </li></ul></ul><ul><ul><li>Historically available (pricing) </li></ul></ul><ul><ul><li>NDVI ~ vegetation available for livestock to consume </li></ul></ul><ul><ul><ul><li>Predicted livestock mortality index </li></ul></ul></ul>
    10. 10. NASA NDVI Image Produced By: USGS-EROS Data Center. Source: Famine Early Warning System Network (FEWS-NET) <ul><li>NDVI Data </li></ul><ul><ul><li>Real-time available in 8×8 km 2 resolution </li></ul></ul><ul><ul><li>27 years available since late 1981 </li></ul></ul>NDVI February 2009, Dekad 3 Deviation of NDVI from long-term average February 2009, Dekad 3 Laisamis Cluster, zndvi (1982-2008) Historical droughts
    11. 11. Cumulative differential NDVI
    12. 12. Derivation of livestock mortality index
    13. 13. Cumulative zNDVI & Temporal structure of IBLI contract Product Design
    14. 14. Attention! Attention!!! <ul><li>Index-Based Livestock Insurance </li></ul><ul><li>Down-scaled climate projections </li></ul>
    15. 15. <ul><li>Climate models (GCMs)  information on future global climate in response to the forcing provided by greenhouse gas emissions. Very coarse: 200-300 km grid cells </li></ul><ul><li>GCMs cannot possibly reproduce the details of local weather (impacts of smallish water bodies, variations in elevation, etc). </li></ul><ul><li>So: </li></ul><ul><li>How to generate climate information at a scale that is useful for decision-making by policy makers, researchers, etc? </li></ul><ul><li>How to generate data useful to assess possible impacts on, for example, crop and pasture production? </li></ul>From global climate change models to local impacts
    16. 16. AOGCMs used in the downscaling work Randall et al. (2007)
    17. 17. Scheme of the down-scaling analysis MarkSim stochastic weather generator Observed climate grid at resolution of choice Generate daily data characteristic of a chosen “year” (time-slice) from 2000-2099 Applications WorldClim CRU etc Weather typing Jones, Thornton, Heinke (2009). Generating characteristic daily weather data using downscaled climate model data from IPCC’s Fourth Assessment
    18. 18. Applications <ul><li>Daily data that are characteristic (to some extent) of the climatology of future time slices: </li></ul><ul><ul><li>Rainfall </li></ul></ul><ul><ul><li>Maximum temp </li></ul></ul><ul><ul><li>Minimum temp </li></ul></ul><ul><li>With these, can derive or estimate other variables: </li></ul><ul><ul><li>Daily: Solar radiation (a function of Tmax, Tmin, lat, long) </li></ul></ul><ul><ul><li>Seasonal: Length of growing period, season start date, duration, ending date (simple water balance, soil data) </li></ul></ul><ul><li>Drive vegetation, crop, livestock models … </li></ul>http://futureclim.info/
    19. 19. ILRI’s offering <ul><li>Livestock expertise </li></ul><ul><li>Targeting </li></ul><ul><li>Forward looking perspective </li></ul>
    20. 20. Livestock Expertise <ul><li>Hardly any agriculture without livestock </li></ul><ul><li>ILRI is truly & explicitly integrating: </li></ul><ul><ul><li>Livestock </li></ul></ul><ul><ul><li>Crops </li></ul></ul><ul><ul><li>Poor people </li></ul></ul><ul><ul><li>NRM </li></ul></ul><ul><ul><li>Examples: our work on feeds </li></ul></ul><ul><ul><li>collaboration with IWMI (WUE, etc) </li></ul></ul>
    21. 21. Targeting and Systems Classification Framework <ul><li>Characteristics: </li></ul><ul><li>Simple and map-able </li></ul><ul><li>Differentiating: production systems, main agro-ecologies, key commodities, livelihood strategies </li></ul><ul><li>Distinguishing vulnerable and poor populations </li></ul><ul><li>Easy to relate to in relation to different centres/MPs activities </li></ul><ul><li>Process: </li></ul><ul><li>Step 1: mapping </li></ul><ul><li>Step 2: identification development challenges and researchable issues </li></ul><ul><li>Aim: </li></ul><ul><li>Articulate development challenges/system/MP </li></ul><ul><li>Target activities and interventions in MPs </li></ul><ul><li>Priority regions </li></ul><ul><li>Differentiate MP1.1 and MP1.2 </li></ul>
    22. 22. Forward looking perspective <ul><li>Experience from past & current projects, lots of up-coming projects </li></ul><ul><ul><li>Avian influenza - transport model, risk assessment </li></ul></ul><ul><ul><li>Global futures – comprehensive modeling environment </li></ul></ul><ul><ul><li>CC – Vulnerability, GHG inventories, adaptation, … </li></ul></ul><ul><ul><li>Healthy futures – decision support for water-borne diseases </li></ul></ul><ul><ul><li>Animal change </li></ul></ul><ul><ul><li>… </li></ul></ul>
    23. 23. ILRI’s offering <ul><li>Livestock as an integral part of agricultural production systems </li></ul><ul><li>Targeting </li></ul><ul><li>Forward looking perspective </li></ul>
    24. 24. Future beauties <ul><li>More collaboration </li></ul><ul><li>Wider application field </li></ul><ul><li>More and more users </li></ul><ul><li>Bigger datasets </li></ul><ul><li>… </li></ul><ul><li> sharing of data, tools, methodologies </li></ul><ul><li> more computing power </li></ul><ul><li> skill/capacity building </li></ul><ul><li> Towards a BECA-like GeoScience Hub? </li></ul>
    25. 25. Example services <ul><li>CGIAR and beyond </li></ul><ul><li>Targeting and priority setting </li></ul><ul><li>Earth Observation/GIS support to MPs </li></ul><ul><li>EO for Impact Assessment </li></ul><ul><li>Capacity Building </li></ul><ul><li>Knowledge Management </li></ul>

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