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dc.contributorMeroni, Micheleen_US
dc.contributorShee, Apurbaen_US
dc.contributorMude, Andrewen_US
dc.contributorWoodard, Joshuaen_US
dc.contributorde Bie, C.A.J.M. (Kees)en_US
dc.contributorRembold, Felixen_US
dc.creatorVrieling, Antonen_US
dc.date2014-05-01en_US
dc.date.accessioned2016-02-14T09:30:51Z
dc.date.available2016-02-14T09:30:51Z
dc.identifierhttp://www.sciencedirect.com/science/article/pii/S0303243413001785en_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/E66FLHHen_US
dc.identifier.citationAnton Vrieling, Michele Meroni, Apurba Shee, Andrew Mude, Joshua Woodard, C. A. J. M. (Kees) de Bie, Felix Rembold. (1/5/2014). Historical extension of operational NDVI products for livestock insurance in Kenya. International Journal of Applied Earth Observation and Geoinformation, 28, pp. 238-251.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/4366
dc.description.abstractDroughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near real-time, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related insurance premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record (1981–2011) to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near-real time NDVI products: five from MODIS and one from SPOT-VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R2 statistics (leave-one-year-out) for the overlapping period 2002–2011. We found that division-specific models were more effective than a global model for linking the division-level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherElsevieren_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceInternational Journal of Applied Earth Observation and Geoinformation;28,(2014) Pagination 238,251en_US
dc.titleHistorical extension of operational NDVI products for livestock insurance in Kenyaen_US
dc.typeJournal Articleen_US
cg.creator.idMude, Andrew: 0000-0003-4903-6613en_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocinsuranceen_US
cg.subject.agrovoclivestocken_US
cg.contributor.centerUniversity of Twente - UT Netherlandsen_US
cg.contributor.centerEuropean Commission, Joint Research Center, Institute for Environment and Sustainability - EU-JRC-IESen_US
cg.contributor.centerInternational Livestock Research Institute - ILRIen_US
cg.contributor.centerCornell University - CORNELLen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.funderNot Applicableen_US
cg.date.embargo-end-date2015-03-15en_US
cg.coverage.regionEastern Africaen_US
cg.coverage.countryKEen_US
cg.contacta.vrieling@utwente.nlen_US
dc.identifier.statusLimited accessen_US
mel.impact-factor3.470en_US


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