DOI: 10.1016/j.jag.2013.12.010
Scopus记录号: 2-s2.0-84897401040
论文题名: Historical extension of operational NDVI products for livestock insurance in Kenya
作者: Vrieling A ; , Meroni M ; , Shee A ; , Mude A ; G ; , Woodard J ; , de Bie C ; A ; J ; M ; , Rembold F
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 28, 期: 1 起始页码: 238
结束页码: 251
语种: 英语
英文关键词: AVHRR
; Index insurance
; Intercalibration
; MODIS
; NDVI
; SPOT
Scopus关键词: arid environment
; AVHRR
; drought
; insurance system
; livestock
; MODIS
; mortality
; NDVI
; SPOT
; Kenya
英文摘要: Droughts 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 realtime, 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. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79784
Appears in Collections: 气候变化事实与影响
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作者单位: University of Twente, Faculty of Geo-Information Science and Earth Observation, P.O. Box 217, 7500 AE Enschede, Netherlands; Institute for Environment and Sustainability, Joint Research Centre, European Commission, Via E. Fermi 2749, I-21027 Ispra (VA), Italy; International Livestock Research Institute, P.O. Box 30709, Nairobi 00100, Kenya; Cornell University, Dyson School of Applied Economics and Management, 236 Warren Hall, Ithaca, NY 14853, United States
Recommended Citation:
Vrieling A,, Meroni M,, Shee A,et al. Historical extension of operational NDVI products for livestock insurance in Kenya[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,28(1)